Energies

16 pages, 4989 KiB

Open AccessEditor’s ChoiceArticle

Evaluation of Some State-Of-The-Art Wind Technologies in the Nearshore of the Black Sea

by Florin Onea and Liliana Rusu

Energies 2018, 11(9), 2452; https://doi.org/10.3390/en11092452 - 15 Sep 2018

Cited by 37 | Viewed by 4884

The main objective of this work was to evaluate the nearshore wind resources in the Black Sea area by using a high resolution wind database (ERA-Interim). A subsequent objective was to estimate what type of wind turbines and wind farm configurations would be [...] Read more.

The main objective of this work was to evaluate the nearshore wind resources in the Black Sea area by using a high resolution wind database (ERA-Interim). A subsequent objective was to estimate what type of wind turbines and wind farm configurations would be more suitable for this coastal environment. A more comprehensive picture of these resources was provided by including some satellite measurements, which were also used to assess the wind conditions in the vicinity of some already operating European wind projects. Based on the results of the present work, it seems that the Crimea Peninsula has the best wind resources. However, considering the current geopolitical situation, it seems that the sites on the western part of this basin (Romania and Bulgaria) would represent more viable locations for developing offshore wind projects. Since there are currently no operational wind projects in this marine area, some possible configurations for the future wind farms are proposed. Full article

(This article belongs to the Special Issue Offshore Renewable Energy: Ocean Waves, Tides and Offshore Wind)

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18 pages, 14119 KiB

Open AccessEditor’s ChoiceArticle

Power and Voltage Control for Single-Phase Cascaded H-Bridge Multilevel Converters under Unbalanced Loads

by Daliang Yang, Li Yin, Shengguang Xu and Ning Wu

Energies 2018, 11(9), 2435; https://doi.org/10.3390/en11092435 - 14 Sep 2018

Cited by 16 | Viewed by 4028

Abstract

The conventional control method for a single-phase cascaded H-bridge (CHB) multilevel converter is vector (dq) control; however, dq control requires complicated calculations and additional time delays. This paper presents a novel power control strategy for the CHB multilevel converter. A power-based [...] Read more.

The conventional control method for a single-phase cascaded H-bridge (CHB) multilevel converter is vector (dq) control; however, dq control requires complicated calculations and additional time delays. This paper presents a novel power control strategy for the CHB multilevel converter. A power-based dc-link voltage balance control is also proposed for unbalanced load conditions. The new control method is designed in a virtual αβ stationary reference frame without coordinate transformation or phase-locked loop (PLL) to avoid the potential issues related to computational complexity. Because only imaginary voltage construction is needed in the proposed control method, the time delay from conventional imaginary current construction can be eliminated. The proposed method can obtain a sinusoidal grid current waveform with unity power factor. Compared with the conventional dq control method, the power control strategy possesses the advantage of a fast dynamic response. The stability of the closed-loop system with the dc-link voltage balance controller is evaluated. Simulation and experimental results are presented to verify the accuracy of the proposed power and voltage control method. Full article

(This article belongs to the Special Issue Design and Control of Power Converters 2019)

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18 pages, 7031 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

FPGA-Based Implementation of MMC Control Based on Sorting Networks

by Mattia Ricco, Laszlo Mathe, Eric Monmasson and Remus Teodorescu

Energies 2018, 11(9), 2394; https://doi.org/10.3390/en11092394 - 11 Sep 2018

Cited by 16 | Viewed by 5315

Abstract

In Modular Multilevel Converter (MMC) applications, the balancing of the capacitor voltages is one of the most important issues for achieving the proper behavior of the MMC. The Capacitor Voltage Balancing (CVB) control is usually based on classical sorting algorithms which consist of [...] Read more.

In Modular Multilevel Converter (MMC) applications, the balancing of the capacitor voltages is one of the most important issues for achieving the proper behavior of the MMC. The Capacitor Voltage Balancing (CVB) control is usually based on classical sorting algorithms which consist of repetitive/recursive loops. This leads to an increase of the execution time when many Sub-Modules (SMs) are employed. When the execution time of the balancing is longer than the sampling period, the proper operation of the MMC cannot be ensured. Moreover, due to their inherent sequential operation, sorting algorithms are suitable for software implementation (microcontrollers or DSPs), but they are not appropriate for a hardware implementation. Instead, in this paper, Sorting Networks (SNs) are proposed due to their convenience for implementation in FPGA devices. The advantages and the main challenges of the Bitonic SN in MMC applications are discussed and different FPGA implementations are presented. Simulation results are provided in normal and faulty conditions. Moreover, a comparison with the widely used bubble sorting algorithm and max/min approach is made in terms of execution time and performance. Finally, hardware-in-the-loop results are shown to prove the effectiveness of the implemented SN. Full article

(This article belongs to the Special Issue Multilevel Converters: Analysis, Modulation, Topologies, and Applications)

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18 pages, 2108 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Economic Advantages of Dry-Etched Black Silicon in Passivated Emitter Rear Cell (PERC) Photovoltaic Manufacturing

by Chiara Modanese, Hannu S. Laine, Toni P. Pasanen, Hele Savin and Joshua M. Pearce

Energies 2018, 11(9), 2337; https://doi.org/10.3390/en11092337 - 5 Sep 2018

Cited by 27 | Viewed by 9683

Abstract

Industrial Czochralski silicon (Cz-Si) photovoltaic (PV) efficiencies have routinely reached >20% with the passivated emitter rear cell (PERC) design. Nanostructuring silicon (black-Si) by dry-etching decreases surface reflectance, allows diamond saw wafering, enhances metal gettering, and may prevent power conversion efficiency degradation under light [...] Read more.

Industrial Czochralski silicon (Cz-Si) photovoltaic (PV) efficiencies have routinely reached >20% with the passivated emitter rear cell (PERC) design. Nanostructuring silicon (black-Si) by dry-etching decreases surface reflectance, allows diamond saw wafering, enhances metal gettering, and may prevent power conversion efficiency degradation under light exposure. Black-Si allows a potential for >20% PERC cells using cheaper multicrystalline silicon (mc-Si) materials, although dry-etching is widely considered too expensive for industrial application. This study analyzes this economic potential by comparing costs of standard texturized Cz-Si and black mc-Si PERC cells. Manufacturing sequences are divided into steps, and costs per unit power are individually calculated for all different steps. Baseline costs for each step are calculated and a sensitivity analysis run for a theoretical 1 GW/year manufacturing plant, combining data from literature and industry. The results show an increase in the overall cell processing costs between 15.8% and 25.1% due to the combination of black-Si etching and passivation by double-sided atomic layer deposition. Despite this increase, the cost per unit power of the overall PERC cell drops by 10.8%. This is a significant cost saving and thus energy policies are reviewed to overcome challenges to accelerating deployment of black mc-Si PERC across the PV industry. Full article

(This article belongs to the Special Issue Recent Research Progress for Energy Policy)

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16 pages, 3470 KiB

Open AccessEditor’s ChoiceArticle

Development and Validation of Numerical Models for Evaluation of Foam-Vacuum Insulation Panel Composite Boards, Including Edge Effects

by Kaushik Biswas

Energies 2018, 11(9), 2228; https://doi.org/10.3390/en11092228 - 25 Aug 2018

Cited by 13 | Viewed by 3479

Abstract

A combined finite element analysis (FEA) and experimental validation approach to estimating effective edge conductivities of vacuum insulation panels (VIPs) embedded in foam-VIP composites is presented. The edge conductivities were estimated by comparing the simulation results with measurements of small-scale (0.61 × 0.61 [...] Read more.

A combined finite element analysis (FEA) and experimental validation approach to estimating effective edge conductivities of vacuum insulation panels (VIPs) embedded in foam-VIP composites is presented. The edge conductivities were estimated by comparing the simulation results with measurements of small-scale (0.61 × 0.61 m) foam-VIP composites and using an error minimization method. The two composites contained multiple VIPs that were butt-jointed with each other in one composite and separated by foam insulation in the other. Edge conductivities were estimated by considering the neighboring materials, i.e., whether the VIPs were adjacent to other VIPs or foam insulation. Models incorporating the edge conductivities were then used to simulate additional small- and large-scale (2.44 × 1.22 m) composites for validation and evaluation of the overall thermal transmission properties. The simulations used either the same boundary conditions as the experiments or used the experimental parameters to define the appropriate boundary conditions. Full article

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25 pages, 315 KiB

Open AccessEditor’s ChoiceReview

Biodiesel Production from Palm Oil, Its By-Products, and Mill Effluent: A Review

by Khairul Azly Zahan and Manabu Kano

Energies 2018, 11(8), 2132; https://doi.org/10.3390/en11082132 - 16 Aug 2018

Cited by 242 | Viewed by 23537

Abstract

The sustainability of petroleum-based fuel supply has gained broad attention from the global community due to the increase of usage in various sectors, depletion of petroleum resources, and uncertain around crude oil market prices. Additionally, environmental problems have also arisen from the increasing [...] Read more.

The sustainability of petroleum-based fuel supply has gained broad attention from the global community due to the increase of usage in various sectors, depletion of petroleum resources, and uncertain around crude oil market prices. Additionally, environmental problems have also arisen from the increasing emissions of harmful pollutants and greenhouse gases. Therefore, the use of clean energy sources including biodiesel is crucial. Biodiesel is mainly produced from unlimited natural resources through a transesterification process. It presents various advantages over petro-diesel; for instance, it is non-toxic, biodegradable, and contains less air pollutant per net energy produced with low sulphur and aromatic content, apart from being safe. Considering the importance of this topic, this paper focuses on the use of palm oil, its by-products, and mill effluent for biodiesel production. Palm oil is known as an excellent raw material because biodiesel has similar properties to the regular petro-diesel. Due to the debate on the usage of palm oil as food versus fuel, extensive studies have been conducted to utilise its by-products and mill effluent as raw materials. This paper also discusses the properties of biodiesel, the difference between palm-biodiesel and other biodiesel sources, and the feasibility of using palm oil as a primary source for future alternative and sustainable energy sources. Full article

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

16 pages, 5326 KiB

Open AccessEditor’s ChoiceArticle

Power Quality: Scientific Collaboration Networks and Research Trends

by Francisco G. Montoya, Raul Baños, Alfredo Alcayde, Maria G. Montoya and Francisco Manzano-Agugliaro

Energies 2018, 11(8), 2067; https://doi.org/10.3390/en11082067 - 8 Aug 2018

Cited by 36 | Viewed by 5960

Abstract

Power quality is a research field related to the proper operation of devices and technological equipment in industry, service, and domestic activities. The level of power quality is determined by variations in voltage, frequency, and waveforms with respect to reference values. These variations [...] Read more.

