Energies

Article

14 pages, 352 KiB

Open AccessEditor’s ChoiceArticle

Intraday Electricity Pricing of Night Contracts

by Marcel Kremer, Rüdiger Kiesel and Florentina Paraschiv

Energies 2020, 13(17), 4501; https://doi.org/10.3390/en13174501 - 1 Sep 2020

Cited by 11 | Viewed by 4382

This paper investigates the intraday electricity pricing of 15-min. contracts in night hours. We tailor a recently introduced econometric model with fundamental impacts, which is successful in describing the pricing of day contracts. Our estimation results show that the mean reversion and the [...] Read more.

This paper investigates the intraday electricity pricing of 15-min. contracts in night hours. We tailor a recently introduced econometric model with fundamental impacts, which is successful in describing the pricing of day contracts. Our estimation results show that the mean reversion and the positive price impact of neighboring contracts are generic features of the price formation process on the intraday market, independent of the time of day. Intraday auction prices have higher explanatory power for the pricing of night than day contracts, particularly, for the first and last 15-min. contract in a night hour. Intradaily updated forecasts of wind power infeed are the only significant fundamental factors for intraday electricity prices at night. Neither expected conventional capacities nor the slope of the merit order curve contribute to explaining price dynamics. Overall, we conclude that fundamentals lose in importance in night hours and the 15-min. intraday market is rather driven by price information. Full article

(This article belongs to the Special Issue Uncertainties and Risk Management in Competitive Energy Markets)

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24 pages, 4970 KiB

Open AccessEditor’s ChoiceArticle

Performance Comparison between Two Established Microgrid Planning MILP Methodologies Tested On 13 Microgrid Projects

by Michael Stadler, Zack Pecenak, Patrick Mathiesen, Kelsey Fahy and Jan Kleissl

Energies 2020, 13(17), 4460; https://doi.org/10.3390/en13174460 - 28 Aug 2020

Cited by 9 | Viewed by 3962

Abstract

Mixed Integer Linear Programming (MILP) optimization algorithms provide accurate and clear solutions for Microgrid and Distributed Energy Resources projects. Full-scale optimization approaches optimize all time-steps of data sets (e.g., 8760 time-step and higher resolutions), incurring extreme and unpredictable run-times, often prohibiting such approaches [...] Read more.

Mixed Integer Linear Programming (MILP) optimization algorithms provide accurate and clear solutions for Microgrid and Distributed Energy Resources projects. Full-scale optimization approaches optimize all time-steps of data sets (e.g., 8760 time-step and higher resolutions), incurring extreme and unpredictable run-times, often prohibiting such approaches for effective Microgrid designs. To reduce run-times down-sampling approaches exist. Given that the literature evaluates the full-scale and down-sampling approaches only for limited numbers of case studies, there is a lack of a more comprehensive study involving multiple Microgrids. This paper closes this gap by comparing results and run-times of a full-scale 8760 h time-series MILP to a peak preserving day-type MILP for 13 real Microgrid projects. The day-type approach reduces the computational time between 85% and almost 100% (from 2 h computational time to less than 1 min). At the same time the day-type approach keeps the objective function (OF) differences below 1.5% for 77% of the Microgrids. The other cases show OF differences between 6% and 13%, which can be reduced to 1.5% or less by applying a two-stage hybrid approach that designs the Microgrid based on down-sampled data and then performs a full-scale dispatch algorithm. This two stage approach results in 20–99% run-time savings. Full article

(This article belongs to the Special Issue Microgrids: Planning, Protection and Control)

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25 pages, 2428 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

New Reactive Power Compensation Strategies for Railway Infrastructure Capacity Increasing

by Vítor A. Morais, João L. Afonso, Adriano S. Carvalho and António P. Martins

Energies 2020, 13(17), 4379; https://doi.org/10.3390/en13174379 - 25 Aug 2020

Cited by 13 | Viewed by 3009

Abstract

In AC railway electrification systems, the impact of reactive power flow in the feeding voltage magnitude is one aspect contributing to the quality of supply degradation. Specifically, this issue results in limitations in the infrastructure capacity, either in the maximum number of trains [...] Read more.

In AC railway electrification systems, the impact of reactive power flow in the feeding voltage magnitude is one aspect contributing to the quality of supply degradation. Specifically, this issue results in limitations in the infrastructure capacity, either in the maximum number of trains and in maximum train power. In this paper, two reactive power compensation strategies are presented and compared, in terms of the theoretical railway infrastructure capacity. The first strategy considers a static VAR compensator, located in the neutral zone and compensating the substation reactive power, achieving a maximum capacity increase up to 50% without depending on each train active power. The second strategy adapts each train reactive power, achieving also a capacity increase around 50%, only with an increase of the train apparent power below 10%. With a smart metering infrastructure, the implementation of such compensation strategy is viable, satisfying the requirements of real-time knowledge of the railway electrification system state. Specifically, the usage of droop curves to adapt in real time the compensation scheme can bring the operation closer to optimality. Thus, the quality of supply and the infrastructure capacity can be increased with a mobile reactive power compensation scheme, based on a smart metering framework. Full article

(This article belongs to the Special Issue Power Quality in Electrified Transportation Systems)

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21 pages, 7211 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Power and Wind Shear Implications of Large Wind Turbine Scenarios in the US Central Plains

by Rebecca J. Barthelmie, Tristan J. Shepherd, Jeanie A. Aird and Sara C. Pryor

Energies 2020, 13(16), 4269; https://doi.org/10.3390/en13164269 - 18 Aug 2020

Cited by 22 | Viewed by 4707

Abstract

Continued growth of wind turbine physical dimensions is examined in terms of the implications for wind speed, power and shear across the rotor plane. High-resolution simulations with the Weather Research and Forecasting model are used to generate statistics of wind speed profiles for [...] Read more.

Continued growth of wind turbine physical dimensions is examined in terms of the implications for wind speed, power and shear across the rotor plane. High-resolution simulations with the Weather Research and Forecasting model are used to generate statistics of wind speed profiles for scenarios of current and future wind turbines. The nine-month simulations, focused on the eastern Central Plains, show that the power scales broadly as expected with the increase in rotor diameter (D) and wind speeds at hub-height (H). Increasing wind turbine dimensions from current values (approximately H = 100 m, D = 100 m) to those of the new International Energy Agency reference wind turbine (H = 150 m, D = 240 m), the power across the rotor plane increases 7.1 times. The mean domain-wide wind shear exponent (α) decreases from 0.21 (H = 100 m, D = 100 m) to 0.19 for the largest wind turbine scenario considered (H = 168 m, D = 248 m) and the frequency of extreme positive shear (α > 0.2) declines from 48% to 38% of 10-min periods. Thus, deployment of larger wind turbines potentially yields considerable net benefits for both the wind resource and reductions in fatigue loading related to vertical shear. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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23 pages, 1559 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Data for Urban Scale Building Energy Modelling: Assessing Impacts and Overcoming Availability Challenges

by Solène Goy, François Maréchal and Donal Finn

Energies 2020, 13(16), 4244; https://doi.org/10.3390/en13164244 - 17 Aug 2020

Cited by 22 | Viewed by 3243

Abstract

Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. This paper addresses this gap [...] Read more.

Data are essential to urban building energy models and yet, obtaining sufficient and accurate building data at a large-scale is challenging. Previous studies have highlighted that the data impact on urban case studies has not been sufficiently discussed. This paper addresses this gap by providing an analysis of the impact of input data on building energy modelling at an urban scale. The paper proposes a joint review of data impact and data accessibility to identify areas where future survey efforts should be concentrated. Moreover, a Morris sensitivity analysis is carried out on a large-scale residential case study, to rank input parameters by impact on space heating demand. This paper shows that accessible data impact the whole modelling process, from approach selection to model replicability. The sensitivity analysis shows that the setpoint and thermal characteristics were the most impactful for the case study considered. Solutions proposed to overcome availability and accessibility issues include organising annual workshops between data users and data owners, or developing online databases that could be populated on a volunteer-basis by data owners. Overall, overcoming data challenges is essential for the transition towards smarter cities, and will require an improved communication between all city stakeholders. Full article

(This article belongs to the Section G: Energy and Buildings)

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26 pages, 5353 KiB

Open AccessEditor’s ChoiceArticle

Power Resilience Enhancement of a Residential Electricity User Using Photovoltaics and a Battery Energy Storage System under Uncertainty Conditions

by Nallapaneni Manoj Kumar, Aritra Ghosh and Shauhrat S. Chopra

Energies 2020, 13(16), 4193; https://doi.org/10.3390/en13164193 - 13 Aug 2020

Cited by 44 | Viewed by 5190

Abstract

Even in today’s modern electric grid infrastructure, the uncertainty in the power supply is more often seen and is mainly due to power outages. The reasons for power outages might be any of the following: extreme weather events, asset failure, natural disasters, power [...] Read more.

Even in today’s modern electric grid infrastructure, the uncertainty in the power supply is more often seen and is mainly due to power outages. The reasons for power outages might be any of the following: extreme weather events, asset failure, natural disasters, power surges, acute accidents, and even operational errors by the workforce. Such uncertain situations are permitting us to think of it as a resilience problem. In most cases, the power outages may last from a few minutes to a few weeks, depending on the nature of the resilience issue and the power supply system (PSS) configuration. Therefore, it is imperative to understand and improve the resilience of a PSS. In this paper, a four-component resilience framework is proposed to study and compare the resilience of three different PSS configurations of residential electricity users (REUs) considering the realistic power outage conditions in the humid subtropical ecosystem. The proposed PSS configurations contain electric grid (EG), natural gas power generator (NGPG), battery energy storage (BES), and photovoltaics (PV) as the assets. The three PSS configurations of a REUs are EG + BES, EG + NGPG + BES, and EG + PV + BES, respectively, and in these, one REU is only the consumer and the other two REUs are prosumers. By using the proposed framework, simulations are performed on the three PSS configuration to understand the increasing load resiliency in the event of a power outage. Also, a comparative techno-economic and life cycle based environmental assessment is performed to select the most resilient PSS configuration among the EG + BES, EG + NGPG + BES, and EG + PV + BES for an REU. From the results, it was established that EG + PV + BES configuration would enhance the power resilience of an REU better than the other two PSS configurations. Besides, it is also observed that the identified resilient PSS configuration is cost-effective and environmentally efficient. Overall, the proposed framework will enable the REUs to opt for the PSS configuration that is resilient and affordable. Full article

(This article belongs to the Special Issue Assessment of Photovoltaic-Battery Systems)

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31 pages, 2982 KiB

Open AccessEditor’s ChoiceArticle

A GIS-Based Planning Approach for Urban Power and Natural Gas Distribution Grids with Different Heat Pump Scenarios

by Jolando M. Kisse, Martin Braun, Simon Letzgus and Tanja M. Kneiske

Energies 2020, 13(16), 4052; https://doi.org/10.3390/en13164052 - 5 Aug 2020

Cited by 11 | Viewed by 5106

Abstract

Next to building insulation, heat pumps driven by electrical compressors (eHPs) or by gas engines (geHPs) can be used to reduce primary energy demand for heating. They come with different investment requirements, operating costs and emissions caused. In addition, they affect both the [...] Read more.

