Editor’s Choice Articles

In this paper, a fuzzy-logic-based energy management system and a multi-port quasi-z-source converter that utilizes hybrid renewable energy sources are proposed. The system ensures that each energy source module can be used individually by employing fuzzy logic to define the power modes. This approach also helps to prevent switching losses resulting from the extra switching of the source modules. In addition, the proposed energy management does not have a mathematical model, so its applicability is simple, and it is suitable for different multiple-input topologies. The Mamdani fuzzy inference system can be designed to capture the nonlinear behavior of the system owing to linguistic rules. Moreover, the switching losses of the multiport modules were significantly reduced by adopting the quasi-z-source network to the end of the multiport converter. Furthermore, different errors, such as the root mean square error (RMSE), average squared error (ASE), average absolute error (AAE), average time-weighted absolute error (ATWAE), tracking error (TE), and unscaled mean bounded relative absolute error (UMBRAE), were applied to evaluate the fuzzy logic performance from different perspectives. The simulation results were obtained using MATLAB Simulink, and the experimental results were obtained by connecting the circuit to MATLAB Simulink using an Arduino Due. Full article

This work studies the term structure dynamics in the natural gas futures market, focusing on the Dutch Title Transfer Facility (TTF) daily futures prices. At first, using the whole dataset, we compared the in-sample fitting performance of three models: the four-factor dynamic Nelson–Siegel–Svensson (4F-DNSS) model, the five-factor dynamic De Rezende–Ferreira (5F-DRF) model, and the B-spline model. Our findings suggest that B-spline is the method that achieves the best in-line fitting results. Then, we turned our attention to forecasting, using data from 20 January 2011 to 13 May 2022 as the training set and the remaining data, from 16 May to 13 June 2022, for day-ahead predictions. In this second part of the work we combined the above mentioned models (4F-DNSS, 5F-DRF and B-spline) with a Nonlinear Autoregressive Neural Network (NAR-NN), asking the NAR-NN to provide parameter tuning. All the models provided accurate out-of-sample prediction; nevertheless, based on extensive statistical tests, we conclude that, as in the previous case, B-spline (combined with an NAR-NN) ensured the best out-of-sample prediction. Full article

This study assesses the biomethane (CH₄) generation and greenhouse gas (GHG) emissions resulting from municipal solid waste landfilling in Phnom Penh, Cambodia, with a focus on the impact of fugitive CH₄ emissions and operation processes in four landfilling scenarios: simple dumping (S1), improved management with leachate treatment (S2), engineered landfill with flaring (S3), and engineered landfill with energy recovery (S4). The study also considered the environmental benefits of carbon sequestration and landfill gas utilization. The LandGEM and IPCC FOD models were used to calculate CH₄ generation over the period of 2009–2022, and it was found that approximately 18 and 21 M kg/year of CH₄ were released, respectively. The energy potential from CH₄ recovery was 51–61 GWh/year. Overall, GHG emissions in S2 were the highest, amounting to 409–509 M kg CO₂-eq/year, while S1 had lower emissions at 397–496 M kg CO₂-eq/year. Flaring-captured CH₄ in S3 could reduce GHG emissions by at least 55%, and using captured CH₄ for electricity production in S4 could mitigate at least 83% of GHG emissions. Electricity recovery (S4) could avoid significant amounts of GHG emissions (−52 to −63 kg CO₂-eq/tMSW). The study suggests that landfill gas-to-energy could significantly reduce GHG emissions. Full article

The influence of different carbon sources, including anthracite, calcined petroleum coke, three samples of high-temperature coke, biochar, and a mixture of 50 wt.% biochar and 50 wt.% coke, on slag foaming behavior was studied. The slag’s composition was set to FeO-CaO-Al₂O₃-MgO-SiO₂, and the temperature for slag foaming was 1600 °C. The effect of the carbon sources was evaluated using foaming characteristics (foam height, foam volume, relative foaming height, and gas fraction), X-ray diffraction (XRD), chemical analysis of the slag foams, Mossbauer spectroscopy, observation by scanning electron microscope (SEM), and energy-dispersive spectroscopy (EDS) mapping. Different foaming phenomena were found among conventional sources, biochar as a single source, and the mixture of coke and biochar. Biochar showed the most inferior foaming characteristics compared to the other studied carbon sources. Nevertheless, the slag foaming process was improved and showed slag foaming characteristics similar to results obtained using conventional carbon sources when the mixture of 50 wt.% coke and 50 wt.% biochar was used. The XRD analysis revealed a difference between the top and bottom of the slag foams. In almost all cases, a maghemite crystalline phase was detected at the top of the slag foams, indicating oxidation; metallic iron was found at the bottom. Furthermore, a difference in the slag foam (mixture of coke and biochar) was found in the presence of such crystalline phases as magnesium iron oxide (Fe₂MgO₄) and magnetite (Mg₀.₄Fe₂.₉₆O₄). Notwithstanding the carbon source applied, a layer between the foam slag and the crucible wall was found in many samples. Based on the SEM/EDS and XRD results, it was assumed this layer consists of gehlenite (Ca₂(Al(AlSi)O₇) and two spinels: magnesium aluminate (MgAl₂O₄) and magnesium iron oxide (Fe₂MgO₄). Full article