Power quality is a research field related to the proper operation of devices and technological equipment in industry, service, and domestic activities. The level of power quality is determined by variations in voltage, frequency, and waveforms with respect to reference values. These variations correspond to different types of disturbances, including power fluctuations, interruptions, and transients. Several studies have been focused on analysing power quality issues. However, there is a lack of studies on the analysis of both the trending topics and the scientific collaboration network underlying the field of power quality. To address these aspects, an advanced model is used to retrieve data from publications related to power quality and analyse this information using a graph visualisation software and statistical tools. The results suggest that research interests are mainly focused on the analysis of power quality problems and mitigation techniques. Furthermore, they are observed important collaboration networks between researchers within and across countries. Full article

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

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22 pages, 1470 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Optimal Component Sizing for Peak Shaving in Battery Energy Storage System for Industrial Applications

by Rodrigo Martins, Holger C. Hesse, Johanna Jungbauer, Thomas Vorbuchner and Petr Musilek

Energies 2018, 11(8), 2048; https://doi.org/10.3390/en11082048 - 7 Aug 2018

Cited by 105 | Viewed by 13385

Abstract

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage [...] Read more.

Recent attention to industrial peak shaving applications sparked an increased interest in battery energy storage. Batteries provide a fast and high power capability, making them an ideal solution for this task. This work proposes a general framework for sizing of battery energy storage system (BESS) in peak shaving applications. A cost-optimal sizing of the battery and power electronics is derived using linear programming based on local demand and billing scheme. A case study conducted with real-world industrial profiles shows the applicability of the approach as well as the return on investment dependence on the load profile. At the same time, the power flow optimization reveals the best storage operation patterns considering a trade-off between energy purchase, peak-power tariff, and battery aging. This underlines the need for a general mathematical optimization approach to efficiently tackle the challenge of peak shaving using an energy storage system. The case study also compares the applicability of yearly and monthly billing schemes, where the highest load of the year/month is the base for the price per kW. The results demonstrate that batteries in peak shaving applications can shorten the payback period when used for large industrial loads. They also show the impacts of peak shaving variation on the return of investment and battery aging of the system. Full article

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

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14 pages, 2546 KiB

Open AccessEditor’s ChoiceArticle

Hydrothermal Carbonization of Fruit Wastes: A Promising Technique for Generating Hydrochar

by Bide Zhang, Mohammad Heidari, Bharat Regmi, Shakirudeen Salaudeen, Precious Arku, Mahendra Thimmannagari and Animesh Dutta

Energies 2018, 11(8), 2022; https://doi.org/10.3390/en11082022 - 3 Aug 2018

Cited by 112 | Viewed by 8437

Abstract

Hydrothermal carbonization (HTC) is a useful method to convert wet biomass to value-added products. Fruit waste generated in juice industries is a huge source of moist feedstock for such conversion to produce hydrochar. This paper deals with four types of fruit wastes as [...] Read more.

Hydrothermal carbonization (HTC) is a useful method to convert wet biomass to value-added products. Fruit waste generated in juice industries is a huge source of moist feedstock for such conversion to produce hydrochar. This paper deals with four types of fruit wastes as feedstocks for HTC; namely, rotten apple (RA), apple chip pomace (ACP), apple juice pomace (AJP), and grape pomace (GP). The operating conditions for HTC processing were 190 °C, 225 °C, and 260 °C for 15 min. For all samples, higher heating value and fixed carbon increased, while volatile matter and oxygen content decreased after HTC. Except for ACP, the ash content of all samples increased after 225 °C. For RA, AJP, and GP, the possible explanation for increased ash content above 225 °C is that the hydrochar increases in porosity after 230 °C. It was observed that an increase in HTC temperature resulted in an increase in the mass yield for RA and GP, which is in contrast with increasing HTC temperature for lignocellulose biomass. Other characterization tests like thermogravimetric analysis (TGA) and scanning electron microscopy (SEM) also showed that the HTC process can be successfully used to convert fruit wastes into valuable products. Full article

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

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19 pages, 435 KiB

Open AccessEditor’s ChoiceArticle

Reinforcement Learning Based Energy Management Algorithm for Smart Energy Buildings

by Sunyong Kim and Hyuk Lim

Energies 2018, 11(8), 2010; https://doi.org/10.3390/en11082010 - 2 Aug 2018

Cited by 145 | Viewed by 12497

Abstract

A smart grid facilitates more effective energy management of an electrical grid system. Because both energy consumption and associated building operation costs are increasing rapidly around the world, the need for flexible and cost-effective management of the energy used by buildings in a [...] Read more.

A smart grid facilitates more effective energy management of an electrical grid system. Because both energy consumption and associated building operation costs are increasing rapidly around the world, the need for flexible and cost-effective management of the energy used by buildings in a smart grid environment is increasing. In this paper, we consider an energy management system for a smart energy building connected to an external grid (utility) as well as distributed energy resources including a renewable energy source, energy storage system, and vehicle-to-grid station. First, the energy management system is modeled using a Markov decision process that completely describes the state, action, transition probability, and rewards of the system. Subsequently, a reinforcement-learning-based energy management algorithm is proposed to reduce the operation energy costs of the target smart energy building under unknown future information. The results of numerical simulation based on the data measured in real environments show that the proposed energy management algorithm gradually reduces energy costs via learning processes compared to other random and non-learning-based algorithms. Full article

(This article belongs to the Special Issue Energy Efficiency in Plants and Buildings 2019)

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26 pages, 15578 KiB

Open AccessEditor’s ChoiceArticle

City Bus Powertrain Comparison: Driving Cycle Variation and Passenger Load Sensitivity Analysis

by Klaus Kivekäs, Antti Lajunen, Jari Vepsäläinen and Kari Tammi

Energies 2018, 11(7), 1755; https://doi.org/10.3390/en11071755 - 4 Jul 2018

Cited by 68 | Viewed by 8781

Abstract

Alternative powertrains are rapidly increasing in popularity in city buses. Hence, it is vitally important to understand the factors affecting the performance of the powertrains in order to operate them on appropriate routes and as efficiently as possible. To that end, this paper [...] Read more.

Alternative powertrains are rapidly increasing in popularity in city buses. Hence, it is vitally important to understand the factors affecting the performance of the powertrains in order to operate them on appropriate routes and as efficiently as possible. To that end, this paper presents an exhaustive driving cycle and passenger load sensitivity analysis for the most common city bus powertrain topologies. Three-thousand synthetic cycles were generated for a typical suburban bus route based on measured cycles and passenger numbers from the route. The cycles were simulated with six bus models: compressed natural gas, diesel, parallel hybrid, series hybrid, hydrogen fuel cell hybrid, and battery electric bus. Twenty reference cycles featuring various types of routes were simulated for comparison. Correlations between energy consumption and the various driving cycle parameters and passenger loads were examined. Further analysis was conducted with variance decomposition. Aggressiveness and stop frequency had the highest correlation with the consumption. The diesel bus was the most sensitive to aggressiveness. The parallel hybrid had a lower statistical dispersion of consumption than the series hybrid on the suburban route. On the varied routes, the opposite was true. The performance of the parallel hybrid powertrain deteriorated significantly on cycles with high aggressiveness and stop frequency. In general, the high correlation between aggressiveness and energy consumption implies that particular attention must be paid to limiting high-speed accelerations of city buses. Full article

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21 pages, 426 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Robust Prescriptive Framework and Performance Metric for Diagnosing and Predicting Wind Turbine Faults Based on SCADA and Alarms Data with Case Study

by Kevin Leahy, Colm Gallagher, Peter O’Donovan, Ken Bruton and Dominic T. J. O’Sullivan

Energies 2018, 11(7), 1738; https://doi.org/10.3390/en11071738 - 3 Jul 2018

Cited by 49 | Viewed by 6983

Abstract

Using 10-minute wind turbine supervisory control and data acquisition (SCADA) system data to predict faults can be an attractive way of working toward a predictive maintenance strategy without needing to invest in extra hardware. Classification methods have been shown to be effective in [...] Read more.

Using 10-minute wind turbine supervisory control and data acquisition (SCADA) system data to predict faults can be an attractive way of working toward a predictive maintenance strategy without needing to invest in extra hardware. Classification methods have been shown to be effective in this regard, but there have been some common issues in their application within the literature. To use these data-driven methods effectively, historical SCADA data must be accurately labelled with the periods when turbines were down due to faults, as well as with the reason for the fault. This can be manually achieved using maintenance logs, but can be highly tedious and time-consuming due to the often unstructured format in which this information is stored. Alarm systems can also help, but the sheer volume of alarms and false positives generated complicate efforts. Furthermore, a way to implement and evaluate the field deployed system beyond simple classification metrics is needed. In this work, we present a prescribed and reproducible framework for: (i) automatically identifying periods of faulty operation using rules applied to the turbine alarm system; (ii) using this information to perform classification which avoids some of the common pitfalls observed in literature; and (iii) generating alerts based on a sliding window metric to evaluate the performance of the system in a real-world scenario. The framework was applied to a dataset from an operating wind farm and the results show that the system can automatically and accurately label historical stoppages from the alarms data. For fault prediction, classification scores are quite low, with precision of 0.16 and recall of 0.49, but it is envisaged that this can be greatly improved with more training data. Nonetheless, the sliding window metric compensates for the low raw classification scores and shows that 71% of faults can be predicted with an average of 30 h notice, with false alarms being active for 122 h of the year. By adjusting some of the parameters of the fault prediction alerts, the duration of false alarms can be drastically reduced to 2 h, but this also reduces the number of predicted faults to 8%. Full article

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

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21 pages, 4136 KiB

Open AccessEditor’s ChoiceArticle

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

by Yongli Wang, Haiyang Yu, Mingyue Yong, Yujing Huang, Fuli Zhang and Xiaohai Wang

Energies 2018, 11(7), 1676; https://doi.org/10.3390/en11071676 - 27 Jun 2018

Cited by 38 | Viewed by 4217

Abstract

Integrated energy systems (IESs) are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of [...] Read more.

Integrated energy systems (IESs) are considered a trending solution for the energy crisis and environmental problems. However, the diversity of energy sources and the complexity of the IES have brought challenges to the economic operation of IESs. Aiming at achieving optimal scheduling of components, an IES operation optimization model including photovoltaic, combined heat and power generation system (CHP) and battery energy storage is developed in this paper. The goal of the optimization model is to minimize the operation cost under the system constraints. For the optimization process, an optimization principle is conducted, which achieves maximized utilization of photovoltaic by adjusting the controllable units such as energy storage and gas turbine, as well as taking into account the battery lifetime loss. In addition, an integrated energy system project is taken as a research case to validate the effectiveness of the model via the improved differential evolution algorithm (IDEA). The comparison between IDEA and a traditional differential evolution algorithm shows that IDEA could find the optimal solution faster, owing to the double variation differential strategy. The simulation results in three different battery states which show that the battery lifetime loss is an inevitable factor in the optimization model, and the optimized operation cost in 2016 drastically decreased compared with actual operation data. Full article

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20 pages, 4147 KiB

Open AccessEditor’s ChoiceArticle

Optimal Deep Learning LSTM Model for Electric Load Forecasting using Feature Selection and Genetic Algorithm: Comparison with Machine Learning Approaches ^†

by Salah Bouktif, Ali Fiaz, Ali Ouni and Mohamed Adel Serhani

Energies 2018, 11(7), 1636; https://doi.org/10.3390/en11071636 - 22 Jun 2018

Cited by 724 | Viewed by 38149

Abstract

Background: With the development of smart grids, accurate electric load forecasting has become increasingly important as it can help power companies in better load scheduling and reduce excessive electricity production. However, developing and selecting accurate time series models is a challenging task as [...] Read more.