Next to building insulation, heat pumps driven by electrical compressors (eHPs) or by gas engines (geHPs) can be used to reduce primary energy demand for heating. They come with different investment requirements, operating costs and emissions caused. In addition, they affect both the power and gas grids, which necessitates the assessment of both infrastructures regarding grid expansion planning. To calculate costs and CO

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emissions, 2000 electrical load profiles and 180 different heat demand profiles for single-family homes were simulated and heat pump models were applied. In a case study for a neighborhood energy model, the load profiles were assigned to buildings in an example town using public data on locations, building age and energetic refurbishment variants. In addition, the town’s gas distribution network and low voltage grid were modeled. Power and gas flows were simulated and costs for required grid extensions were calculated for 11% and 16% heat pump penetration. It was found that eHPs have the highest energy costs but will also have the lowest CO

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emissions by 2030 and 2050. For the investigated case, power grid investments of 11,800 euros/year are relatively low compared to gas grid connection costs of 70,400 euros/year. If eHPs and geHPs are combined, a slight reduction of overall costs is possible, but emissions would rise strongly compared to the all-electric case. Full article

(This article belongs to the Special Issue Integration of Renewables in Power Systems by Multi-Energy System Interaction)

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15 pages, 1549 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Education for Sustainable Energy: Comparison of Different Types of E-Learning Activities

by María Ángeles Martín-Lara and Nuria Rico

Energies 2020, 13(15), 4022; https://doi.org/10.3390/en13154022 - 4 Aug 2020

Cited by 4 | Viewed by 2971

Abstract

This paper reports a comparison of results obtained by using different e-learning strategies for teaching a biogas topic in two courses of the chemical engineering degree at the University of Granada. Particularly, four different asynchronous e-learning activities were carefully chosen: (1) noninteractive videos [...] Read more.

This paper reports a comparison of results obtained by using different e-learning strategies for teaching a biogas topic in two courses of the chemical engineering degree at the University of Granada. Particularly, four different asynchronous e-learning activities were carefully chosen: (1) noninteractive videos and audio files; (2) reading papers and discussion; (3) virtual tour of recommended websites of entities/associations/organizations working in the biogas sector; (4) PowerPoint slides and class notes. Students evaluated their satisfaction level (assessment) and teachers gave scores for evaluation exams (scores). We discuss the results from a quantitative point of view to suggest recommendations for improving e-learning implementations in education for sustainable energy. For dependent variables, reached scores and satisfaction assessment, we find the differences between means for students in two different academic years are no significant. In addition, there are no significant differences between means depending on the type of course. Significant differences appear for scores and satisfaction assessment between different activities. Finally, we deeply analyze the relationship between score and satisfaction assessment. The results show a positive correlation between assessment of e-learning activities and the score level reached by students. Full article

(This article belongs to the Special Issue Toward the Circular Economy in the Energy Sector: The Role of Higher Education)

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20 pages, 10547 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Occupancy Prediction Using Differential Evolution Online Sequential Extreme Learning Machine Model

by Jonas Bielskus, Violeta Motuzienė, Tatjana Vilutienė and Audrius Indriulionis

Energies 2020, 13(15), 4033; https://doi.org/10.3390/en13154033 - 4 Aug 2020

Cited by 11 | Viewed by 2963

Abstract

Despite increasing energy efficiency requirements, the full potential of energy efficiency is still unlocked; many buildings in the EU tend to consume more energy than predicted. Gathering data and developing models to predict occupants’ behaviour is seen as the next frontier in sustainable [...] Read more.

Despite increasing energy efficiency requirements, the full potential of energy efficiency is still unlocked; many buildings in the EU tend to consume more energy than predicted. Gathering data and developing models to predict occupants’ behaviour is seen as the next frontier in sustainable design. Measurements in the analysed open-space office showed accordingly 3.5 and 2.7 times lower occupancy compared to the ones given by DesignBuilder’s and EN 16798-1. This proves that proposed occupancy patterns are only suitable for typical open-space offices. The results of the previous studies and proposed occupancy prediction models have limited applications and limited accuracies. In this paper, the hybrid differential evolution online sequential extreme learning machine (DE-OSELM) model was applied for building occupants’ presence prediction in open-space office. The model was not previously applied in this area of research. It was found that prediction using experimentally gained indoor and outdoor parameters for the whole analysed period resulted in a correlation coefficient R² = 0.72. The best correlation was found with indoor CO₂ concentration—R² = 0.71 for the analysed period. It was concluded that a 4 week measurement period was sufficient for the prediction of the building’s occupancy and that DE-OSELM is a fast and reliable model suitable for this purpose. Full article

(This article belongs to the Section A: Sustainable Energy)

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27 pages, 2419 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Adaptive Energy Management in 5G Network Slicing: Requirements, Architecture, and Strategies

by Christian Tipantuña and Xavier Hesselbach

Energies 2020, 13(15), 3984; https://doi.org/10.3390/en13153984 - 2 Aug 2020

Cited by 10 | Viewed by 3378

Abstract

Energy consumption is a critical issue for the communications network operators, impacting deeply the cost of the services, as well as the ecological footprint. Network slicing architecture for 5G mobile communications enables multiple independent virtual networks to be created on top of a [...] Read more.

Energy consumption is a critical issue for the communications network operators, impacting deeply the cost of the services, as well as the ecological footprint. Network slicing architecture for 5G mobile communications enables multiple independent virtual networks to be created on top of a common shared physical infrastructure. Each network slice needs different types of resources, including energy, to fulfill the demands requested by each application, operator, or vertical market. The existing literature on network slicing is mainly targeted at the partition of network resources; however, the corresponding management of energy consumption is an unconsidered critical concern. This paper analyzes the requirements for an energy-aware 5G network slicing provisioning according to the 3GPP specifications, proposes an architecture, and studies the strategies to provide efficient energy consumption in terms of renewable and non-renewable sources. NFV and SDN technologies are the essential enablers and leverage the Internet of Things (IoT) connectivity provided by 5G networks. This paper also presents the technical 5G technology documentation related to the proposal, the requirements for adaptive energy management, and the Integer Linear Programming (ILP) formulation of the energy management model. To validate the improvements, an exact optimal algorithmic solution is presented and some heuristic strategies. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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21 pages, 6249 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

CFD Simulation and a Pragmatic Analysis of Performance and Emissions of Tomato Seed Biodiesel Blends in a 4-Cylinder Diesel Engine

by Rahim Karami, Mohammad G. Rasul and Mohammad M. K. Khan

Energies 2020, 13(14), 3688; https://doi.org/10.3390/en13143688 - 17 Jul 2020

Cited by 10 | Viewed by 3711

Abstract

Rising global concerns about global warming caused by pollution from excessive fossil fuels consumption, along with the high price of them in diesel engines, are the important reasons to search for fuels which is readily available and do not have destructive effects on [...] Read more.

Rising global concerns about global warming caused by pollution from excessive fossil fuels consumption, along with the high price of them in diesel engines, are the important reasons to search for fuels which is readily available and do not have destructive effects on the environment. Biodiesel is arguably the most appropriate and sustainable alternative to diesel fuel. Tomato seeds are one of the potential sources of biodiesel. They make up about 72% by weight of tomato waste, which contains an average of 24% oil. Tomato seed oil (TSO) can be used as a cheap and non-edible source of biodiesel. This paper investigated, both experimentally and numerically, the effects of different diesel–TSOB (tomato seed oil biodiesel) blends on the performance and emissions parameters of a four-cylinder, four-stroke, indirect injection diesel engine. The main goal of the paper was the simulation of the formation process of the emissions in the combustion chamber. The experimentally measured parameters such as torque, brake specific fuel consumption, exhaust gas temperature, nitrogen oxides, carbon monoxide, carbon dioxide, particulate matter, peak in-cylinder pressure, in-cylinder temperature and Reaction_Progress_Variable at different engine loads and speeds from 1200 to 2400 rpm at increments of 200 rpm are analyzed through ANOVA. The highest brake specific fuel consumption (BSFC) was observed for pure diesel and the lowest for the fuel blend with 10% biodiesel. The fuel blend with 20% biodiesel produced the highest torque. The engine was modeled using the AVL FIRE software. The model simulation results revealed that the highest nitrogen oxide (NOx) is produced in the throat of the combustion chamber to the top of the piston, the place of carbon dioxides (CO₂) formation is near the combustion chamber boundaries and the location of carbon monoxides (CO) formation is near the combustion chamber boundaries and at the center area of the top of the piston. These results also show that the particulate matter (PM) emissions are formed where the fuel is injected into the combustion chamber. Full article

(This article belongs to the Collection Feature Papers in Bio-Energy)

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18 pages, 4282 KiB

Open AccessEditor’s ChoiceArticle

Optimal Model for Energy Management Strategy in Smart Building with Energy Storage Systems and Electric Vehicles

by Francisco David Moya, José Luis Torres-Moreno and José Domingo Álvarez

Energies 2020, 13(14), 3605; https://doi.org/10.3390/en13143605 - 13 Jul 2020

Cited by 15 | Viewed by 3368

Abstract

The aim of this work was to develop an optimal model for an energy management strategy in a real micro-grid, which involves a smart building, a photovoltaic system with storage, and a plug-in full electric vehicle. A controller based on a mathematical algorithm [...] Read more.

The aim of this work was to develop an optimal model for an energy management strategy in a real micro-grid, which involves a smart building, a photovoltaic system with storage, and a plug-in full electric vehicle. A controller based on a mathematical algorithm was the core of each strategy, which directly acted on a relay board managing the interconnection between the different elements comprising the micro-grid. The development of an optimization model involving binary variables required an efficient code that achieved solutions in a short time. The analyzed case-study corresponded to the solar energy research center (CIESOL) smart building, a bioclimatic building, that is located at the University of Almería (Spain), designated to research in renewable energies. Using the methodologies described in this work, the total cost of the smart building energy consumption was minimized by decreasing the power supplied from the grid, especially at peak hours. Highlighting the use of a simple model that provided better performance than the current state of the art methodologies. The optimal model for energy management strategy demonstrated the advantages of using classical optimization techniques to solve this specific optimization problem, compared to a rule-based controller. The linear modeling was capable of producing a simple algorithm with less code development and a reduction in the computational effort. Full article

(This article belongs to the Special Issue Assessment of Photovoltaic-Battery Systems)

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30 pages, 1849 KiB

Open AccessEditor’s ChoiceArticle

Cities4ZERO Approach to Foresight for Fostering Smart Energy Transition on Municipal Level

by Merit Tatar, Tarmo Kalvet and Marek Tiits

Energies 2020, 13(14), 3533; https://doi.org/10.3390/en13143533 - 9 Jul 2020

Cited by 8 | Viewed by 4472

Abstract

Smart energy transition efforts at the municipal level are gaining importance and go far beyond implementing single projects. Decarbonising cities involves complex strategic planning and needs system level thinking and changes. This has been increasingly realised at the municipal level, but challenges remain [...] Read more.