Background: With the development of smart grids, accurate electric load forecasting has become increasingly important as it can help power companies in better load scheduling and reduce excessive electricity production. However, developing and selecting accurate time series models is a challenging task as this requires training several different models for selecting the best amongst them along with substantial feature engineering to derive informative features and finding optimal time lags, a commonly used input features for time series models. Methods: Our approach uses machine learning and a long short-term memory (LSTM)-based neural network with various configurations to construct forecasting models for short to medium term aggregate load forecasting. The research solves above mentioned problems by training several linear and non-linear machine learning algorithms and picking the best as baseline, choosing best features using wrapper and embedded feature selection methods and finally using genetic algorithm (GA) to find optimal time lags and number of layers for LSTM model predictive performance optimization. Results: Using France metropolitan’s electricity consumption data as a case study, obtained results show that LSTM based model has shown high accuracy then machine learning model that is optimized with hyperparameter tuning. Using the best features, optimal lags, layers and training various LSTM configurations further improved forecasting accuracy. Conclusions: A LSTM model using only optimally selected time lagged features captured all the characteristics of complex time series and showed decreased Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) for medium to long range forecasting for a wider metropolitan area. Full article

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20 pages, 5159 KiB

Open AccessEditor’s ChoiceArticle

A Class of Control Strategies for Energy Internet Considering System Robustness and Operation Cost Optimization

by Haochen Hua, Chuantong Hao, Yuchao Qin and Junwei Cao

Energies 2018, 11(6), 1593; https://doi.org/10.3390/en11061593 - 18 Jun 2018

Cited by 31 | Viewed by 3971

Abstract

Aiming at restructuring the conventional energy delivery infrastructure, the concept of energy Internet (EI) has become popular in recent years. Outstanding benefits from an EI include openness, robustness and reliability. Most of the existing literatures focus on the conceptual design of EI and [...] Read more.

Aiming at restructuring the conventional energy delivery infrastructure, the concept of energy Internet (EI) has become popular in recent years. Outstanding benefits from an EI include openness, robustness and reliability. Most of the existing literatures focus on the conceptual design of EI and are lack of theoretical investigation on developing specific control strategies for the operation of EI. In this paper, a class of control strategies for EI considering system robustness and operation cost optimization is investigated. Focusing on the EI system robustness issue, system parameter uncertainty, external disturbance and tracking error are taken into consideration, and we formulate such robust control issue as a structure specified mixed

H_{2} / H_{\infty}

control problem. When formulating the operation cost optimization problem, three aspects are considered: realizing the bottom-up energy management principle, reducing the cost involved by power delivery from power grid (PG) to microgrid (MG), and avoiding the situation of over-control. We highlight that this is the very first time that the above targets are considered simultaneously in the field of EI. The integrated control issue is considered in frequency domain and is solved by a particle swarm optimization (PSO) algorithm. Simulation results show that our proposed method achieves the targets. Full article

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22 pages, 1241 KiB

Open AccessEditor’s ChoiceReview

Peer to Peer Distributed Energy Trading in Smart Grids: A Survey

by Juhar Abdella and Khaled Shuaib

Energies 2018, 11(6), 1560; https://doi.org/10.3390/en11061560 - 14 Jun 2018

Cited by 200 | Viewed by 14899

Abstract

Due to the expansion of distributed renewable energy resources, peer to peer energy trading (P2P DET) is expected to be one of the key elements of next generation power systems. P2P DET can provide various benefits such as creating a competitive energy market, [...] Read more.

Due to the expansion of distributed renewable energy resources, peer to peer energy trading (P2P DET) is expected to be one of the key elements of next generation power systems. P2P DET can provide various benefits such as creating a competitive energy market, reducing power outages, increasing overall efficiency of power systems and supplementing alternative sources of energy according to user preferences. Because of these promising advantages, P2P DET has attracted the attention of several researchers. Current research related to P2P DET include demand response optimization, power routing, network communication, security and privacy. This paper presents a review of the main research topics revolving around P2P DET. Particularly, we present a comprehensive survey of existing demand response optimization models, power routing devices and power routing algorithms. We also identify some key challenges faced in realizing P2P DET. Furthermore, we discuss state of the art enabling technologies such as Energy Internet, Blockchain and Software Defined Networking (SDN) and we provide insights into future research directions. Full article

(This article belongs to the Collection Smart Grid)

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16 pages, 3931 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

An Assessment of the Sustainability of Lignocellulosic Bioethanol Production from Wastes in Iceland

by Sahar Safarian and Runar Unnthorsson

Energies 2018, 11(6), 1493; https://doi.org/10.3390/en11061493 - 7 Jun 2018

Cited by 48 | Viewed by 6823

Abstract

This paper describes the development of a model to comprehensively assess the sustainability impacts of producing lignocellulosic bioethanol from various types of municipal organic wastes (MOWs) in Iceland: paper and paperboard, timber and wood and garden waste. The tool integrates significant economic, energy, [...] Read more.

This paper describes the development of a model to comprehensively assess the sustainability impacts of producing lignocellulosic bioethanol from various types of municipal organic wastes (MOWs) in Iceland: paper and paperboard, timber and wood and garden waste. The tool integrates significant economic, energy, environmental and technical aspects to analyse and rank twelve systems using the most common pretreatment technologies: dilute acid, dilute alkali, hot water and steam explosion. The results show that among the MOWs, paper and paperboard have higher positive rankings under most assessments. Steam explosion is also ranked at the top from the economic, energy and environmental perspectives, followed by the hot water method for paper and timber wastes. Finally, a potential evaluation of total wastes and bioethanol production in Iceland is carried out. The results show that the average production of lignocellulosic bioethanol in 2015 could be 12.5, 11 and 3 thousand tons from paper, timber and garden wastes, respectively, and that production could reach about 15.9, 13.7 and 3.7 thousand tons, respectively, by 2030. Full article

(This article belongs to the Special Issue BioEnergy and BioChemicals Production from Biomass and Residual Resources)

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26 pages, 7562 KiB

Open AccessEditor’s ChoiceReview

A Review of Particulate Number (PN) Emissions from Gasoline Direct Injection (GDI) Engines and Their Control Techniques

by Mohsin Raza, Longfei Chen, Felix Leach and Shiting Ding

Energies 2018, 11(6), 1417; https://doi.org/10.3390/en11061417 - 1 Jun 2018

Cited by 207 | Viewed by 15400

Abstract

Particulate Matter (PM) emissions from gasoline direct injection (GDI) engines, particularly Particle Number (PN) emissions, have been studied intensively in both academia and industry because of the adverse effects of ultrafine PM emissions on human health and other environmental concerns. GDI engines are [...] Read more.

Particulate Matter (PM) emissions from gasoline direct injection (GDI) engines, particularly Particle Number (PN) emissions, have been studied intensively in both academia and industry because of the adverse effects of ultrafine PM emissions on human health and other environmental concerns. GDI engines are known to emit a higher number of PN emissions (on an engine-out basis) than Port Fuel Injection (PFI) engines, due to the reduced mixture homogeneity in GDI engines. Euro 6 emission standards have been introduced in Europe (and similarly in China) to limit PN emissions from GDI engines. This article summarises the current state of research in GDI PN emissions (engine-out) including a discussion of PN formation, and the characteristics of PN emissions from GDI engines. The effect of key GDI engine operating parameters is analysed, including air-fuel ratio, ignition and injection timing, injection pressure, and EGR; in addition the effect of fuel composition on particulate emissions is explored, including the effect of oxygenate components such as ethanol. Full article

(This article belongs to the Special Issue Recent Advances in Internal Combustion Engines Operation and Emissions)

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22 pages, 3972 KiB

Open AccessEditor’s ChoiceArticle

A New Method for Contrasting Energy Performance and Near-Zero Energy Building Requirements in Different Climates and Countries

by Kaiser Ahmed, Margaux Carlier, Christian Feldmann and Jarek Kurnitski

Energies 2018, 11(6), 1334; https://doi.org/10.3390/en11061334 - 23 May 2018

Cited by 31 | Viewed by 4642

Abstract

In this study a robust method enabling one to compare the energy performance in different climates was developed. Derived normalization factors allow “to move” the building from one climate to another with corresponding changes in heating, cooling, and electric lighting energy. Degree days, [...] Read more.

In this study a robust method enabling one to compare the energy performance in different climates was developed. Derived normalization factors allow “to move” the building from one climate to another with corresponding changes in heating, cooling, and electric lighting energy. Degree days, solar-air temperature and economic insulation thickness were used to normalize space heating and cooling needs. Solar-air temperature based degree days resulted in 5% accuracy in space heating and dry-bulb air temperature based cooling degree days were trustworthy in cooling need normalization. To overcome the limitation of the same thermal insulation in all climates, an economic insulation thickness was applied. Existing and nearly zero energy requirements were contrasted in four countries with a reference office building to analyze the impacts of climate and national regulation on primary energy use. By applying standard energy calculation input data and primary energy factors from European standards to buildings with national technical solutions, nearly zero energy building requirements comparison with European Commission benchmarks was possible to conduct. Generally, in Central and North Europe comparison, national input data caused much more difference than the climate. Full article

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24 pages, 5529 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Plasma-Assisted Biomass Gasification with Focus on Carbon Conversion and Reaction Kinetics Compared to Thermal Gasification

by Yin Pang, Leo Bahr, Peter Fendt, Lars Zigan, Stefan Will, Thomas Hammer, Manfred Baldauf, Robert Fleck, Dominik Müller and Jürgen Karl

Energies 2018, 11(5), 1302; https://doi.org/10.3390/en11051302 - 20 May 2018

Cited by 28 | Viewed by 9184

Abstract

Compared to conventional allothermal gasification of solid fuels (e.g., biomass, charcoal, lignite, etc.), plasma-assisted gasification offers an efficient method for applying energy to the gasification process to increase the flexibility of operation conditions and to increase the reaction kinetics. In particular, non-thermal plasmas [...] Read more.

Compared to conventional allothermal gasification of solid fuels (e.g., biomass, charcoal, lignite, etc.), plasma-assisted gasification offers an efficient method for applying energy to the gasification process to increase the flexibility of operation conditions and to increase the reaction kinetics. In particular, non-thermal plasmas (NTP) are promising, in which thermal equilibrium is not reached and electrons have a substantially higher mean energy than gas molecules. Thus, it is generally assumed that in NTP the supplied energy is utilized more efficiently for generating free radicals initiating gasification reactions than thermal plasma processes. In order to investigate this hypothesis, we compared purely thermal to non-thermal plasma-assisted gasification of biomass in steam in a drop tube reactor at atmospheric pressure. The NTP was provided by means of gliding arcs between two electrodes aligned in the inlet steam flow with an electric power of about 1 kW. Reaction yields and rates were evaluated using measured gas temperatures by the optical technique. The first experimental results show that the non-thermal plasma not only promotes the carbon conversion of the fuel particles, but also accelerates the reaction kinetics. The carbon conversion is increased by nearly 10% using wood powder as the fuel. With charcoal powder, more than 3% are converted into syngas. Full article

(This article belongs to the Special Issue Electric Fields in Energy & Process Engineering)

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19 pages, 374 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Is District Heating Combined Heat and Power at Risk in the Nordic Area?—An Electricity Market Perspective

by Kristo Helin, Behnam Zakeri and Sanna Syri

Energies 2018, 11(5), 1256; https://doi.org/10.3390/en11051256 - 14 May 2018

Cited by 23 | Viewed by 5545

Abstract

The Nordic power market has exceptionally low carbon emissions. Energy efficient combined heat and power (CHP) plays an important role in the market, and also produces a large share of Nordic district heating (DH) energy. In future Nordic energy systems, DH CHP is [...] Read more.

The Nordic power market has exceptionally low carbon emissions. Energy efficient combined heat and power (CHP) plays an important role in the market, and also produces a large share of Nordic district heating (DH) energy. In future Nordic energy systems, DH CHP is often seen as vital for flexibility in electricity production. However, CHP electricity production may not be profitable in the future Nordic market. Even currently, the prevailing trend is for CHP plants to be replaced with heat-only boilers in DH production. In this work, we aim to describe the future utilisation of CHP in the Nordic area. We use an electricity market simulation model to examine the development of the Nordic electricity market until 2030. We examine one main projection of electricity production capacity changes, and based on it we assess scenarios with different electricity demands and CO₂ emission prices. Differences between scenarios are notable: For example, the stalling or increasing of electricity demand from the 2014 level can mean a difference of 15 €/MWh in the average market price of electricity in 2020. The results of this paper underline the importance of considering several alternative future paths of electricity production and consumption when designing new energy policies. Full article

(This article belongs to the Special Issue District Heating)

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27 pages, 6881 KiB

Open AccessEditor’s ChoiceArticle

On the Mobile Communication Requirements for the Demand-Side Management of Electric Vehicles

by Stefano Rinaldi, Marco Pasetti, Emiliano Sisinni, Federico Bonafini, Paolo Ferrari, Mattia Rizzi and Alessandra Flammini

Energies 2018, 11(5), 1220; https://doi.org/10.3390/en11051220 - 10 May 2018

Cited by 61 | Viewed by 6942

Abstract

The rising concerns about global warming and environmental pollution are increasingly pushing towards the replacement of road vehicles powered by Internal Combustion Engines (ICEs). Electric Vehicles (EVs) are generally considered the best candidates for this transition, however, existing power grids and EV management [...] Read more.

The rising concerns about global warming and environmental pollution are increasingly pushing towards the replacement of road vehicles powered by Internal Combustion Engines (ICEs). Electric Vehicles (EVs) are generally considered the best candidates for this transition, however, existing power grids and EV management systems are not yet ready for a large penetration of EVs, and the current opinion of the scientific community is that further research must be done in this field. The so-called Vehicle-to-Grid (V2G) concept plays a relevant role in this scenario by providing the communication capabilities required by advanced control and Demand-Side Management (DSM) strategies. Following this research trend, in this paper the communication requirements for the DSM of EVs in urban environments are discussed, by focusing on the mobile communication among EVs and smart grids. A specific system architecture for the DSM of EVs moving inside urban areas is proposed and discussed in terms of the required data throughput. In addition, the use of a Low-Power Wide-Area Network (LPWAN) solution—the Long-Range Wide Area Network (LoRaWAN) technology—is proposed as a possible alternative to cellular-like solutions, by testing an experimental communication infrastructure in a real environment. The results show that the proposed LPWAN technology is capable to handle an adequate amount of information for the considered application, and that one LoRa base station is able to serve up to 438 EVs per cell, and 1408 EV charging points. Full article

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14 pages, 2474 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Density Measurements of Waste Cooking Oil Biodiesel and Diesel Blends Over Extended Pressure and Temperature Ranges

by Thanh Xuan NguyenThi, Jean-Patrick Bazile and David Bessières

Energies 2018, 11(5), 1212; https://doi.org/10.3390/en11051212 - 9 May 2018

Cited by 33 | Viewed by 7985

Abstract

Density and compressibility are primordial parameters for the optimization of diesel engine operation. With this objective, these properties were reported for waste cooking oil biodiesel and its blends (5% and 10% by volume) mixed with diesel. The density measurements were performed over expanded [...] Read more.

Density and compressibility are primordial parameters for the optimization of diesel engine operation. With this objective, these properties were reported for waste cooking oil biodiesel and its blends (5% and 10% by volume) mixed with diesel. The density measurements were performed over expanded ranges of pressure (0.1 to 140 MPa) and temperature (293.15 to 353.15 K) compatible with engine applications. The isothermal compressibility was estimated within the same experimental range by density differentiation. The Fatty Acid Methyl Esters (FAMEs) profile of the biodiesel was determined using a Gas Chromatography–Mass Spectrometry (GC-MS) technique. The storage stability of the biodiesel was assessed in terms of the reproducibility of the measured properties. The transferability of this biodiesel fuel was discussed on the basis of the standards specifications that support their use in fuel engines. Additionally, this original set of data represents meaningful information to develop new approaches or to evaluate the predictive capability of models previously developed. Full article

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

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43 pages, 18052 KiB

Open AccessEditor’s ChoiceReview

A Comprehensive Review of the Techniques on Regenerative Shock Absorber Systems

by Ran Zhang, Xu Wang and Sabu John

Energies 2018, 11(5), 1167; https://doi.org/10.3390/en11051167 - 7 May 2018

Cited by 67 | Viewed by 16505

Abstract

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their [...] Read more.

In this paper, the current technologies of the regenerative shock absorber systems have been categorized and evaluated. Three drive modes of the regenerative shock absorber systems, namely the direct drive mode, the indirect drive mode and hybrid drive mode are reviewed for their readiness to be implemented. The damping performances of the three different modes are listed and compared. Electrical circuit and control algorithms have also been evaluated to maximize the power output and to deliver the premium ride comfort and handling performance. Different types of parameterized road excitations have been applied to vehicle suspension systems to investigate the performance of the regenerative shock absorbers. The potential of incorporating nonlinearity into the regenerative shock absorber design analysis is discussed. The research gaps for the comparison of the different drive modes and the nonlinearity analysis of the regenerative shock absorbers are identified and, the corresponding research questions have been proposed for future work. Full article

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22 pages, 3212 KiB

Open AccessEditor’s ChoiceArticle

Arrays of Point-Absorbing Wave Energy Converters in Short-Crested Irregular Waves

by Malin Göteman, Cameron McNatt, Marianna Giassi, Jens Engström and Jan Isberg

Energies 2018, 11(4), 964; https://doi.org/10.3390/en11040964 - 17 Apr 2018

Cited by 28 | Viewed by 6471

Abstract

For most wave energy technology concepts, large-scale electricity production and cost-efficiency require that the devices are installed together in parks. The hydrodynamical interactions between the devices will affect the total performance of the park, and the optimization of the park layout and other [...] Read more.

For most wave energy technology concepts, large-scale electricity production and cost-efficiency require that the devices are installed together in parks. The hydrodynamical interactions between the devices will affect the total performance of the park, and the optimization of the park layout and other park design parameters is a topic of active research. Most studies have considered wave energy parks in long-crested, unidirectional waves. However, real ocean waves can be short-crested, with waves propagating simultaneously in several directions, and some studies have indicated that the wave energy park performance might change in short-crested waves. Here, theory for short-crested waves is integrated in an analytical multiple scattering method, and used to evaluate wave energy park performance in irregular, short-crested waves with different number of wave directions and directional spreading parameters. The results show that the energy absorption is comparable to the situation in long-crested waves, but that the power fluctuations are significantly lower. Full article

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23 pages, 9566 KiB

Open AccessFeature PaperEditor’s ChoiceReview

A Comprehensive Overview of CO₂ Flow Behaviour in Deep Coal Seams

by Mandadige Samintha Anne Perera

Energies 2018, 11(4), 906; https://doi.org/10.3390/en11040906 - 12 Apr 2018

Cited by 23 | Viewed by 5034

Abstract

Although enhanced coal bed methane recovery (ECBM) and CO₂ sequestration are effective approaches for achieving lower and safer CO₂ levels in the atmosphere, the effectiveness of CO₂ storage is greatly influenced by the flow ability of the injected CO₂ [...] Read more.

Although enhanced coal bed methane recovery (ECBM) and CO₂ sequestration are effective approaches for achieving lower and safer CO₂ levels in the atmosphere, the effectiveness of CO₂ storage is greatly influenced by the flow ability of the injected CO₂ through the coal seam. A precious understanding of CO₂ flow behaviour is necessary due to various complexities generated in coal seams upon CO₂ injection. This paper aims to provide a comprehensive overview on the CO₂ flow behaviour in deep coal seams, specifically addressing the permeability alterations associated with different in situ conditions. The low permeability nature of natural coal seams has a significant impact on the CO₂ sequestration process. One of the major causative factors for this low permeability nature is the high effective stresses applying on them, which reduces the pore space available for fluid movement with giving negative impact on the flow capability. Further, deep coal seams are often water saturated where, the moisture behave as barriers for fluid movement and thus reduce the seam permeability. Although the high temperatures existing at deep seams cause thermal expansion in the coal matrix, reducing their permeability, extremely high temperatures may create thermal cracks, resulting permeability enhancements. Deep coal seams preferable for CO₂ sequestration generally are high-rank coal, as they have been subjected to greater pressure and temperature variations over a long period of time, which confirm the low permeability nature of such seams. The resulting extremely low CO₂ permeability nature creates serious issues in large-scale CO₂ sequestration/ECBM projects, as critically high injection pressures are required to achieve sufficient CO₂ injection into the coal seam. The situation becomes worse when CO₂ is injected into such coal seams, because CO₂ movement in the coal seam creates a significant influence on the natural permeability of the seams through CO₂ adsorption-induced swelling and hydrocarbon mobilisation. With regard to the temperature, the combined effects of the generation of thermal cracks, thermal expansion, adsorption behaviour alterations and the associated phase transition must be considered before coming to a final conclusion. A reduction in coal’s CO₂ permeability with increasing CO₂ pressure may occur due to swelling and slip-flow effects, both of which are influenced by the phase transition in CO₂ from sub- to super-critical in deep seams. To date, many models have been proposed to simulate CO₂ movement in coal considering various factors, including porosity, effective stress, and swelling/shrinkage. These models have been extremely useful to predict CO₂ injectability into coal seams prior to field projects and have therefore assisted in implementing number of successful CO₂ sequestration/ECBM projects. Full article

(This article belongs to the Collection Bioenergy and Biofuel)

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20 pages, 52962 KiB

Open AccessEditor’s ChoiceArticle

Cascaded Multilevel Inverter Topology Based on Cascaded H-Bridge Multilevel Inverter

by Abdullah M. Noman, Abdullrahman A. Al-Shamma’a, Khaled E. Addoweesh, Ayman A. Alabduljabbar and Abdulrahman I. Alolah

Energies 2018, 11(4), 895; https://doi.org/10.3390/en11040895 - 11 Apr 2018

Cited by 30 | Viewed by 8491

Abstract

A three-phase multilevel inverter topology for use in various applications is proposed. The present topology introduces a combination of a cascaded H-bridge multilevel inverter with a cascaded three-phase voltage source inverter (three-phase triple voltage source inverter (TVSI)). This combination will increase the number [...] Read more.