Smart energy transition efforts at the municipal level are gaining importance and go far beyond implementing single projects. Decarbonising cities involves complex strategic planning and needs system level thinking and changes. This has been increasingly realised at the municipal level, but challenges remain regarding the tools, involvement of stakeholders and on the development of policies. The focus of the research is on the use of participatory foresight for fostering smart energy transition on a municipal level, the key benefits and success factors that participatory foresight brings, and the replicability of this approach. Within the novel Cities4ZERO framework, an overarching methodology for a smart urban decarbonisation transition, guiding cities through the process of developing the most appropriate strategies, plans, projects, as well as looking for the commitment of key local stakeholders for an effective transition–foresight framework, was developed and tested in five pilot cities. Foresight as applied within the Cities4ZERO framework creates a participatory process which brings stakeholders together to achieve unified scenarios, and a common vision for future urban decarbonisation strategies. The methodology is replicable and increases the quality of strategic energy planning by fostering long-term system thinking. Full article

(This article belongs to the Special Issue Integrated Sustainable Urban Development: Governance and Management Strategies for Connecting Urban Systems)

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18 pages, 4597 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Optimal Sizing of Fuel Cell Hybrid Power Sources with Reliability Consideration

by Adriano Ceschia, Toufik Azib, Olivier Bethoux and Francisco Alves

Energies 2020, 13(13), 3510; https://doi.org/10.3390/en13133510 - 7 Jul 2020

Cited by 8 | Viewed by 3095

Abstract

This paper addresses the issue of optimal sizing reliability applied to a fuel cell/battery hybrid system. This specific problem raises the global problem of strong coupling between hardware and control parameters. To tackle this matter, the proposed methodology uses nested optimization loops. Furthermore, [...] Read more.

This paper addresses the issue of optimal sizing reliability applied to a fuel cell/battery hybrid system. This specific problem raises the global problem of strong coupling between hardware and control parameters. To tackle this matter, the proposed methodology uses nested optimization loops. Furthermore, to increase the optimal design relevance, a reliability assessment of the optimal sizing set is introduced. This new paradigm enables showing the early impact of the reliability criteria on design choices regarding energetic performance index. It leads to a smart design methodology permitting to avoid complexity and save computing time. It considerably helps design engineers set up the best hybridization rate and enables practicing tradeoffs, including reliability aspects in the early design stages. Full article

(This article belongs to the Special Issue Design, Diagnosis and Control and Social Acceptance of Battery, Solar Cell and Fuel Cell System)

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13 pages, 4136 KiB

Open AccessEditor’s ChoiceArticle

An Electric Vehicle Charge Scheduling Approach Suited to Local and Supplying Distribution Transformers

by Teguh Kurniawan, Craig A. Baguley, Udaya K. Madawala, Suwarno, Nanang Hariyanto and Yuana Adianto

Energies 2020, 13(13), 3486; https://doi.org/10.3390/en13133486 - 6 Jul 2020

Cited by 7 | Viewed by 3230

Abstract

Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution [...] Read more.

Distribution networks with high electric vehicle (EV) penetration levels can experience transformer overloading and voltage instability issues. A charge scheduling approach is proposed to mitigate against these issues that suits smart home settings in residential areas. It comprises measurement systems located at distribution transformers that communicate directly with fuzzy logic controller (FLC) systems embedded within EV supply equipment (EVSE). This realizes a reduction in data processing requirements compared to more centralized control approaches, which is advantageous for distribution networks with large numbers of transformers and EV scheduling requests. A case study employing the proposed approach is presented. Realistic driver behavior patterns, EV types, and multivariate probabilistic modeling were used to estimate EV charging demands, daily travel mileage, and plug-in times. A Monte Carlo simulation approach was developed to obtain EV charging loads. The effectiveness of mitigation in terms of reducing distribution transformer peak load levels and losses, as well as improving voltage stability is demonstrated for a distribution network in Jakarta, Indonesia. Full article

(This article belongs to the Special Issue Bidirectional Energy Transfer Technologies for Vehicle-to-Grid and Other Vehicle-to-X Applications, and Solutions to Issues Caused by High Electric Vehicle Penetration Rates)

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27 pages, 3232 KiB

Open AccessEditor’s ChoiceArticle

Life Cycle Assessment of Classic and Innovative Batteries for Solar Home Systems in Europe

by Federico Rossi, Maria Laura Parisi, Sarah Greven, Riccardo Basosi and Adalgisa Sinicropi

Energies 2020, 13(13), 3454; https://doi.org/10.3390/en13133454 - 3 Jul 2020

Cited by 21 | Viewed by 4550

Abstract

This paper presents an environmental sustainability assessment of residential user-scale energy systems, named solar home systems, encompassing their construction, operation, and end of life. The methodology adopted is composed of three steps, namely a design phase, a simulation of the solar home systems’ [...] Read more.

This paper presents an environmental sustainability assessment of residential user-scale energy systems, named solar home systems, encompassing their construction, operation, and end of life. The methodology adopted is composed of three steps, namely a design phase, a simulation of the solar home systems’ performance and a life cycle assessment. The analysis aims to point out the main advantages, features, and challenges of lithium-ion batteries, considered as a benchmark, compared with other innovative devices. As the environmental sustainability of these systems is affected by the solar radiation intensity during the year, a sensitivity analysis is performed varying the latitude of the installation site in Europe. For each site, both isolated and grid-connected solar home systems have been compared considering also the national electricity mix. A general overview of the results shows that, regardless of the installation site, solid state nickel cobalt manganese and nickel cobalt aluminium lithium-ion batteries are the most suitable choices in terms of sustainability. Remarkably, other novel devices, like sodium-ion batteries, are already competitive with them and have great potential. With these batteries, the solar home systems’ eco-profile is generally advantageous compared to the energy mix, especially in on-grid configurations, with some exceptions. Full article

(This article belongs to the Special Issue Life Cycle Assessment of Sustainable Energy System)

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14 pages, 3346 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Dependencies for Determining the Thermal Conductivity of Moist Capillary-Porous Materials

by Abdrahman Alsabry, Beata Backiel-Brzozowska and Vadzim I. Nikitsin

Energies 2020, 13(12), 3211; https://doi.org/10.3390/en13123211 - 20 Jun 2020

Cited by 5 | Viewed by 2130

Abstract

A method of determining the effective thermal conductivity of moist capillary-porous materials has been proposed, in which calculations are carried out while taking into account all components of the system (solid, liquid and gas) at once. The method makes it easy to take [...] Read more.

A method of determining the effective thermal conductivity of moist capillary-porous materials has been proposed, in which calculations are carried out while taking into account all components of the system (solid, liquid and gas) at once. The method makes it easy to take into account the way water is distributed in the pore space of the material, either as isolated inclusions (drops) or as a continuous component, depending on the moisture content of the material. In the analysis of heat transport in moist capillary-porous materials, the theory of generalized conductivity is used and the structure of moist material is modeled using an ordered geometric structure consisting of identical unit cells in the form of a cube. An equation is obtained for calculating the effective conductivity of capillary-porous materials with isolated and continuous liquid inclusions, with adiabatic and isothermal division of the unit cell. The proposed method is compared to the previously proposed method of determining the effective thermal conductivity of moist materials, in which the three-component system is gradually reduced to a binary system, showing disadvantages of this method compared to the currently proposed. It has been shown that the proposed formulas grant the possibility of a sufficiently accurate prediction of experimental results using the experimental results of the thermal conductivity of moist aerated concrete. Full article

(This article belongs to the Section G: Energy and Buildings)

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37 pages, 7221 KiB

Open AccessEditor’s ChoiceArticle

Waste to Energy: Solid Fuel Production from Biogas Plant Digestate and Sewage Sludge by Torrefaction-Process Kinetics, Fuel Properties, and Energy Balance

by Kacper Świechowski, Martyna Hnat, Paweł Stępień, Sylwia Stegenta-Dąbrowska, Szymon Kugler, Jacek A. Koziel and Andrzej Białowiec

Energies 2020, 13(12), 3161; https://doi.org/10.3390/en13123161 - 18 Jun 2020

Cited by 12 | Viewed by 4248

Abstract

Sustainable solutions are needed to manage increased energy demand and waste generation. Renewable energy production from abundant sewage sludge (SS) and digestate (D) from biogas is feasible. Concerns about feedstock contamination (heavy metals, pharmaceuticals, antibiotics, and antibiotic-resistant bacteria) in SS and D limits [...] Read more.

Sustainable solutions are needed to manage increased energy demand and waste generation. Renewable energy production from abundant sewage sludge (SS) and digestate (D) from biogas is feasible. Concerns about feedstock contamination (heavy metals, pharmaceuticals, antibiotics, and antibiotic-resistant bacteria) in SS and D limits the use (e.g., agricultural) of these carbon-rich resources. Low temperature thermal conversion that results in carbonized solid fuel (CSF) has been proposed as sustainable waste utilization. The aim of the research was to investigate the feasibility of CSF production from SS and D via torrefaction. The CSF was produced at 200~300 °C (interval of 20 °C) for 20~60 min (interval 20 min). The torrefaction kinetics and CSF fuel properties were determined. Next, the differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA) of SS and D torrefaction were used to build models of energy demand for torrefaction. Finally, the evaluation of the energy balance of CSF production from SS and D was completed. The results showed that torrefaction improved the D-derived CSF’s higher heating value (HHV) up to 11% (p < 0.05), whereas no significant HHV changes for SS were observed. The torrefied D had the highest HHV of 20 MJ∙kg⁻¹ under 300 °C and 30 min, (the curve fitted value from the measured time periods) compared to HHV = 18 MJ∙kg⁻¹ for unprocessed D. The torrefied SS had the highest HHV = 14.8 MJ∙kg⁻¹ under 200 °C and 20 min, compared to HHV 14.6 MJ∙kg⁻¹ for raw SS. An unwanted result of the torrefaction was an increase in ash content in CSF, up to 40% and 22% for SS and D, respectively. The developed model showed that the torrefaction of dry SS and D could be energetically self-sufficient. Generating CSF with the highest HHV requires raw feedstock containing ~15.4 and 45.9 MJ∙kg⁻¹ for SS and D, respectively (assuming that part of feedstock is a source of energy for the process). The results suggest that there is a potential to convert biogas D to CSF to provide renewable fuel for, e.g., plants currently fed/co-fed with municipal solid waste. Full article

(This article belongs to the Special Issue Materials Recycling and Energy Use of Waste)

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20 pages, 4936 KiB

Open AccessEditor’s ChoiceArticle

A Real-Time Dynamic Fuel Cell System Simulation for Model-Based Diagnostics and Control: Validation on Real Driving Data

by Daniel Ritzberger, Christoph Hametner and Stefan Jakubek

Energies 2020, 13(12), 3148; https://doi.org/10.3390/en13123148 - 17 Jun 2020

Cited by 18 | Viewed by 4021

Abstract

Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demands poses significant challenges. Efficiency is to be [...] Read more.

Fuel cell systems are regarded as a promising candidate in replacing the internal combustion engine as a renewable and emission free alternative in automotive applications. However, the operation of a fuel cell stack fulfilling transient power-demands poses significant challenges. Efficiency is to be maximized while adhering to critical constraints, avoiding adverse operational conditions (fuel starvation, membrane flooding or drying, etc.) and mitigating degradation as to increase the life-time of the stack. Owing to this complexity, advanced model-based diagnostic and control methods are increasingly investigated. In this work, a real time stack model is presented and its experimental parameterization is discussed. Furthermore, the stack model is integrated in a system simulation, where the compressor dynamics, the feedback controls for the hydrogen injection and back-pressure valve actuation, and the purging strategy are considered. The resulting system simulation, driven by the set-point values of the operating strategy is evaluated and validated on experimental data obtained from a fuel cell vehicle during on-road operation. It will be shown how the internal states of the fuel cell simulation evolve during the transient operation of the fuel cell vehicle. The measurement data, for which this analysis is conducted, stem from a fuel cell research and demonstrator vehicle, developed by a consortium of several academic and industrial partners under the lead of AVL List GmbH. Full article

(This article belongs to the Special Issue Polymer Electrolyte Membrane Fuel Cell Systems)

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21 pages, 16732 KiB

Open AccessEditor’s ChoiceArticle

Partial Discharge Behaviour of a Protrusion in Gas-Insulated Systems under DC Voltage Stress

by Thomas Götz, Hannah Kirchner and Karsten Backhaus

Energies 2020, 13(12), 3102; https://doi.org/10.3390/en13123102 - 16 Jun 2020

Cited by 10 | Viewed by 3478

Abstract

High reliability, independence from environmental conditions, and the compact design of gas-insulated systems will lead to a wide application in future high voltage direct current (HVDC) transmission systems. Reliable operation of these assets can be ensured by applying meaningful and robust partial discharge [...] Read more.

High reliability, independence from environmental conditions, and the compact design of gas-insulated systems will lead to a wide application in future high voltage direct current (HVDC) transmission systems. Reliable operation of these assets can be ensured by applying meaningful and robust partial discharge diagnosis during development tests, acceptance tests, or operation. Therefore, the discharge behavior must be well understood. This paper aims to contribute to this understanding by investigating the partial discharge behavior of a distorted weakly inhomogeneous electrode arrangement in sulfur hexafluoride (SF₆) and synthetic air under high DC voltage stress. In order to get a better understanding, the partial discharge current is measured under the variation of the insulation gas pressure, the gas type, the electric field strength, and the voltage polarity. Derived from this, a classification of the different discharge types is performed. As a result, four different discharge types can be categorized depending on the experimental parameters: discharge impulses, discharge impulses with superimposed pulseless discharges, discharge impulses with superimposed pulseless discharges, and subsequent smaller discharges and pulseless discharges. Concluding suggestions for partial discharge measurements under DC voltage stress are given: recommendations for the necessary measurement time, the applied voltage and polarity, and useful measurement techniques. Full article

(This article belongs to the Special Issue Outdoor Insulation and Gas Insulated Switchgears)

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33 pages, 7279 KiB

Open AccessEditor’s ChoiceArticle

Unlocking the Effects of Fluid Optimization on Remaining Oil Saturation for the Combined Sulfate-Modified Water and Polymer Flooding

by Muhammad Tahir, Rafael E. Hincapie and Leonhard Ganzer

Energies 2020, 13(12), 3049; https://doi.org/10.3390/en13123049 - 12 Jun 2020

Cited by 7 | Viewed by 2720

Abstract

Interfacial interactions and wettability alteration remain as the main recovery mechanism when modified water is applied seeking to obtain higher oil recoveries. Fluid-fluid interaction could lead to the development of the called viscoelastic layer at the interface in oil-brine systems. This interfacial layer [...] Read more.

Interfacial interactions and wettability alteration remain as the main recovery mechanism when modified water is applied seeking to obtain higher oil recoveries. Fluid-fluid interaction could lead to the development of the called viscoelastic layer at the interface in oil-brine systems. This interfacial layer stabilizes thanks to the slow chemical interaction between oil polar compounds and salts in the brine. This study investigates the role of sulfate presence in injection brine that could possible lead to develop the interfacial viscoelastic layer and hence to contribute to the higher oil recovery. Furthermore, polymer flooding is performed in tertiary mode after brine flood to investigate/unlock the synergies and potential benefits of the hybrid enhanced oil recovery. Brine optimization is performed using the composition of two formation brines and four injection brines. Moreover, interfacial tension measurements and oil drop snap-off volume measurements are performed in parallel with the core flooding experiments to define the role of interfacial viscoelasticity as the recovery mechanism other than wettability alteration. Synthetic seawater spiked with double amount of sulfate depicted potential results of interfacial viscoelastic layer development and hence to contribute the higher oil recovery. Total oil recovery after secondary-mode using sulfate-modified water and tertiary-mode polymer flood was higher than the combination of seawater brine in secondary-mode and polymer flood in tertiary-mode. Nevertheless, experiments helped us concluding that the amount of sulfate added is a critical factor to obtain maximum oil recovery and to avoid pore-plugging problems. We, therefore, demonstrate that executing a detailed fluid optimization leads to promising laboratory results, potentially linked with an improvement in the economics of the field applications. Full article

(This article belongs to the Special Issue Enhanced Oil Recovery 2020)

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11 pages, 1809 KiB

Open AccessEditor’s ChoiceArticle

An Aqueous CaCl₂ Solution in the Condenser/Evaporator Instead of Pure Water: Application for the New Adsorptive Cycle “Heat from Cold”

by Ilya Girnik and Yuri Aristov

Energies 2020, 13(11), 2904; https://doi.org/10.3390/en13112904 - 5 Jun 2020

Cited by 5 | Viewed by 3085

Abstract

This paper addresses the analysis of the applicability of water as a working fluid for the new adsorptive heat transformation (AHT) cycle "Heat from Cold" (HeCol). The cycle proposed for cold countries operates at the ambient temperature below 0 °C. In this work, [...] Read more.

This paper addresses the analysis of the applicability of water as a working fluid for the new adsorptive heat transformation (AHT) cycle "Heat from Cold" (HeCol). The cycle proposed for cold countries operates at the ambient temperature below 0 °C. In this work, an aqueous solution of calcium chloride is proposed instead of liquid water to prevent the ice formation in the evaporator and condenser. The proposed water-based cycle is compared with the common methanol-based HeCol one in terms of the specific useful heat generated per cycle. The effect of the CaCl₂ solution on the cycle boundary pressures and its useful heat is studied both theoretically and experimentally. This approach can be extended to other adsorptive heat transformation cycles working at an evaporator or condenser temperature below 0 °C. Full article

(This article belongs to the Special Issue Adsorptive Systems for Heat Transformation and Heat Storage Applications)

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17 pages, 5197 KiB

Open AccessEditor’s ChoiceArticle

Comparative Building Energy Simulation Study of Static and Thermochromically Adaptive Energy-Efficient Glazing in Various Climate Regions

by Daniel Mann, Cindy Yeung, Roberto Habets, Zeger Vroon and Pascal Buskens

Energies 2020, 13(11), 2842; https://doi.org/10.3390/en13112842 - 3 Jun 2020

Cited by 28 | Viewed by 6422

Abstract

The building sector contributes approximately one third of the total energy consumption worldwide. A large part of this energy is used for the heating and cooling of buildings, which can be drastically reduced by use of energy-efficient glazing. In this study, we performed [...] Read more.

The building sector contributes approximately one third of the total energy consumption worldwide. A large part of this energy is used for the heating and cooling of buildings, which can be drastically reduced by use of energy-efficient glazing. In this study, we performed building energy simulations on a prototypical residential building, and compared commercially available static (low-e, solar IR blocking) to newly developed adaptive thermochromic glazing systems for various climate regions. The modeling results show that static energy-efficient glazing is mainly optimized for either hot climates, where low solar heat gain can reduce cooling demands drastically, or cold climates, where low-e properties have a huge influence on heating demands. For intermediate climates, we demonstrate that adaptive thermochromic glazing in combination with a low-e coating is perfectly suited. The newly developed thermochromic glazing can lead to annual energy consumption improvement of up to 22% in comparison to clear glass, which exceeds all other glazing systems. Furthermore, we demonstrate that in the Netherlands the use of this new glazing system can lead to annual cost savings of EU 638 per dwelling (172 m², 25% window façade), and to annual nationwide CO₂ savings of 4.5 Mt. Ergo, we show that further development of thermochromic smart windows into market-ready products can have a huge economic, ecological and societal impact on all intermediate climate region in the northern hemisphere. Full article

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14 pages, 1275 KiB

Open AccessEditor’s ChoiceArticle

Machine Learning Modeling of Horizontal Photovoltaics Using Weather and Location Data

by Christil Pasion, Torrey Wagner, Clay Koschnick, Steven Schuldt, Jada Williams and Kevin Hallinan

Energies 2020, 13(10), 2570; https://doi.org/10.3390/en13102570 - 19 May 2020

Cited by 17 | Viewed by 4757

Abstract

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal [...] Read more.

Solar energy is a key renewable energy source; however, its intermittent nature and potential for use in distributed systems make power prediction an important aspect of grid integration. This research analyzed a variety of machine learning techniques to predict power output for horizontal solar panels using 14 months of data collected from 12 northern-hemisphere locations. We performed our data collection and analysis in the absence of irradiation data—an approach not commonly found in prior literature. Using latitude, month, hour, ambient temperature, pressure, humidity, wind speed, and cloud ceiling as independent variables, a distributed random forest regression algorithm modeled the combined dataset with an R² value of 0.94. As a comparative measure, other machine learning algorithms resulted in R² values of 0.50–0.94. Additionally, the data from each location was modeled separately with R² values ranging from 0.91 to 0.97, indicating a range of consistency across all sites. Using an input variable permutation approach with the random forest algorithm, we found that the three most important variables for power prediction were ambient temperature, humidity, and cloud ceiling. The analysis showed that machine learning potentially allowed for accurate power prediction while avoiding the challenges associated with modeled irradiation data. Full article

(This article belongs to the Section A2: Solar Energy and Photovoltaic Systems)

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24 pages, 2029 KiB

Open AccessEditor’s ChoiceArticle

A Coordination Mechanism For Reducing Price Spikes in Distribution Grids

by Shantanu Chakraborty, Remco Verzijlbergh, Kyri Baker, Milos Cvetkovic, Laurens De Vries and Zofia Lukszo

Energies 2020, 13(10), 2500; https://doi.org/10.3390/en13102500 - 15 May 2020

Cited by 3 | Viewed by 2789

Abstract

Recently, given the increased integration of renewables and growing uncertainty in demand, the wholesale market price has become highly volatile. Energy communities connected to the main electricity grid may be exposed to this increasing price volatility. Additionally, they may also be exposed to [...] Read more.