A three-phase multilevel inverter topology for use in various applications is proposed. The present topology introduces a combination of a cascaded H-bridge multilevel inverter with a cascaded three-phase voltage source inverter (three-phase triple voltage source inverter (TVSI)). This combination will increase the number of voltage levels generated when using fewer components compared with the conventional multilevel inverter topologies for the same voltage levels generated. The other advantage gained from the proposed configuration is the assurance of a continuous power supply to the grid in case of failure in one part of the proposed configuration. In addition, the voltage stresses on switches are reduced by half compared if each part in the proposed topology is working independently. The comparison of the proposed topology with some conventional multilevel inverter topologies is presented. The proposed topology is built in the SIMULINK environment and is simulated under various loads in addition to being connected to the grid. Phase-shifted pulse width modulation technique is used to generate the required switching pulses to drive the switches of the proposed topology. The inverter is experimentally implemented in the lab, and the switching pulses are generated with the help of MicroLabBox produced by dSPACE (digital signal processing and control engineering) company. The simulation and experimental results and their comparisons are presented to verify the proposed topology’s effectiveness and reliability. Full article

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21 pages, 14996 KiB

Open AccessEditor’s ChoiceArticle

Contributions of Bottom-Up Energy Transitions in Germany: A Case Study Analysis

by Ortzi Akizu, Gorka Bueno, Iñaki Barcena, Erol Kurt, Nurettin Topaloğlu and Jose Manuel Lopez-Guede

Energies 2018, 11(4), 849; https://doi.org/10.3390/en11040849 - 5 Apr 2018

Cited by 35 | Viewed by 9314

Abstract

Within the context of an energy transition towards achieving a renewable low-impact energy consumption system, this study analyses how bottom-up initiatives can contribute to state driven top-down efforts to achieve the sustainability related goals of (1) reducing total primary energy consumption; (2) reducing [...] Read more.

Within the context of an energy transition towards achieving a renewable low-impact energy consumption system, this study analyses how bottom-up initiatives can contribute to state driven top-down efforts to achieve the sustainability related goals of (1) reducing total primary energy consumption; (2) reducing residential electricity and heat consumption; and (3) increasing generated renewable energy and even attaining self-sufficiency. After identifying the three most cited German bottom-up energy transition cases, the initiatives have been qualitatively and quantitatively analysed. The case study methodology has been used and each initiative has been examined in order to assess and compare these with the German national panorama. The novel results of the analysis demonstrate the remarkable effects of communal living, cooperative investment and participatory processes on the creation of a new sustainable energy system. The study supports the claim that bottom-up initiatives could also contribute to energy sustainability goals together within the state driven plans. Furthermore, the research proves that the analysed bottom-up transitions are not only environmentally and socially beneficial but they can also be economically feasible, at least in a small scale, such as the current German national top-down energy policy panorama. Full article

(This article belongs to the Special Issue Energy Efficient and Smart Cities)

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17 pages, 26736 KiB

Open AccessEditor’s ChoiceArticle

Novel Concept of an Installation for Sustainable Thermal Utilization of Sewage Sludge

by Wilhelm Jan Tic, Joanna Guziałowska-Tic, Halina Pawlak-Kruczek, Eugeniusz Woźnikowski, Adam Zadorożny, Łukasz Niedźwiecki, Mateusz Wnukowski, Krystian Krochmalny, Michał Czerep, Michał Ostrycharczyk, Marcin Baranowski, Jacek Zgóra and Mateusz Kowal

Energies 2018, 11(4), 748; https://doi.org/10.3390/en11040748 - 26 Mar 2018

Cited by 24 | Viewed by 7010

Abstract

This study proposes an innovative installation concept for the sustainable utilization of sewage sludge. The aim of the study is to prove that existing devices and technologies allow construction of such an installation by integration of a dryer, torrefaction reactor and gasifier with [...] Read more.

This study proposes an innovative installation concept for the sustainable utilization of sewage sludge. The aim of the study is to prove that existing devices and technologies allow construction of such an installation by integration of a dryer, torrefaction reactor and gasifier with engine, thus maximizing recovery of the waste heat by the installation. This study also presents the results of drying tests, performed at a commercial scale paddle dryer as well as detailed analysis of the torrefaction process of dried sewage sludge. Both tests aim to identify potential problems that could occur during the operation. The scarce literature studies published so far on the torrefaction of sewage sludge presents results from batch reactors, thus giving very limited data of the composition of the torgas. This study aims to cover that gap by presenting results from the torrefaction of sewage sludge in a continuously working, laboratory scale, isothermal rotary reactor. The study confirmed the feasibility of a self-sustaining installation of thermal utilization of sewage sludge using low quality heat. Performed study pointed out the most favorable way to use limited amounts of high temperature heat. Plasma gasification of the torrefied sewage sludge has been identified that requires further studies. Full article

(This article belongs to the Special Issue Selected Papers from SDEWES 2017: The 12th Conference on Sustainable Development of Energy, Water and Environment Systems)

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19 pages, 3094 KiB

Open AccessEditor’s ChoiceArticle

Big Data Analytics for Discovering Electricity Consumption Patterns in Smart Cities

by Rubén Pérez-Chacón, José M. Luna-Romera, Alicia Troncoso, Francisco Martínez-Álvarez and José C. Riquelme

Energies 2018, 11(3), 683; https://doi.org/10.3390/en11030683 - 18 Mar 2018

Cited by 90 | Viewed by 11788

Abstract

New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent years, which can be used to extract consumption patterns [...] Read more.

New technologies such as sensor networks have been incorporated into the management of buildings for organizations and cities. Sensor networks have led to an exponential increase in the volume of data available in recent years, which can be used to extract consumption patterns for the purposes of energy and monetary savings. For this reason, new approaches and strategies are needed to analyze information in big data environments. This paper proposes a methodology to extract electric energy consumption patterns in big data time series, so that very valuable conclusions can be made for managers and governments. The methodology is based on the study of four clustering validity indices in their parallelized versions along with the application of a clustering technique. In particular, this work uses a voting system to choose an optimal number of clusters from the results of the indices, as well as the application of the distributed version of the k-means algorithm included in Apache Spark’s Machine Learning Library. The results, using electricity consumption for the years 2011–2017 for eight buildings of a public university, are presented and discussed. In addition, the performance of the proposed methodology is evaluated using synthetic big data, which cab represent thousands of buildings in a smart city. Finally, policies derived from the patterns discovered are proposed to optimize energy usage across the university campus. Full article

(This article belongs to the Special Issue Data Science and Big Data in Energy Forecasting)

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35 pages, 5074 KiB

Open AccessFeature PaperEditor’s ChoiceReview

Model Predictive Control (MPC) for Enhancing Building and HVAC System Energy Efficiency: Problem Formulation, Applications and Opportunities

by Gianluca Serale, Massimo Fiorentini, Alfonso Capozzoli, Daniele Bernardini and Alberto Bemporad

Energies 2018, 11(3), 631; https://doi.org/10.3390/en11030631 - 12 Mar 2018

Cited by 461 | Viewed by 32094

Abstract

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems [...] Read more.

In the last few years, the application of Model Predictive Control (MPC) for energy management in buildings has received significant attention from the research community. MPC is becoming more and more viable because of the increase in computational power of building automation systems and the availability of a significant amount of monitored building data. MPC has found successful implementation in building thermal regulation, fully exploiting the potential of building thermal mass. Moreover, MPC has been positively applied to active energy storage systems, as well as to the optimal management of on-site renewable energy sources. MPC also opens up several opportunities for enhancing energy efficiency in the operation of Heating Ventilation and Air Conditioning (HVAC) systems because of its ability to consider constraints, prediction of disturbances and multiple conflicting objectives, such as indoor thermal comfort and building energy demand. Despite the application of MPC algorithms in building control has been thoroughly investigated in various works, a unified framework that fully describes and formulates the implementation is still lacking. Firstly, this work introduces a common dictionary and taxonomy that gives a common ground to all the engineering disciplines involved in building design and control. Secondly the main scope of this paper is to define the MPC formulation framework and critically discuss the outcomes of different existing MPC algorithms for building and HVAC system management. The potential benefits of the application of MPC in improving energy efficiency in buildings were highlighted. Full article

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16 pages, 8902 KiB

Open AccessEditor’s ChoiceArticle

Smart Global Maximum Power Point Tracking Controller of Photovoltaic Module Arrays

by Long-Yi Chang, Yi-Nung Chung, Kuei-Hsiang Chao and Jia-Jing Kao

Energies 2018, 11(3), 567; https://doi.org/10.3390/en11030567 - 6 Mar 2018

Cited by 14 | Viewed by 3686

Abstract

This study first explored the effect of shading on the output characteristics of modules in a photovoltaic module array. Next, a modified particle swarm optimization (PSO) method was employed to track the maximum power point of the multiple-peak characteristic curve of the array. [...] Read more.

This study first explored the effect of shading on the output characteristics of modules in a photovoltaic module array. Next, a modified particle swarm optimization (PSO) method was employed to track the maximum power point of the multiple-peak characteristic curve of the array. Through the optimization method, the weighting value and cognition learning factor decreased with an increasing number of iterations, whereas the social learning factor increased, thereby enhancing the tracking capability of a maximum power point tracker. In addition, the weighting value was slightly modified on the basis of the changes in the slope and power of the characteristic curve to increase the tracking speed and stability of the tracker. Finally, a PIC18F8720 microcontroller was coordinated with peripheral hardware circuits to realize the proposed PSO method, which was then adopted to track the maximum power point of the power–voltage (P–V) output characteristic curve of the photovoltaic module array under shading. Subsequently, tests were conducted to verify that the modified PSO method exhibited favorable tracking speed and accuracy. Full article

(This article belongs to the Section I: Energy Fundamentals and Conversion)

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15 pages, 21969 KiB

Open AccessEditor’s ChoiceArticle

Wind Predictions Upstream Wind Turbines from a LiDAR Database

by Soledad Le Clainche, Luis S. Lorente and José M. Vega

Energies 2018, 11(3), 543; https://doi.org/10.3390/en11030543 - 3 Mar 2018

Cited by 36 | Viewed by 4721

Abstract

This article presents a new method to predict the wind velocity upstream a horizontal axis wind turbine from a set of light detection and ranging (LiDAR) measurements. The method uses higher order dynamic mode decomposition (HODMD) to construct a reduced order model (ROM) [...] Read more.