Recently, given the increased integration of renewables and growing uncertainty in demand, the wholesale market price has become highly volatile. Energy communities connected to the main electricity grid may be exposed to this increasing price volatility. Additionally, they may also be exposed to local network congestions, resulting in price spikes. Motivated by this problem, in this paper, we present a coordination mechanism between entities at the distribution grid to reduce price volatility. The mechanism relies on the concept of duality theory in mathematical programming through which explicit constraints can be imposed on the local electricity price. Constraining the dual variable related to price enables the quantification of the demand-side flexibility required to guarantee a certain price limit. We illustrate our approach with a case study of a congested distribution grid and an energy storage system as the source of the required demand-side flexibility. Through detailed simulations, we determine the optimal size and operation of the storage system required to constrain prices. An economic evaluation of the case study shows that the business case for providing the contracted flexibility with the storage system depends strongly on the chosen price limit. Full article

(This article belongs to the Special Issue Flexibility in Distribution Systems from EVs and Batteries)

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24 pages, 4098 KiB

Open AccessEditor’s ChoiceArticle

The Role of Powertrain Electrification in Achieving Deep Decarbonization in Road Freight Transport

by Juan C. González Palencia, Van Tuan Nguyen, Mikiya Araki and Seiichi Shiga

Energies 2020, 13(10), 2459; https://doi.org/10.3390/en13102459 - 13 May 2020

Cited by 31 | Viewed by 4504

Abstract

Decarbonizing road freight transport is difficult due to its reliance on fossil fuel internal combustion engine vehicles (ICEVs). The role of powertrain electrification in achieving deep decarbonization in road freight transport was studied using a vehicle stock turnover model, focusing on Japan. Twelve [...] Read more.

Decarbonizing road freight transport is difficult due to its reliance on fossil fuel internal combustion engine vehicles (ICEVs). The role of powertrain electrification in achieving deep decarbonization in road freight transport was studied using a vehicle stock turnover model, focusing on Japan. Twelve vehicle types were considered; combining four powertrains, ICEV, hybrid electric vehicle (HEV), battery electric vehicle (BEV) and fuel cell electric vehicle (FCEV); and three vehicle size classes, normal, compact and mini-sized vehicles. A scenario-based approach was used; considering a Base scenario, and three alternative scenarios targeting powertrain electrification. Between 2012 and 2050, tank to wheel CO₂ emissions decrease 42.8% in the Base scenario, due to the reduction of vehicle stock, the improvement of vehicle fuel consumption and the adoption of HEVs. Diffusion of FCEVs in normal vehicles and BEVs in compact and mini-sized vehicles achieves the largest tank to wheel CO₂ emissions reductions, up to 44.6% compared with the 2050 baseline value. The net cash flow is positive over the whole time horizon, peaking at 6.7 billion USD/year in 2049 and reaching 6.6 billion USD/year by 2050. Powertrain electrification is not enough to achieve any of the CO₂ emissions reduction targets in road freight transport. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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19 pages, 5463 KiB

Open AccessEditor’s ChoiceArticle

The Application of Hierarchical Clustering to Power Quality Measurements in an Electrical Power Network with Distributed Generation

by Michał Jasiński, Tomasz Sikorski, Zbigniew Leonowicz, Klaudiusz Borkowski and Elżbieta Jasińska

Energies 2020, 13(9), 2407; https://doi.org/10.3390/en13092407 - 11 May 2020

Cited by 16 | Viewed by 3393

Abstract

This article presents the application of data mining (DM) to long-term power quality (PQ) measurements. The Ward algorithm was selected as the cluster analysis (CA) technique to achieve an automatic division of the PQ measurement data. The measurements were conducted in an electrical [...] Read more.

This article presents the application of data mining (DM) to long-term power quality (PQ) measurements. The Ward algorithm was selected as the cluster analysis (CA) technique to achieve an automatic division of the PQ measurement data. The measurements were conducted in an electrical power network (EPN) of the mining industry with distributed generation (DG). The obtained results indicate that the application of the Ward algorithm to PQ data assures the division with regards to the work of the distributed generation, and also to other important working conditions (e.g., reconfiguration or high harmonic pollution). The presented analysis is conducted for the area-related approach—all measurement point data are connected at an initial stage. The importance rate was proposed in order to indicate the parameters that have a high impact on the classification of the data. Another element of the article was the reduction of the size of the input database. The reduction of input data by 57% assured the classification with a 95% agreement when compared to the complete database classification. Full article

(This article belongs to the Special Issue Signal Analysis in Power Systems)

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18 pages, 3037 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

The Application of Molten Salt Energy Storage to Advance the Transition from Coal to Green Energy Power Systems

by Wojciech Kosman and Andrzej Rusin

Energies 2020, 13(9), 2222; https://doi.org/10.3390/en13092222 - 2 May 2020

Cited by 15 | Viewed by 3102

Abstract

The paper presents technical solutions for a power grid that undergoes the elimination of a significant number of coal-based power generating units. The purpose of the solutions is to adapt the existing machines with sufficient lifespans to the new operating conditions. In particular [...] Read more.

The paper presents technical solutions for a power grid that undergoes the elimination of a significant number of coal-based power generating units. The purpose of the solutions is to adapt the existing machines with sufficient lifespans to the new operating conditions. In particular these include steam turbines. The steam turbines’ cycles may be extended with energy storage systems based on a molten salt. This allows to increase the flexibility of the power generating units while maintaining the largest possible efficiency of the power generation. The solutions presented here allow to connect the steam turbines cycles to renewable energy sources and reduce the overall number of the units that create the fundamental layer of the power grid. The analysis of the solutions involves numerical modeling. The paper describes the assumptions and the results of the modeling for chosen cases of the modernization. The researched considered a number of options that differed in the investment costs and the resulting performance. Full article

(This article belongs to the Special Issue Advanced Mathematical Modeling Technology for Heat Storage and Conversion Systems)

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20 pages, 1494 KiB

Open AccessEditor’s ChoiceArticle

Energy Vision Strategies for the EU Green New Deal: A Case Study of European Cities

by David Maya-Drysdale, Louise Krog Jensen and Brian Vad Mathiesen

Energies 2020, 13(9), 2194; https://doi.org/10.3390/en13092194 - 2 May 2020

Cited by 27 | Viewed by 5310

Abstract

There are three strategic levels for successful energy planning in cities: 1) Integration strategy for integrating energy planning into urban planning institutions; 2) Practice strategy for developing suitable energy planning practices in urban planning institutions, and 3) Vision strategy for the creation and [...] Read more.

There are three strategic levels for successful energy planning in cities: 1) Integration strategy for integrating energy planning into urban planning institutions; 2) Practice strategy for developing suitable energy planning practices in urban planning institutions, and 3) Vision strategy for the creation and integration of energy visions and scenarios required for long-term decarbonisation. The vision strategy is critical but not well researched and is the focus of this article. Using Strategic Energy Planning (SEP) as an analytical framework, the vision strategy of eight forerunner European cities are analysed. Some critical elements of SEP include the use of long-term targets, holistic energy system thinking, and retention of scenarios. The results indicate that the level of understanding and practice of the vision strategy is still deficient in the cities. Cities often use the practice of urban planning, which does not fit very well with energy planning, particularly with the vision strategy. The energy planning in the cities mostly focuses on shorter-term goals and actions, and they often abandon energy scenarios once extracted. However, through trial and error, some cities are finding ways forward. The article concludes with several recommendations, particularly that cities need to see scenarios as retainable long-term servants providing information desired by the planner, rather than serving as a guide to the planner. Full article

(This article belongs to the Special Issue Municipal Energy System Planning: New Approaches, Applications and Future Research Needs)

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18 pages, 3616 KiB

Open AccessEditor’s ChoiceArticle

The Effect of Renewable and Nuclear Energy Consumption on Decoupling Economic Growth from CO₂ Emissions in Spain

by Mariola Piłatowska, Andrzej Geise and Aneta Włodarczyk

Energies 2020, 13(9), 2124; https://doi.org/10.3390/en13092124 - 25 Apr 2020

Cited by 72 | Viewed by 6172

Abstract

This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the [...] Read more.

This study examines the relationship between renewable and nuclear energy consumption, carbon dioxide emissions and economic growth by using the Granger causality and non-linear impulse response function in a business cycle in Spain. We estimate the threshold vector autoregression (TVAR) model on the basis of annual data from the period 1970–2018, which are disaggregated into quarterly data to obtain robust empirical results through avoiding a sample size problem. Our analysis reveals that economic growth and CO₂ emissions are positively correlated during expansions but not during recessions. Moreover, we find that rising nuclear energy consumption leads to decreased CO₂ emissions during expansions, while the impact of increasing renewable energy consumption on emissions is negative but insignificant. In addition, there is a positive feedback between nuclear energy consumption and economic growth, but unidirectional positive causality running from renewable energy consumption to economic growth in upturns. Our findings do indicate that both nuclear and renewable energy consumption contribute to a reduction in emissions; however, the rise in economic activity, leading to a greater increase in emissions, offsets this positive impact of green energy. Therefore, a decoupling of economic growth from CO₂ emissions is not observed. These results demand some crucial changes in legislation targeted at reducing emissions, as green energy alone is insufficient to reach this goal. Full article

(This article belongs to the Section C: Energy Economics and Policy)

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25 pages, 7419 KiB

Open AccessEditor’s ChoiceArticle

Wave Power Absorption by Arrays of Wave Energy Converters in Front of a Vertical Breakwater: A Theoretical Study

by Dimitrios N. Konispoliatis and Spyridon A. Mavrakos

Energies 2020, 13(8), 1985; https://doi.org/10.3390/en13081985 - 17 Apr 2020

Cited by 19 | Viewed by 3049

Abstract

The present paper deals with the theoretical evaluation of the efficiency of an array of cylindrical Wave Energy Converters (WECs) having a vertical symmetry axis and placed in front of a reflecting vertical breakwater. Linear potential theory is assumed, and the associated diffraction [...] Read more.