This article presents a new method to predict the wind velocity upstream a horizontal axis wind turbine from a set of light detection and ranging (LiDAR) measurements. The method uses higher order dynamic mode decomposition (HODMD) to construct a reduced order model (ROM) that can be extrapolated in space. LiDAR measurements have been carried out upstream a wind turbine at six different planes perpendicular to the wind turbine axis. This new HODMD-based ROM predicts with high accuracy the wind velocity during a timespan of 24 h in a plane of measurements that is more than 225 m far away from the wind turbine. Moreover, the technique introduced is general and obtained with an almost negligible computational cost. This fact makes it possible to extend its application to both vertical axis wind turbines and real-time operation. Full article

(This article belongs to the Special Issue Data Science and Big Data in Energy Forecasting)

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26 pages, 1172 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Towards Biochar and Hydrochar Engineering—Influence of Process Conditions on Surface Physical and Chemical Properties, Thermal Stability, Nutrient Availability, Toxicity and Wettability

by Alba Dieguez-Alonso, Axel Funke, Andrés Anca-Couce, Alessandro Girolamo Rombolà, Gerardo Ojeda, Jörg Bachmann and Frank Behrendt

Energies 2018, 11(3), 496; https://doi.org/10.3390/en11030496 - 27 Feb 2018

Cited by 104 | Viewed by 11090

Abstract

The impact of conversion process parameters in pyrolysis (maximum temperature, inert gas flow rate) and hydrothermal carbonization (maximum temperature, residence time and post-washing) on biochar and hydrochar properties is investigated. Pine wood (PW) and corn digestate (CD), with low and high inorganic species [...] Read more.

The impact of conversion process parameters in pyrolysis (maximum temperature, inert gas flow rate) and hydrothermal carbonization (maximum temperature, residence time and post-washing) on biochar and hydrochar properties is investigated. Pine wood (PW) and corn digestate (CD), with low and high inorganic species content respectively, are used as feedstock. CD biochars show lower H/C ratios, thermal recalcitrance and total specific surface area than PW biochars, but higher mesoporosity. CD and PW biochars present higher naphthalene and phenanthrene contents, respectively, which may indicate different reaction pathways. High temperatures (>500 °C) lead to lower PAH (polycyclic aromatic hydrocarbons) content (<12 mg/kg) and higher specific surface area. With increasing process severity the biochars carbon content is also enhanced, as well as the thermal stability. High inert gas flow rates increase the microporosity and wettability of biochars. In hydrochars the high inorganic content favor decarboxylation over dehydration reactions. Hydrochars show mainly mesoporosity, with a higher pore volume but generally lower specific surface area than biochars. Biochars present negligible availability of NO

_{3}^{-}

and NH

_{4}^{+}

, irrespective of the nitrogen content of the feedstock. For hydrochars, a potential increase in availability of NO

_{3}^{-}

, NH

_{4}^{+}

, PO

_{4}^{3 -}

, and K

^{+}

with respect to the feedstock is possible. The results from this work can be applied to “engineer” appropriate biochars with respect to soil demands and certification requirements. Full article

(This article belongs to the Special Issue Biomass Chars: Elaboration, Characterization and Applications Ⅱ)

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13 pages, 2409 KiB

Open AccessEditor’s ChoiceArticle

PV Hosting Capacity Dependence on Harmonic Voltage Distortion in Low-Voltage Grids: Model Validation with Experimental Data

by Tiago E. C. de Oliveira, Pedro M. S. Carvalho, Paulo F. Ribeiro and Benedito D. Bonatto

Energies 2018, 11(2), 465; https://doi.org/10.3390/en11020465 - 23 Feb 2018

Cited by 46 | Viewed by 6105

Abstract

This paper introduces a brief analysis on hosting capacity and related concepts as applied to distribution network systems. Furthermore, it addresses the applicability of hosting capacity study methodologies to harmonic voltage distortion caused by photovoltaic panels (PV) connected at a low-voltage (LV) side [...] Read more.

This paper introduces a brief analysis on hosting capacity and related concepts as applied to distribution network systems. Furthermore, it addresses the applicability of hosting capacity study methodologies to harmonic voltage distortion caused by photovoltaic panels (PV) connected at a low-voltage (LV) side of a university campus grid. The analysis of the penetration of new distributed generation technologies, such as PV panels, in the distribution grid of the campus was carried out via measurement processes, and later by computer simulations analyzing a new concept of the hosting capacity approach in relation to voltage harmonics distortion. The voltage rise due to harmonic injection is analyzed and discussed with the aim of validating the discussed model and also putting forward recommendations for connecting PV generation across other network systems. Full article

(This article belongs to the Special Issue Distributed and Renewable Power Generation)

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19 pages, 2380 KiB

Open AccessEditor’s ChoiceArticle

A Fully Three Dimensional Semianalytical Model for Shale Gas Reservoirs with Hydraulic Fractures

by Yuwei Li, Lihua Zuo, Wei Yu and Youguang Chen

Energies 2018, 11(2), 436; https://doi.org/10.3390/en11020436 - 15 Feb 2018

Cited by 25 | Viewed by 4370

Abstract

Two challenges exist for modeling gas transport in shale. One is the existence of complex gas transport mechanisms, and the other is the impact of hydraulic fracture networks. In this study, a truly three dimensional semianalytical model was developed for shale gas reservoirs [...] Read more.

Two challenges exist for modeling gas transport in shale. One is the existence of complex gas transport mechanisms, and the other is the impact of hydraulic fracture networks. In this study, a truly three dimensional semianalytical model was developed for shale gas reservoirs with hydraulic fractures of various shapes. Using the instantaneous point source solution, the pressure are solved for a bounded reservoir with fully 3D, partially penetrated hydraulic fractures of different strike angles and dip angles. The fractures could have various shapes such as rectangles, disks and ellipses. The shale gas diffusion equations considers complex transport mechanism such as gas slippage and gas diffusion. This semianalytical model is verified with a commercial software and an analytical method for single fully penetrated rectangle fracture, and the production results of shale gas are consistent. The impacts of fracture height and strike angles are investigated by five systematically constructed models. The comparison shows that the production increases proportionally with the fracture height, and decreases with the increase of strike angles. The method proposed in this study could also be applied in well testing to analyze the reservoir properties and used to forecast the production for tight oil and conventional resources. Full article

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15 pages, 5269 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

A Traveling-Wave-Based Fault Location Scheme for MMC-Based Multi-Terminal DC Grids

by Shuo Zhang, Guibin Zou, Qiang Huang and Houlei Gao

Energies 2018, 11(2), 401; https://doi.org/10.3390/en11020401 - 9 Feb 2018

Cited by 25 | Viewed by 4634

Abstract

This paper presents a novel fault location scheme of DC line in modular multilevel converter (MMC)-based multi-terminal DC (MTDC) grids. Considering the low-inertia characteristics and the meshed topology, the scheme, based on traveling-wave principle, is divided into three steps, namely, faulty pole identification, [...] Read more.

This paper presents a novel fault location scheme of DC line in modular multilevel converter (MMC)-based multi-terminal DC (MTDC) grids. Considering the low-inertia characteristics and the meshed topology, the scheme, based on traveling-wave principle, is divided into three steps, namely, faulty pole identification, faulty segment determination and fault-distance calculation. With accurate amplitude, polarities and arrival times of the first arrival current traveling waves (FACTWs) collected from time-synchronized measurements taken just at the converter stations, the proposed scheme can correctly determine the faulty pole, the faulty segment and the precise fault location. The continuous wavelet transform (CWT) is deployed to extract the required features of the input signals at the DC lines. Since the scheme merely needs the features of FACTWs, the practical difficulties of detecting subsequent traveling waves are avoided. A four-terminal MMC-based high voltage direct current (HVDC) grid was built in PSCAD/EMTDC software to evaluate the performance of the fault-location scheme. Simulation results for different cases demonstrate that the proposed fault-location scheme has high accuracy, good adaptability and reliability. Furthermore, the algorithm can be used for a MMC-MTDC grid with any number of meshes. Full article

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

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23 pages, 8186 KiB

Open AccessEditor’s ChoiceArticle

Dynamic Analysis of a Hybrid Energy Storage System (H-ESS) Coupled to a Photovoltaic (PV) Plant

by Linda Barelli, Gianni Bidini, Fabio Bonucci, Luca Castellini, Simone Castellini, Andrea Ottaviano, Dario Pelosi and Alberto Zuccari

Energies 2018, 11(2), 396; https://doi.org/10.3390/en11020396 - 8 Feb 2018

Cited by 62 | Viewed by 7109

Abstract

Nowadays energy storage is strongly needed to allow grid safety and stability due to the wide penetration of renewable plants. Mainly economic and technological issues impede a relevant integration of conventional storage devices in the energy system. In this scenario, the hybridization of [...] Read more.

Nowadays energy storage is strongly needed to allow grid safety and stability due to the wide penetration of renewable plants. Mainly economic and technological issues impede a relevant integration of conventional storage devices in the energy system. In this scenario, the hybridization of different storage technologies can be a techno-economic solution useful to overcome these issues and promote their diffusion. Hybridization allows multi-operation modes of the Energy Storage System (ESS), merging the positive features of base-technologies and extending their application ranges. This paper provides a dynamic analysis of a hybrid energy storage system (H-ESS) consisting of a flywheel and a battery pack coupled to a photovoltaic generation plant and a residential load up to 20 kW. A dynamic model of the overall micro-grid (MG) was developed implementing the H-ESS preliminary sizing and a suitable management algorithm. The instantaneous behavior of each component was evaluated. A brief summary of the MG performance at different weather and load conditions was provided together with a characterization of the impact of power fluctuations on the battery current and on the power exchange with the grid. Full article

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

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14 pages, 929 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

Development of Easily Accessible Electricity Consumption Model Using Open Data and GA-SVR

by Seunghyeon Wang, Hyeonyong Hae and Juhyung Kim

Energies 2018, 11(2), 373; https://doi.org/10.3390/en11020373 - 5 Feb 2018

Cited by 17 | Viewed by 5919

Abstract

In many countries, DR (Demand Response) has been developed for which customers are motivated to save electricity by themselves during peak time to prevent grand-scale blackouts. One of the common methods in DR, is CPP (Critical Peak Pricing). Predicting energy consumption is recognized [...] Read more.

In many countries, DR (Demand Response) has been developed for which customers are motivated to save electricity by themselves during peak time to prevent grand-scale blackouts. One of the common methods in DR, is CPP (Critical Peak Pricing). Predicting energy consumption is recognized as one of the tool for dealing with CPP. There are a variety of studies in developing the model of energy consumption, which is based on energy simulation, data-driven model or metamodelling. However, it is difficult for general users to use these models due to requirement of various sensing data and expertise. And it also takes long time to simulate the models. These limitations can be an obstacle for achieving CPP’s purpose that encourages general users to manage their energy usage by themselves. As an alternative, this research suggests to use open data and GA (Genetic Algorithm)–SVR (Support Vector Regression). The model is applied to a hospital in Korea and 34,636 data sets (1 year) are collected while 31,756 (11 months) sets are used for training and 2880 sets (1 month) are used for validation. As a result, the performance of proposed model is 14.17% in CV (RMSE), which satisfies the Korea Energy Agency’s and ASHRAE (American Society of Heating, Refrigerating and Air-Conditioning Engineers) error allowance range of ±30%, and ±20% respectively. Full article

(This article belongs to the Special Issue Building Energy Use: Modeling and Analysis)

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15 pages, 3319 KiB

Open AccessEditor’s ChoiceArticle

Data Analysis of Heating Systems for Buildings—A Tool for Energy Planning, Policies and Systems Simulation

by Michel Noussan and Benedetto Nastasi

Energies 2018, 11(1), 233; https://doi.org/10.3390/en11010233 - 18 Jan 2018

Cited by 39 | Viewed by 7218

Abstract

Heating and cooling in buildings is a central aspect for adopting energy efficiency measures and implementing local policies for energy planning. The knowledge of features and performance of those existing systems is fundamental to conceiving realistic energy savings strategies. Thanks to Information and [...] Read more.

Heating and cooling in buildings is a central aspect for adopting energy efficiency measures and implementing local policies for energy planning. The knowledge of features and performance of those existing systems is fundamental to conceiving realistic energy savings strategies. Thanks to Information and Communication Technologies (ICT) development and energy regulations’ progress, the amount of data able to be collected and processed allows detailed analyses on entire regions or even countries. However, big data need to be handled through proper analyses, to identify and highlight the main trends by selecting the most significant information. To do so, careful attention must be paid to data collection and preprocessing, for ensuring the coherence of the associated analyses and the accuracy of results and discussion. This work presents an insightful analysis on building heating systems of the most populated Italian region—Lombardy. From a dataset of almost 2.9 million of heating systems, selected reference values are presented, aiming at describing the features of current heating systems in households, offices and public buildings. Several aspects are considered, including the type of heating systems, their thermal power, fuels, age, nominal and measured efficiency. The results of this work can be a support for local energy planners and policy makers, and for a more accurate simulation of existing energy systems in buildings. Full article

(This article belongs to the Special Issue Energy Production Systems)

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26 pages, 4874 KiB

Open AccessEditor’s ChoiceArticle

Conceptual Design of Operation Strategies for Hybrid Electric Aircraft

by Julian Hoelzen, Yaolong Liu, Boris Bensmann, Christopher Winnefeld, Ali Elham, Jens Friedrichs and Richard Hanke-Rauschenbach

Energies 2018, 11(1), 217; https://doi.org/10.3390/en11010217 - 16 Jan 2018

Cited by 177 | Viewed by 21291

Abstract

Ambitious targets to reduce emissions caused by aviation in the light of an expected ongoing rise of the air transport demand in the future drive the research of propulsion systems with lower CO₂ emissions. Regional hybrid electric aircraft (HEA) powered by conventional [...] Read more.

Ambitious targets to reduce emissions caused by aviation in the light of an expected ongoing rise of the air transport demand in the future drive the research of propulsion systems with lower CO₂ emissions. Regional hybrid electric aircraft (HEA) powered by conventional gas turbines and battery powered electric motors are investigated to test hybrid propulsion operation strategies. Especially the role of the battery within environmentally friendly concepts with significantly reduced carbon footprint is analyzed. Thus, a new simulation approach for HEA is introduced. The main findings underline the importance of choosing the right power-to-energy-ratio of a battery according to the flight mission. The gravimetric energy and power density of the electric storages determine the technologically feasibility of hybrid concepts. Cost competitive HEA configurations are found, but do not promise the targeted CO₂ emission savings, when the well-to-wheel system is regarded with its actual costs. Sensitivity studies are used to determine external levers that favor the profitability of HEA. Full article

(This article belongs to the Special Issue Towards a Transformation to Sustainable Aviation Systems)

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25 pages, 8172 KiB

Open AccessEditor’s ChoiceArticle

Optimal Operation of Interdependent Power Systems and Electrified Transportation Networks

by M. Hadi Amini and Orkun Karabasoglu

Energies 2018, 11(1), 196; https://doi.org/10.3390/en11010196 - 14 Jan 2018

Cited by 79 | Viewed by 7768

Abstract

Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with [...] Read more.

Electrified transportation and power systems are mutually coupled networks. In this paper, a novel framework is developed for interdependent power and transportation networks. Our approach constitutes solving an iterative least cost vehicle routing process, which utilizes the communication of electrified vehicles (EVs) with competing charging stations, to exchange data such as electricity price, energy demand, and time of arrival. The EV routing problem is solved to minimize the total cost of travel using the Dijkstra algorithm with the input from EVs battery management system, electricity price from charging stations, powertrain component efficiencies and transportation network traffic conditions. Through the bidirectional communication of EVs with competing charging stations, EVs’ charging demand estimation is done much more accurately. Then the optimal power flow problem is solved for the power system, to find the locational marginal price at load buses where charging stations are connected. Finally, the electricity prices were communicated from the charging stations to the EVs, and the loop is closed. Locational electricity price acts as the shared parameter between the two optimization problems, i.e., optimal power flow and optimal routing problem. Electricity price depends on the power demand, which is affected by the charging of EVs. On the other hand, location of EV charging stations and their different pricing strategies might affect the routing decisions of the EVs. Our novel approach that combines the electrified transportation with power system operation, holds tremendous potential for solving electrified transportation issues and reducing energy costs. The effectiveness of the proposed approach is demonstrated using Shanghai transportation network and IEEE 9-bus test system. The results verify the cost-savings for both power system and transportation networks. Full article

(This article belongs to the Special Issue Distribution System Operation and Control)

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32 pages, 6144 KiB

Open AccessEditor’s ChoiceArticle

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

by Wim Munters and Johan Meyers

Energies 2018, 11(1), 177; https://doi.org/10.3390/en11010177 - 11 Jan 2018

Cited by 135 | Viewed by 8840

Abstract

In wind farms, wakes originating from upstream turbines cause reduced energy extraction and increased loading variability in downstream rows. The prospect of mitigating these detrimental effects through coordinated controllers at the wind-farm level has fueled a multitude of research efforts in wind-farm control. [...] Read more.

In wind farms, wakes originating from upstream turbines cause reduced energy extraction and increased loading variability in downstream rows. The prospect of mitigating these detrimental effects through coordinated controllers at the wind-farm level has fueled a multitude of research efforts in wind-farm control. The main strategies in wind-farm control are to influence the velocity deficits in the wake by deviating from locally optimal axial induction setpoints on the one hand, and steering wakes away from downstream rows through yaw misalignment on the other hand. The current work investigates dynamic induction and yaw control of individual turbines for wind-farm power maximization in large-eddy simulations. To this end, receding-horizon optimal control techniques combined with continuous adjoint gradient evaluations are used. We study a 4 × 4 aligned wind farm, and find that for this farm layout yaw control is more effective than induction control, both for uniform and turbulent inflow conditions. Analysis of optimal yaw controls leads to the definition of two simplified yaw control strategies, in which wake meandering and wake redirection are exploited respectively. Furthermore it is found that dynamic yawing provides significant benefits over static yaw control in turbulent flow environments, whereas this is not the case for uniform inflow. Finally, the potential of combining overinductive axial induction control with yaw control is shown, with power gains that approximate the sum of those achieved by each control strategy separately. Full article

(This article belongs to the Special Issue Wind Turbine Loads and Wind Plant Performance)

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18 pages, 1924 KiB

Open AccessEditor’s ChoiceReview

Role and Potential of Direct Interspecies Electron Transfer in Anaerobic Digestion

by Gahyun Baek, Jaai Kim, Jinsu Kim and Changsoo Lee

Energies 2018, 11(1), 107; https://doi.org/10.3390/en11010107 - 3 Jan 2018

Cited by 276 | Viewed by 15026

Abstract

Anaerobic digestion (AD) is an effective biological treatment for stabilizing organic compounds in waste/wastewater and in simultaneously producing biogas. However, it is often limited by the slow reaction rates of different microorganisms’ syntrophic biological metabolisms. Stable and fast interspecies electron transfer (IET) between [...] Read more.

Anaerobic digestion (AD) is an effective biological treatment for stabilizing organic compounds in waste/wastewater and in simultaneously producing biogas. However, it is often limited by the slow reaction rates of different microorganisms’ syntrophic biological metabolisms. Stable and fast interspecies electron transfer (IET) between volatile fatty acid-oxidizing bacteria and hydrogenotrophic methanogens is crucial for efficient methanogenesis. In this syntrophic interaction, electrons are exchanged via redox mediators such as hydrogen and formate. Recently, direct IET (DIET) has been revealed as an important IET route for AD. Microorganisms undergoing DIET form interspecies electrical connections via membrane-associated cytochromes and conductive pili; thus, redox mediators are not required for electron exchange. This indicates that DIET is more thermodynamically favorable than indirect IET. Recent studies have shown that conductive materials (e.g., iron oxides, activated carbon, biochar, and carbon fibers) can mediate direct electrical connections for DIET. Microorganisms attach to conductive materials’ surfaces or vice versa according to particle size, and form conductive biofilms or aggregates. Different conductive materials promote DIET and improve AD performance in digesters treating different feedstocks, potentially suggesting a new approach to enhancing AD performance. This review discusses the role and potential of DIET in methanogenic systems, especially with conductive materials for promoting DIET. Full article

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23 pages, 23119 KiB

Open AccessEditor’s ChoiceArticle

Flow Adjustment Inside and Around Large Finite-Size Wind Farms

by Ka Ling Wu and Fernando Porté-Agel

Energies 2017, 10(12), 2164; https://doi.org/10.3390/en10122164 - 18 Dec 2017

Cited by 80 | Viewed by 11034

Abstract

In this study, large-eddy simulations are performed to investigate the flow inside and around large finite-size wind farms in conventionally-neutral atmospheric boundary layers. Special emphasis is placed on characterizing the different farm-induced flow regions, including the induction, entrance and development, fully-developed, exit and [...] Read more.