The present paper deals with the theoretical evaluation of the efficiency of an array of cylindrical Wave Energy Converters (WECs) having a vertical symmetry axis and placed in front of a reflecting vertical breakwater. Linear potential theory is assumed, and the associated diffraction and motion radiation problems are solved in the frequency domain. Axisymmetric eigenfunction expansions of the velocity potential are introduced into properly defined ring-shaped fluid regions surrounding each body of the array. The potential solutions are matched at the boundaries of adjacent fluid regions by enforcing continuity of the hydrodynamic pressures and redial velocities. A theoretical model for the evaluation of the WECs’ performance is developed. The model properly accounts for the effect of the breakwater on each body’s hydrodynamic characteristics and the coupling between the bodies’ motions and the power take-off mechanism. Numerical results are presented and discussed in terms of the expected power absorption. The results show how the efficiency of the array is affected by (a) the distance between the devices and the wall, (b) the shape of the WEC array configuration, as well as (c) the angle of the incoming incident wave. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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17 pages, 2005 KiB

Open AccessEditor’s ChoiceArticle

Experimental Assessment of Flow, Performance, and Loads for Tidal Turbines in a Closely-Spaced Array

by Donald R. Noble, Samuel Draycott, Anup Nambiar, Brian G. Sellar, Jeffrey Steynor and Aristides Kiprakis

Energies 2020, 13(8), 1977; https://doi.org/10.3390/en13081977 - 16 Apr 2020

Cited by 28 | Viewed by 5421

Abstract

Tidal stream turbines are subject to complex flow conditions, particularly when installed in staggered array configurations where the downstream turbines are affected by the wake and/or bypass flow of upstream turbines. This work presents, for the first time, methods for and results from [...] Read more.

Tidal stream turbines are subject to complex flow conditions, particularly when installed in staggered array configurations where the downstream turbines are affected by the wake and/or bypass flow of upstream turbines. This work presents, for the first time, methods for and results from the physical testing of three 1/15 scale instrumented turbines configured in a closely-spaced staggered array, and demonstrates experimentally that increased power extraction can be achieved through reduced array separation. A comprehensive set of flow measurements was taken during several weeks testing in the FloWave Ocean Energy Research Facility, with different configurations of turbines installed in the tank in a current of

0.8

m/s, to understand the effect that the front turbines have on flow through the array and on the inflow to the centrally placed rearmost turbine. Loads on the turbine structure, rotor, and blade roots were measured along with the rotational speed of the rotor to assess concurrently in real-time the effects of flow and array geometry on structural loading and performance. Operating in this closely-spaced array was found to improve the power delivered by the rear turbine by 5.7–10.4% with a corresponding increase in the thrust loading on the rotor of 4.8–7.3% around the peak power operating point. The experimental methods developed and results arising from this work will also be useful for further scale-testing elsewhere, validating numerical models, and for understanding the performance and loading of full-scale tidal stream turbines in arrays. Full article

(This article belongs to the Section A3: Wind, Wave and Tidal Energy)

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16 pages, 2492 KiB

Open AccessEditor’s ChoiceArticle

Thermochromic Paints on External Surfaces: Impact Assessment for a Residential Building through Thermal and Energy Simulation

by Vasco Granadeiro, Margarida Almeida, Tiago Souto, Vítor Leal, João Machado and Adélio Mendes

Energies 2020, 13(8), 1912; https://doi.org/10.3390/en13081912 - 14 Apr 2020

Cited by 18 | Viewed by 5650

Abstract

This work addresses the effect of using thermochromic paints in residential buildings. Two different thermochromic paint types were considered: One that changes properties through a step transition at a certain temperature, and another that changes properties in a gradual/linear manner throughout a temperature [...] Read more.

This work addresses the effect of using thermochromic paints in residential buildings. Two different thermochromic paint types were considered: One that changes properties through a step transition at a certain temperature, and another that changes properties in a gradual/linear manner throughout a temperature range. The studied building was a two-floor villa, virtually simulated through a digital model with and without thermal insulation, and considering thermochromic paints applied both on external walls and on the roof. The performance assessment was done through the energy use for heating and cooling (in conditioned mode), as well as in terms of the indoor temperature (in free-floating mode). Three different cities/climates were considered: Porto, Madrid, and Abu Dhabi. Results showed that energy savings up to 50.6% could be reached if the building is operated in conditioned mode. Conversely, when operated in free-floating mode, optimally selected thermochromic paints enable reductions up to 11.0 °C, during summertime, and an increase up to 2.7 °C, during wintertime. These results point out the great benefits of using optimally selected thermochromic paints for obtaining thermal comfort, and also the need to further develop stable and cost-effective thermochromic pigments for outdoor applications, as well as to test physical models in a real environment. Full article

(This article belongs to the Special Issue Buildings Energy Efficiency and Innovative Energy Systems)

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11 pages, 3677 KiB

Open AccessEditor’s ChoiceArticle

Recursive State of Charge and State of Health Estimation Method for Lithium-Ion Batteries Based on Coulomb Counting and Open Circuit Voltage

by Alejandro Gismero, Erik Schaltz and Daniel-Ioan Stroe

Energies 2020, 13(7), 1811; https://doi.org/10.3390/en13071811 - 9 Apr 2020

Cited by 64 | Viewed by 4893

Abstract

The state of charge (SOC) and state of health (SOH) are two crucial indicators needed for a proper and safe operation of the battery. Coulomb counting is one of the most adopted and straightforward methods to calculate the SOC. Although it can be [...] Read more.

The state of charge (SOC) and state of health (SOH) are two crucial indicators needed for a proper and safe operation of the battery. Coulomb counting is one of the most adopted and straightforward methods to calculate the SOC. Although it can be implemented for all kinds of applications, its accuracy is strongly dependent on the operation conditions. In this work, the behavior of the batteries at different current and temperature conditions is analyzed in order to adjust the charge measurement according to the battery efficiency at the specific operating conditions. The open-circuit voltage (OCV) is used to reset the SOC estimation and prevent the error accumulation. Furthermore, the SOH is estimated by evaluating the accumulated charge between two different SOC using a recursive least squares (RLS) method. The SOC and SOH estimations are verified through an extensive test in which the battery is subjected to a dynamic load profile at different temperatures. Full article

(This article belongs to the Special Issue Energy Storage Systems for Electric Vehicles)

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18 pages, 6085 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Electric Vehicle–Grid Integration with Voltage Regulation in Radial Distribution Networks

by Chong Cao, Zhouquan Wu and Bo Chen

Energies 2020, 13(7), 1802; https://doi.org/10.3390/en13071802 - 8 Apr 2020

Cited by 21 | Viewed by 3336

Abstract

In this paper, a vehicle–grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is [...] Read more.

In this paper, a vehicle–grid integration (VGI) control strategy for radial power distribution networks is presented. The control schemes are designed at both microgrid level and distribution level. At the VGI microgrid level, the available power capacity for electric vehicle (EV) charging is optimally allocated for charging electric vehicles to meet charging requirements. At the distribution grid level, a distributed voltage compensation algorithm is designed to recover voltage violation when it happens at a distribution node. The voltage compensation is achieved through a negotiation between the grid-level agent and VGI microgrid agents using the alternating direction method of multipliers. In each negotiation round, individual agents pursue their own objectives. The computation can be carried out in parallel for each agent. The presented VGI control schemes are simulated and verified in a modified IEEE 37 bus distribution system. The simulation results are presented to show the effectiveness of the VGI control algorithms and the effect of algorithm parameters on the convergence of agent negotiation. Full article

(This article belongs to the Special Issue Electric Systems for Transportation)

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22 pages, 8785 KiB

Open AccessEditor’s ChoiceArticle

Single-Solution-Based Vortex Search Strategy for Optimal Design of Offshore and Onshore Natural Gas Liquefaction Processes

by Muhammad Abdul Qyyum, Muhammad Yasin, Alam Nawaz, Tianbiao He, Wahid Ali, Junaid Haider, Kinza Qadeer, Abdul-Sattar Nizami, Konstantinos Moustakas and Moonyong Lee

Energies 2020, 13(7), 1732; https://doi.org/10.3390/en13071732 - 5 Apr 2020

Cited by 23 | Viewed by 4520

Abstract

Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to [...] Read more.

Propane-Precooled Mixed Refrigerant (C3MR) and Single Mixed Refrigerant (SMR) processes are considered as optimal choices for onshore and offshore natural gas liquefaction, respectively. However, from thermodynamics point of view, these processes are still far away from their maximum achievable energy efficiency due to nonoptimal execution of the design variables. Therefore, Liquefied Natural Gas (LNG) production is considered as one of the energy-intensive cryogenic industries. In this context, this study examines a single-solution-based Vortex Search (VS) approach to find the optimal design variables corresponding to minimal energy consumption for LNG processes, i.e., C3MR and SMR. The LNG processes are simulated using Aspen Hysys and then linked with VS algorithm, which is coded in MATLAB. The results indicated that the SMR process is a potential process for offshore sites that can liquefy natural gas with 16.1% less energy consumption compared with the published base case. Whereas, for onshore LNG production, the energy consumption for the C3MR process is reduced up to 27.8% when compared with the previously published base case. The optimal designs of the SMR and C3MR processes are also found via distinctive well-established optimization approaches (i.e., genetic algorithm and particle swarm optimization) and their performance is compared with that of the VS methodology. The authors believe this work will greatly help the process engineers overcome the challenges relating to the energy efficiency of LNG industry, as well as other mixed refrigerant-based cryogenic processes. Full article

(This article belongs to the Section A: Sustainable Energy)

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23 pages, 9502 KiB

Open AccessEditor’s ChoiceArticle

Analysis of the Use of Electric Drive Systems for Crew Transfer Vessels Servicing Offshore Wind Farms

by Andrzej Łebkowski

Energies 2020, 13(6), 1466; https://doi.org/10.3390/en13061466 - 20 Mar 2020

Cited by 16 | Viewed by 5982

Abstract

The article presents issues related to the possibility of using electric propulsion systems in units used to transport crews servicing wind towers at sea. Offshore wind energy issues are discussed. Proposals for electric propulsion systems that could be used on units for transporting [...] Read more.

The article presents issues related to the possibility of using electric propulsion systems in units used to transport crews servicing wind towers at sea. Offshore wind energy issues are discussed. Proposals for electric propulsion systems that could be used on units for transporting crews servicing offshore wind farms are presented. The possibility of using purely electrical drive systems or hybrid drive systems operating in a diesel-electric configuration is analyzed. By observing the motion of real CTV units, based on the data from the MarineTraffic service, a mathematical simulation model was developed, for which a number of simulations were carried out in the Modelica environment. The developed mathematical model takes into account the dynamic loads acting on the ship’s hull, hydrodynamic resistances, electric and diesel propulsion systems’ properties together with their individual elements’ characteristics. The tests of the electric propulsion system showed reduced fuel consumption (approx. 60%) and harmful gas emissions to the atmosphere (approximately 70%) in relation to conventional, internal combustion engine propulsion. Full article

(This article belongs to the Section D: Energy Storage and Application)

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20 pages, 5943 KiB

Open AccessEditor’s ChoiceArticle

Geological and Thermodynamic Analysis of Low Enthalpy Geothermal Resources to Electricity Generation Using ORC and Kalina Cycle Technology

by Michał Kaczmarczyk, Barbara Tomaszewska and Leszek Pająk

Energies 2020, 13(6), 1335; https://doi.org/10.3390/en13061335 - 13 Mar 2020

Cited by 21 | Viewed by 5567

Abstract

The article presents an assessment of the potential for using low enthalpy geothermal resources for electricity generation on the basis of the Małopolskie Voivodeship (southern Poland). Identification the locations providing the best prospects with the highest efficiency and possible gross power output. Thermodynamic [...] Read more.

The article presents an assessment of the potential for using low enthalpy geothermal resources for electricity generation on the basis of the Małopolskie Voivodeship (southern Poland). Identification the locations providing the best prospects with the highest efficiency and possible gross power output. Thermodynamic calculations of power plants were based on data from several geothermal wells: the Bańska PGP-1, Bańska IG-1, Bańska PGP-3 and Chochołów PIG-1 which are working wells located in one of the best geothermal reservoirs in Poland. As the temperature of geothermal waters from the wells does not exceed 86 °C, considerations include the use of binary technologies—the Organic Rankine Cycle (ORC) and Kalina Cycle. The potential gross capacity calculated for existing geothermal wells will not exceed 900 kW for ORC and 1.6 MW for Kalina Cycle. In the case of gross electricity, the total production will not exceed 3.3 GWh/year using the ORC, and will not exceed 6.3 GWh/year for the Kalina Cycle. Full article

(This article belongs to the Special Issue Assessment, Management and Treatment of Waters and Geothermal Systems)

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14 pages, 3829 KiB

Open AccessEditor’s ChoiceArticle

Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells

by Vladimir Gurau and Emory S. De Castro

Energies 2020, 13(6), 1345; https://doi.org/10.3390/en13061345 - 13 Mar 2020

Cited by 3 | Viewed by 3414

Abstract

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and [...] Read more.

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm²/cm³) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm²). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer. Full article

(This article belongs to the Special Issue Polymer Electrolyte Membrane Fuel Cells 2019)

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26 pages, 10513 KiB

Open AccessEditor’s ChoiceArticle

Low Enthalpy Geothermal Systems in Structural Controlled Areas: A Sustainability Analysis of Geothermal Resource for Heating Plant (The Mondragone Case in Southern Appennines, Italy)

by Marina Iorio, Alberto Carotenuto, Alfonso Corniello, Simona Di Fraia, Nicola Massarotti, Alessandro Mauro, Renato Somma and Laura Vanoli

Energies 2020, 13(5), 1237; https://doi.org/10.3390/en13051237 - 6 Mar 2020

Cited by 19 | Viewed by 4488

Abstract

In this study, the sustainability of low-temperature geothermal field exploitation in a carbonate reservoir near Mondragone (CE), Southern Italy, is analyzed. The Mondragone geothermal field has been extensively studied through the research project VIGOR (Valutazione del potenzIale Geotermico delle RegiOni della convergenza). From [...] Read more.

In this study, the sustainability of low-temperature geothermal field exploitation in a carbonate reservoir near Mondragone (CE), Southern Italy, is analyzed. The Mondragone geothermal field has been extensively studied through the research project VIGOR (Valutazione del potenzIale Geotermico delle RegiOni della convergenza). From seismic, geo-electric, hydro-chemical and groundwater data, obtained through the experimental campaigns carried out, physiochemical features of the aquifers and characteristics of the reservoir have been determined. Within this project, a well-doublet open-loop district heating plant has been designed to feed two public schools in Mondragone town. The sustainability of this geothermal application is analyzed in this study. A new exploration well (about 300 m deep) is considered to obtain further stratigraphic and structural information about the reservoir. Using the derived hydrogeological model of the area, a numerical analysis of geothermal exploitation was carried out to assess the thermal perturbation of the reservoir and the sustainability of its exploitation. The effect of extraction and reinjection of fluids on the reservoir was evaluated for 60 years of the plant activity. The results are fundamental to develop a sustainable geothermal heat plant and represent a real case study for the exploitation of similar carbonate reservoir geothermal resources. Full article

(This article belongs to the Special Issue Geothermal Energy Utilization and Technologies 2020)

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14 pages, 2195 KiB

Open AccessEditor’s ChoiceArticle

Logistics Design for Mobile Battery Energy Storage Systems

by Hassan S. Hayajneh and Xuewei Zhang

Energies 2020, 13(5), 1157; https://doi.org/10.3390/en13051157 - 4 Mar 2020

Cited by 15 | Viewed by 3973

Abstract

Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the [...] Read more.

Currently, there are three major barriers toward a greener energy landscape in the future: (a) Curtailed grid integration of energy from renewable sources like wind and solar; (b) The low investment attractiveness of large-scale battery energy storage systems; and, (c) Constraints from the existing electric infrastructure on the development of charging station networks to meet the increasing electrical transportation demands. A new conceptual design of mobile battery energy storage systems has been proposed in recent studies to reduce the curtailment of renewable energy while limiting the public costs of battery energy storage systems. This work designs a logistics system in which electric semi-trucks ship batteries between the battery energy storage system and electric vehicle charging stations, enabling the planning and operation of power grid independent electric vehicle charging station networks. This solution could be viable in many regions in the United States (e.g., Texas) where there are plenty of renewable resources and little congestion pressure on the road networks. With Corpus Christi, Texas and the neighboring Chapman Ranch wind farm as the test case, this work implement such a design and analyze its performance based on the simulation of its operational processes. Further, we formulate an optimization problem to find design parameters that minimize the total costs. The main design parameters include the number of trucks and batteries. The results in this work, although preliminary, will be instrumental for potential stakeholders to make investment or policy decisions. Full article

(This article belongs to the Special Issue Integration of Electric Vehicles and Battery Storage Systems)

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21 pages, 1893 KiB

Open AccessEditor’s ChoiceArticle

Addressing Abrupt PV Disturbances, and Mitigating Net Load Profile’s Ramp and Peak Demands, Using Distributed Storage Devices

by Roshan Sharma and Masoud Karimi-Ghartemani

Energies 2020, 13(5), 1024; https://doi.org/10.3390/en13051024 - 25 Feb 2020

Cited by 19 | Viewed by 3412

Abstract

At high penetration level of photovoltaic (PV) generators, their abrupt disturbances (caused by moving clouds) cause voltage and frequency perturbations and increase system losses. Meanwhile, the daily irradiation profile increases the slope in the net-load profile, for example, California duck curve, which imposes [...] Read more.

At high penetration level of photovoltaic (PV) generators, their abrupt disturbances (caused by moving clouds) cause voltage and frequency perturbations and increase system losses. Meanwhile, the daily irradiation profile increases the slope in the net-load profile, for example, California duck curve, which imposes the challenge of quickly bringing on-line conventional generators in the early evening hours. Accordingly, this paper presents an approach to achieve two objectives: (1) address abrupt disturbances caused by PV generators, and (2) shape the net load profile. The approach is based on employing battery energy storage (BES) systems coupled with PV generators and equipped with proper controls. The proposed BES addresses these two issues by realizing flexible power ramp-up and ramp-down rates by the combined PV and BES. This paper presents the principles, modeling and control design aspects of the proposed system. A hybrid dc/ac study system is simulated and the effectiveness of the proposed BES in reducing the impacts of disturbances on both the dc and ac subsystems is verified. It is then shown that the proposed PV-BES modifies the daily load profile to mitigate the required challenge for quickly bringing on-line synchronous generators. Full article

(This article belongs to the Special Issue Grid-Connected PV Plants)

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18 pages, 3790 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Temporal Complexity Reduction Techniques Applied to Storage Expansion Planning in Power System Models

by Oriol Raventós and Julian Bartels

Energies 2020, 13(4), 988; https://doi.org/10.3390/en13040988 - 22 Feb 2020

Cited by 14 | Viewed by 3320

Abstract

The growing share of renewable energy makes the optimization of power flows in power system models computationally more complicated, due to the widely distributed weather-dependent electricity generation. This article evaluates two methods to reduce the temporal complexity of a power transmission grid model [...] Read more.

The growing share of renewable energy makes the optimization of power flows in power system models computationally more complicated, due to the widely distributed weather-dependent electricity generation. This article evaluates two methods to reduce the temporal complexity of a power transmission grid model with storage expansion planning. The goal of the reduction techniques is to accelerate the computation of the linear optimal power flow of the grid model. This is achieved by choosing a small number of representative time periods to represent one whole year. To select representative time periods, a hierarchical clustering is used to aggregate either adjacent hours chronologically or independently distributed coupling days into clusters of time series. The aggregation efficiency is evaluated by means of the error of the objective value and the computational time reduction. Further, both the influence of the network size and the efficiency of parallel computation in the optimization process are analysed. As a test case, the transmission grid of the northernmost German federal state of Schleswig-Holstein with a scenario corresponding to the year 2035 is considered. The considered scenario is characterized by a high share of installed renewables. Full article

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37 pages, 7120 KiB

Open AccessEditor’s ChoiceArticle

by Jarosław Brodny and Magdalena Tutak

Energies 2020, 13(4), 913; https://doi.org/10.3390/en13040913 - 18 Feb 2020

Cited by 100 | Viewed by 8921

Abstract

The European Union (EU) countries, as one of the most economically developed regions in the world, are taking increasingly decisive actions to reduce the emission of harmful substances into the natural environment. This can be exemplified by a new climate strategy referred to [...] Read more.