In this study, large-eddy simulations are performed to investigate the flow inside and around large finite-size wind farms in conventionally-neutral atmospheric boundary layers. Special emphasis is placed on characterizing the different farm-induced flow regions, including the induction, entrance and development, fully-developed, exit and farm wake regions. The wind farms extend 20 km in the streamwise direction and comprise 36 wind turbine rows arranged in aligned and staggered configurations. Results show that, under weak free-atmosphere stratification (

Γ = 1

K/km), the flow inside and above both wind farms, and thus the turbine power, do not reach the fully-developed regime even though the farm length is two orders of magnitude larger than the boundary layer height. In that case, the wind farm induction region, affected by flow blockage, extends upwind about 0.8 km and leads to a power reduction of 1.3% and 3% at the first row of turbines for the aligned and staggered layouts, respectively. The wind farm wake leads to velocity deficits at hub height of around 3.5% at a downwind distance of 10 km for both farm layouts. Under stronger stratification (

Γ = 5

K/km), the vertical deflection of the subcritical flow induced by the wind farm at its entrance and exit regions triggers standing gravity waves whose effects propagate upwind. They, in turn, induce a large decelerating induction region upwind of the farm leading edge, and an accelerating exit region upwind of the trailing edge, both extending about 7 km. As a result, the turbine power output in the entrance region decreases more than 35% with respect to the weakly stratified case. It increases downwind as the flow adjusts, reaching the fully-developed regime only for the staggered layout at a distance of about 8.5 km from the farm edge. The flow acceleration in the exit region leads to an increase of the turbine power with downwind distance in that region, and a relatively fast (compared with the weakly stratified case) recovery of the farm wake, which attains its inflow hub height speed at a downwind distance of 5 km. Full article

(This article belongs to the Collection Wind Turbines)

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42 pages, 1535 KiB

Open AccessEditor’s ChoiceReview

Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids

by Holger C. Hesse, Michael Schimpe, Daniel Kucevic and Andreas Jossen

Energies 2017, 10(12), 2107; https://doi.org/10.3390/en10122107 - 11 Dec 2017

Cited by 614 | Viewed by 53273

Abstract

Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application [...] Read more.

Battery energy storage systems have gained increasing interest for serving grid support in various application tasks. In particular, systems based on lithium-ion batteries have evolved rapidly with a wide range of cell technologies and system architectures available on the market. On the application side, different tasks for storage deployment demand distinct properties of the storage system. This review aims to serve as a guideline for best choice of battery technology, system design and operation for lithium-ion based storage systems to match a specific system application. Starting with an overview to lithium-ion battery technologies and their characteristics with respect to performance and aging, the storage system design is analyzed in detail based on an evaluation of real-world projects. Typical storage system applications are grouped and classified with respect to the challenges posed to the battery system. Publicly available modeling tools for technical and economic analysis are presented. A brief analysis of optimization approaches aims to point out challenges and potential solution techniques for system sizing, positioning and dispatch operation. For all areas reviewed herein, expected improvements and possible future developments are highlighted. In order to extract the full potential of stationary battery storage systems and to enable increased profitability of systems, future research should aim to a holistic system level approach combining not only performance tuning on a battery cell level and careful analysis of the application requirements, but also consider a proper selection of storage sub-components as well as an optimized system operation strategy. Full article

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

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13 pages, 2995 KiB

Open AccessEditor’s ChoiceArticle

Spray Combustion Characteristics and Soot Emission Reduction of Hydrous Ethanol Diesel Emulsion Fuel Using Color-Ratio Pyrometry

by Xiaoqing Zhang, Tie Li, Pengfei Ma and Bin Wang

Energies 2017, 10(12), 2062; https://doi.org/10.3390/en10122062 - 5 Dec 2017

Cited by 21 | Viewed by 4944

Abstract

To elucidate the relationship between physicochemical properties, spray characteristics, and combustion performance, a series of experiments have been conducted in a constant volume vessel with injection of hydrous ethanol diesel emulsion and regular diesel. HE30 (emulsion with 30% volume fraction of 20% water-containing [...] Read more.

To elucidate the relationship between physicochemical properties, spray characteristics, and combustion performance, a series of experiments have been conducted in a constant volume vessel with injection of hydrous ethanol diesel emulsion and regular diesel. HE30 (emulsion with 30% volume fraction of 20% water-containing ethanol and 70% volume fraction of 0# diesel) is developed using Shah’s technique and regular diesel is also employed for comparison. Firstly, the physicochemical properties of two kinds of fuels are investigated. Then, the non-evaporating and evaporating spray characteristics are examined through the high-speed shadowgraphs. Finally, spray combustion experiments under different ambient oxygen concentrations are carried out, and color-ratio pyrometry (CRP) is applied to measure the flame temperature and soot concentration (KL) distributions. The results indicate that the physicochemical properties, such as density, surface tension, kinematic viscosity, cetane number, and oxygen content, have significant impact on the spray mixture formation and combustion performance. HE30 exhibits lower soot emissions than that of regular diesel. Further analysis supports the standpoint that the hydrous ethanol diesel emulsion can suppress the soot and NO_x simultaneously. Therefore, the hydrous ethanol diesel emulsion has great potential to be an alternative clean energy resource. Full article

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25 pages, 1024 KiB

Open AccessEditor’s ChoiceArticle

Towards Efficient Energy Management of Smart Buildings Exploiting Heuristic Optimization with Real Time and Critical Peak Pricing Schemes

by Sheraz Aslam, Zafar Iqbal, Nadeem Javaid, Zahoor Ali Khan, Khursheed Aurangzeb and Syed Irtaza Haider

Energies 2017, 10(12), 2065; https://doi.org/10.3390/en10122065 - 5 Dec 2017

Cited by 119 | Viewed by 8774

Abstract

The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the [...] Read more.

The smart grid plays a vital role in decreasing electricity cost through Demand Side Management (DSM). Smart homes, a part of the smart grid, contribute greatly to minimizing electricity consumption cost via scheduling home appliances. However, user waiting time increases due to the scheduling of home appliances. This scheduling problem is the motivation to find an optimal solution that could minimize the electricity cost and Peak to Average Ratio (PAR) with minimum user waiting time. There are many studies on Home Energy Management (HEM) for cost minimization and peak load reduction. However, none of the systems gave sufficient attention to tackle multiple parameters (i.e., electricity cost and peak load reduction) at the same time as user waiting time was minimum for residential consumers with multiple homes. Hence, in this work, we propose an efficient HEM scheme using the well-known meta-heuristic Genetic Algorithm (GA), the recently developed Cuckoo Search Optimization Algorithm (CSOA) and the Crow Search Algorithm (CSA), which can be used for electricity cost and peak load alleviation with minimum user waiting time. The integration of a smart Electricity Storage System (ESS) is also taken into account for more efficient operation of the Home Energy Management System (HEMS). Furthermore, we took the real-time electricity consumption pattern for every residence, i.e., every home has its own living pattern. The proposed scheme is implemented in a smart building; comprised of thirty smart homes (apartments), Real-Time Pricing (RTP) and Critical Peak Pricing (CPP) signals are examined in terms of electricity cost estimation for both a single smart home and a smart building. In addition, feasible regions are presented for single and multiple smart homes, which show the relationship among the electricity cost, electricity consumption and user waiting time. Experimental results demonstrate the effectiveness of our proposed scheme for single and multiple smart homes in terms of electricity cost and PAR minimization. Moreover, there exists a tradeoff between electricity cost and user waiting. Full article

(This article belongs to the Special Issue Intelligent Management and Control of Energy Storage Systems)

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14 pages, 628 KiB

Open AccessEditor’s ChoiceArticle

Normal Behaviour Models for Wind Turbine Vibrations: Comparison of Neural Networks and a Stochastic Approach

by Pedro G. Lind, Luis Vera-Tudela, Matthias Wächter, Martin Kühn and Joachim Peinke

Energies 2017, 10(12), 1944; https://doi.org/10.3390/en10121944 - 23 Nov 2017

Cited by 42 | Viewed by 7097

Abstract

To monitor wind turbine vibrations, normal behaviour models are built to predict tower top accelerations and drive-train vibrations. Signal deviations from model prediction are labelled as anomalies and are further investigated. In this paper we assess a stochastic approach to reconstruct the 1 [...] Read more.

To monitor wind turbine vibrations, normal behaviour models are built to predict tower top accelerations and drive-train vibrations. Signal deviations from model prediction are labelled as anomalies and are further investigated. In this paper we assess a stochastic approach to reconstruct the 1 Hz tower top acceleration signal, which was measured in a wind turbine located at the wind farm Alpha Ventus in the German North Sea. We compare the resulting data reconstruction with that of a model based on a neural network, which has been previously reported as a data-mining algorithm suitable for reconstructing this signal. Our results present evidence that the stochastic approach outperforms the neural network in the high frequency domain (1 Hz). Although neural network retrieves accurate step-forward predictions, with low mean square errors, the stochastic approach predictions better preserve the statistics and the frequency components of the original signal, retaining high accuracy levels. The implementation of our stochastic approach is available as open source code and can easily be adapted for other situations involving stochastic data reconstruction. Based on our findings we argue that such an approach could be implemented in signal reconstruction for monitoring purposes or for abnormal behaviour detection. Full article

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

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21 pages, 5348 KiB

Open AccessEditor’s ChoiceArticle

Factors Influencing the Thermal Efficiency of Horizontal Ground Heat Exchangers

by Eloisa Di Sipio and David Bertermann

Energies 2017, 10(11), 1897; https://doi.org/10.3390/en10111897 - 18 Nov 2017

Cited by 39 | Viewed by 7059

Abstract

The performance of very shallow geothermal systems (VSGs), interesting the first 2 m of depth from ground level, is strongly correlated to the kind of sediment locally available. These systems are attractive due to their low installation costs, less legal constraints, easy maintenance [...] Read more.

The performance of very shallow geothermal systems (VSGs), interesting the first 2 m of depth from ground level, is strongly correlated to the kind of sediment locally available. These systems are attractive due to their low installation costs, less legal constraints, easy maintenance and possibility for technical improvements. The Improving Thermal Efficiency of horizontal ground heat exchangers Project (ITER) aims to understand how to enhance the heat transfer of the sediments surrounding the pipes and to depict the VSGs behavior in extreme thermal situations. In this regard, five helices were installed horizontally surrounded by five different backfilling materials under the same climatic conditions and tested under different operation modes. The field test monitoring concerned: (a) monthly measurement of thermal conductivity and moisture content on surface; (b) continuous recording of air and ground temperature (inside and outside each helix); (c) continuous climatological and ground volumetric water content (VWC) data acquisition. The interactions between soils, VSGs, environment and climate are presented here, focusing on the differences and similarities between the behavior of the helix and surrounding material, especially when the heat pump is running in heating mode for a very long time, forcing the ground temperature to drop below 0 °C. Full article

(This article belongs to the Special Issue Low Enthalpy Geothermal Energy)

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