The European Union (EU) countries, as one of the most economically developed regions in the world, are taking increasingly decisive actions to reduce the emission of harmful substances into the natural environment. This can be exemplified by a new climate strategy referred to as “The European Green Deal”. Its basic assumption is that the EU countries will have achieved climate neutrality by 2050. To do so, it is necessary to make an energy transition involving the widest possible use of renewable energy sources (RES) for energy production. However, activities in this area should be preceded by analyses due to the large diversity of the EU countries in terms of economic development, the number of inhabitants and their wealth as well as geographical location and area. The results of such analyses should support the implementation of adopted strategies. In order to assess the current state of the energy sector in the EU and indicate future directions of activities, research was carried out to analyze the structure and volume of energy production from RES in the EU countries. The aim of the study was to divide the EU countries into similar groups by the structure and volume of energy production from RES. This production was compared with the number of inhabitants of each EU country, its area and the value of Gross Domestic Product (GDP). This approach allows a new and broader view of the structure of energy production from RES and creates an opportunity to take into account additional factors when developing and implementing new climate strategies. The k-means algorithm was used for the analysis. The presented analyses and obtained results constitute a new approach to studying the diversified energy market in the EU. The results should be used for the development of a common energy and climate policy and economic integration of the EU countries. Full article

(This article belongs to the Special Issue 100% Renewable Energy Transition: Pathways and Implementation II)

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17 pages, 2127 KiB

Open AccessEditor’s ChoiceArticle

An Investigation of an Adaptive Neuro-Fuzzy Inference System to Predict the Relationship among Energy Intensity, Globalization, and Financial Development in Major ASEAN Economies

by Hafezali Iqbal Hussain, Beata Slusarczyk, Fakarudin Kamarudin, Hassanudin Mohd Thas Thaker and Katarzyna Szczepańska-Woszczyna

Energies 2020, 13(4), 850; https://doi.org/10.3390/en13040850 - 15 Feb 2020

Cited by 60 | Viewed by 4672

Abstract

The enhancement of the financial sector significantly drives a nation’s economy and thereby increase energy intensity. Considering this situation, the current study aims to examine the link between globalization and financial advancements with the energy intensity of the top 5 ASEAN (Association of [...] Read more.

The enhancement of the financial sector significantly drives a nation’s economy and thereby increase energy intensity. Considering this situation, the current study aims to examine the link between globalization and financial advancements with the energy intensity of the top 5 ASEAN (Association of Southeast Asian Nations) economies. The development structure of the ASEAN region is considered significant for having stable growth. The authors used the annual data from 1990 to 2018 for five of the largest ASEAN economies: Singapore, Malaysia, Thailand, Indonesia, and the Philippines. The present study used novel methodology, the Adaptive Neuro-Fuzzy Inference System (ANFIS), to examine the nonlinear behaviour among globalization, financial development, and energy intensity in the top 5 ASEAN countries. The study results using ANFIS confirm that globalization and financial development are positively correlated and have a significant impact on the energy intensity level in the top ASEAN countries. The results further suggest that globalization and financial development increase the level of energy intensity more in the countries that are developed relative to their peers in the top ASEAN countries. Moreover, the outcomes of ANFIS also suggest that those countries, which are more globalized and financially developed, have more potential to increase the level of energy intensity. Therefore, the government needs to focus more on projects that involve renewable energy and are environmentally friendly. Full article

(This article belongs to the Special Issue Management and Technology for Energy Efficiency Development)

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34 pages, 19966 KiB

Open AccessEditor’s ChoiceArticle

Low Temperature District Heating: An Expert Opinion Survey

by Alessandro Guzzini, Marco Pellegrini, Edoardo Pelliconi and Cesare Saccani

Energies 2020, 13(4), 810; https://doi.org/10.3390/en13040810 - 13 Feb 2020

Cited by 16 | Viewed by 3700

Abstract

Among the available solutions for building heating and cooling, district heating (DH) and district cooling (DC) systems are considered some of the best options since they can ensure a better control of pollutant emissions and greater efficiency than individual systems. Nevertheless, improvements are [...] Read more.

Among the available solutions for building heating and cooling, district heating (DH) and district cooling (DC) systems are considered some of the best options since they can ensure a better control of pollutant emissions and greater efficiency than individual systems. Nevertheless, improvements are needed to increase their sustainability and reliability. The so-called “low temperature district heating” (LTDH) concept has been introduced in recent years in an attempt (i) to reduce the distribution heat losses through a temperature decrease in the DH network, (ii) to favor the integration with renewable energy sources, and (iii) to create the conditions required for the development of future smart energy systems. However, many concerns have been raised about its implementation in both existing and new systems. For this reason, this paper aims to identify the stakeholders’ ranking of the barriers against LTDH system development and implementation over the next few years. Aiming to this, a questionnaire was designed, including an analysis of current gaps and strengths, and then submitted to more than 50 Italian and international experts in the field of DH. An in-depth analysis of the received answers was performed, focusing in particular on the Italian experts’ answers. Comments and suggestions on how to promote the transition to the new LTDH approach are reported. Full article

(This article belongs to the Section A1: Smart Grids and Microgrids)

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17 pages, 10575 KiB

Open AccessEditor’s ChoiceArticle

Self-Powered Autonomous Wireless Sensor Node by Using Silicon-Based 3D Thermoelectric Energy Generator for Environmental Monitoring Application

by Jong-Pil Im, Jeong Hun Kim, Jae Woo Lee, Ji Yong Woo, Sol Yee Im, Yeriaron Kim, Yong-Sung Eom, Won Chul Choi, Jun Soo Kim and Seung Eon Moon

Energies 2020, 13(3), 674; https://doi.org/10.3390/en13030674 - 4 Feb 2020

Cited by 15 | Viewed by 4467

Abstract

In this paper, we present the results of a preliminary study on the self-powered autonomous wireless sensor node by using thermoelectric energy generator based on Silicon (Si) thermoelectric legs, energy management integrated circuit (EMIC), Radio Frequency (RF) module with a temperature and humidity [...] Read more.

In this paper, we present the results of a preliminary study on the self-powered autonomous wireless sensor node by using thermoelectric energy generator based on Silicon (Si) thermoelectric legs, energy management integrated circuit (EMIC), Radio Frequency (RF) module with a temperature and humidity sensor, etc. A novel thermoelectric module structure is designed as an energy generator module, which consists of 127 pairs of Silicon legs and this module is fabricated and tested to demonstrate the feasibility of generating electrical power under the temperature gradient of 70K. EMIC has three key features besides high efficiency, which are maximum power point tracking (MPPT), cold start, and complete self-power operation. EMIC achieved a cold start voltage of 200 mV, peak efficiency of 78.7%, MPPT efficiency 99.4%, and an output power of 34 mW through only the Thermoelectric Generator (TEG) source. To assess the capability of the device as a small scale power source for internet of things (IoT) service, we also tested energy conversion and storage experiments. Finally, the proposed sensor node system which can transmit and monitor the information from the temperature and humidity sensor through the RF module in real time demonstrates the feasibility for variable applications. Full article

(This article belongs to the Section F: Electrical Engineering)

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21 pages, 4346 KiB

Open AccessEditor’s ChoiceArticle

Improving the Efficiency of PEM Electrolyzers through Membrane-Specific Pressure Optimization

by Fabian Scheepers, Markus Stähler, Andrea Stähler, Edward Rauls, Martin Müller, Marcelo Carmo and Werner Lehnert

Energies 2020, 13(3), 612; https://doi.org/10.3390/en13030612 - 1 Feb 2020

Cited by 68 | Viewed by 14224

Abstract

Hydrogen produced in a polymer electrolyte membrane (PEM) electrolyzer must be stored under high pressure. It is discussed whether the gas should be compressed in subsequent gas compressors or by the electrolyzer. While gas compressor stages can be reduced in the case of [...] Read more.

Hydrogen produced in a polymer electrolyte membrane (PEM) electrolyzer must be stored under high pressure. It is discussed whether the gas should be compressed in subsequent gas compressors or by the electrolyzer. While gas compressor stages can be reduced in the case of electrochemical compression, safety problems arise for thin membranes due to the undesired permeation of hydrogen across the membrane to the oxygen side, forming an explosive gas. In this study, a PEM system is modeled to evaluate the membrane-specific total system efficiency. The optimum efficiency is given depending on the external heat requirement, permeation, cell pressure, current density, and membrane thickness. It shows that the heat requirement and hydrogen permeation dominate the maximum efficiency below 1.6 V, while, above, the cell polarization is decisive. In addition, a pressure-optimized cell operation is introduced by which the optimum cathode pressure is set as a function of current density and membrane thickness. This approach indicates that thin membranes do not provide increased safety issues compared to thick membranes. However, operating an N212-based system instead of an N117-based one can generate twice the amount of hydrogen at the same system efficiency while only one compressor stage must be added. Full article

(This article belongs to the Special Issue Polymer Electrolyte Membrane Fuel Cells and Electrolyzers)

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17 pages, 2388 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Optimization of Isolated Hybrid Microgrids with Renewable Energy Based on Different Battery Models and Technologies

by Yimy E. García-Vera, Rodolfo Dufo-López and José L. Bernal-Agustín

Energies 2020, 13(3), 581; https://doi.org/10.3390/en13030581 - 26 Jan 2020

Cited by 37 | Viewed by 5203

Abstract

Energy supply in remote areas (mainly in developing countries such as Colombia) has become a challenge. Hybrid microgrids are local and reliable sources of energy for these areas where access to the power grid is generally limited or unavailable. These systems generally include [...] Read more.

Energy supply in remote areas (mainly in developing countries such as Colombia) has become a challenge. Hybrid microgrids are local and reliable sources of energy for these areas where access to the power grid is generally limited or unavailable. These systems generally include a diesel generator, solar modules, wind turbines, and storage devices such as batteries. Battery life estimation is an essential factor in the optimization of a hybrid microgrid since it determines the system’s final costs, including future battery replacements. This article presents a comparison of different technologies and battery models in a hybrid microgrid. The optimization is achieved using the iHOGA software, based on data from a real microgrid in Colombia. The simulation results allowed the comparison of prediction models for lifespan calculation for both lead–acid and lithium batteries in a hybrid microgrid, showing that the most accurate models are more realistic in predicting battery life by closely estimating real lifespans that are shorter, unlike other simplified methods that obtain much longer and unrealistic lifetimes. Full article

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24 pages, 8844 KiB

Open AccessEditor’s ChoiceArticle

Energy End-Use Categorization and Performance Indicators for Energy Management in the Engineering Industry

by Fayas Malik Kanchiralla, Noor Jalo, Simon Johnsson, Patrik Thollander and Maria Andersson

Energies 2020, 13(2), 369; https://doi.org/10.3390/en13020369 - 12 Jan 2020

Cited by 18 | Viewed by 3774

Abstract

Energy efficiency (EE) improvement is one of the most crucial elements in the decarbonization of industry. EE potential within industries largely remains untapped due to the lack of information regarding potential EE measures (EEM), knowledge regarding energy use, and due to the existence [...] Read more.

Energy efficiency (EE) improvement is one of the most crucial elements in the decarbonization of industry. EE potential within industries largely remains untapped due to the lack of information regarding potential EE measures (EEM), knowledge regarding energy use, and due to the existence of some inconsistencies in the evaluation of energy use. Classification of energy end-using processes would increase the understanding of energy use, which in turn would increase the detection and deployment of EEMs. The study presents a novel taxonomy with hierarchical levels for energy end-use in manufacturing operations for the engineering industry, analyzes processes in terms of energy end-use (EEU) and CO₂ emissions, and scrutinizes energy performance indicators (EnPIs), as well as proposing potential new EnPIs that are suitable for the engineering industry. Even though the study has been conducted with a focus on the Swedish engineering industry, the study may be generalizable to the engineering industry beyond Sweden. Full article

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