The paper uses a hydraulic performance analysis method to support the design of stock production multistage pumps. The method relies on a hybrid numerical–experimental approach conceived as a trade-off between accuracy and cost. It is based on CFD analyses incorporating experimental data of leakage flows across the sealing elements to obtain accurate predictions without the need of inclusion in the CFD model of small-scale features, which strongly increase the model complexity and computational effort. The aim of the paper is to present and validate this method. To this end, a 6-stage vertical pump manufactured by the stainless-steel metal-sheets-forming technique was considered as the benchmark. A series of experimental tests were performed to hydraulically characterize the impeller and return-channels-sealing elements by means of an “ad hoc” designed test rig. The characteristic curves of the sealing elements were embedded on the CFD model implemented in accordance with the strategy proposed in a previous authors’ work to obtain satisfactory predictions of multistage pumps’ hydraulic performance with minimum computational effort with the analytical correction of single-stage single-channel computations to account for the interaction between adjacent stages. To further explore the capabilities of the hybrid model, axial thrust measurements were performed by means of another “ad hoc” designed experimental apparatus. The application of the method to the benchmark pump shows that the hybrid model predicts the static head and efficiency with an error value lower than 1% at its best efficiency operation, and estimates the axial thrust with a 5% average error in the operating range from approximately 70% to 120% of the best efficiency duty. Full article

The increasing environmental awareness paired with the rise of global warming effects has led, in the past few years, to an increase in the sales of electric vehicles (EVs), partly but not only, caused by governmental incentives. A significant roadblock in the mass transition to EVs can be found in the so-called range anxiety: not only do EVs have, generally, considerably shorter ranges than their internal combustion engine vehicle (ICEV) equivalents, but recharge takes significantly longer than does filling up a gas tank, and charging stations are less widespread than are petrol stations. To counteract this, EV manufacturers are developing route planners which select the best route to go from A to B according to the range of the vehicle and the availability of charging stations. These tools are indeed powerful but do not account for the state of health (SoH) of the battery or for temperature conditions, two factors which may severely degrade the range of an EV. This article presents an innovative route planning method which takes into account SoH, temperature and driving style and selects, along the planned route, the charging stations among those which can be reached with the energy of the battery. To verify its proper operativity, simulations were conducted, highlighting the risk of running out of battery before destination, considering if the route is planned based on the declared range, and taking into account battery SoH, external temperature and driving style. Full article

Several previous experiments showed that the leapfrog–hopscotch and the adapted Dufort–Frankel methods are the most efficient among the explicit and stable numerical methods to solve heat transfer problems in building walls. In this paper, we extensively measure the running times of the most successful methods and compare them to the performance of other available solvers, for example, ANSYS transient thermal analysis and the built-in routines of MATLAB, where three different mesh resolutions are used. We show that the running time of our methods changes linearly with mesh size, unlike in the case of other methods. After that, we make a long-term simulation (one full winter month) of two-dimensional space systems to test the two best versions of the methods. The real-life engineering problem we solve is the examination of thermal bridges with different shapes in buildings to increase energy efficiency. Full article

Maintenance of urban green infrastructure generates a large amount of biomass that can be considered a valuable feedstock for biogas production. This study aims to determine the effect of the cutting time and method of substrate preservation on the specific methane yield (SMY) of urban grass collected from road verges and median strips between roadways in wet (WF) and dry fermentation (DF) technology. The grass was collected three times in a growing season, including in spring, summer, and autumn. The biochemical methane potential (BMP) test was performed on fresh grass, grass ensiled without additives, and grass ensiled with microbiological additives. In addition, the energy potentially produced from biogas and the avoided CO₂ emissions were calculated. The highest SMY (274.18 ± 22.59 NL kg_VS⁻¹) was observed for the fresh grass collected in spring and subjected to WF. At the same time, the lowest CH₄ production (182.63 ± 0.48 NL kg_VS⁻¹) was found in the grass ensiled without additives, collected in summer, and digested in DF technology. A comparison of the SMY obtained from the same grass samples in the WF and DF technologies revealed that higher CH₄ yields were produced in WF. The electricity and heat production were affected by the time of grass cutting, ensilage method, and AD technology. Generally, less electricity but more heat was produced in DF technology. The least electricity (469–548 kWh t_DM⁻¹) was produced from the grass cut in spring and subjected to DF, while the most electricity (621–698 kWh t_DM⁻¹) was obtained from the grass collected in autumn and subjected to WF. In the case of heat production, the situation was reversed. The least heat (1.4–1.9 GJ t_DM⁻¹) was produced by the grass collected in spring and subjected to WF, while the most heat (2.2–2.7 GJ t_DM⁻¹) was produced by the grass collected in autumn and subjected to DF. Ensilage decreased the electricity and heat production in almost all the cuttings. The total reduction in CO₂ emissions may amount to 2400 kg CO₂ per 1 hectare of road verges. This significant reduction demonstrates that the use of grass from roadside verges in biogas plants should be considered a feasible option. Even though urban grass should be considered a co-substrate only, it can be a valuable feedstock that may partially substitute energy crops and reduce the area needed for energy purposes. Our results reveal that biogas production from the grass waste in WF technology is a stable process. The cutting time and preservation method do not affect the AD process. In DF technology, fresh grass, especially from the late growing season used as feedstock, extends the time of biomass decomposition and, therefore, should be avoided in a real-life biogas plant. Full article

Even though eco-efficiency (EE) is already applied to various energy systems, so far, no study investigates in detail the hourly, marginal and seasonal impacts of a decentralized energy system. This study assesses the hourly EE of the Research Park Zellik (RPZ), located in the Brussels metropolitan area for 2022 composed of photovoltaic installations, wind turbines and batteries. A cradle-to-grave life cycle assessment (LCA) to identify the carbon footprint (CF) and a levelized cost of electricity (LCOE) calculation is conducted. An existing design optimization framework is applied to the RPZ. Consumption data are obtained from smart meters of five consumers at the RPZ on a one-hour time resolution for 2022 and upscaled based on the annual consumption of the RPZ. As the EE is presented as the sum of the CF and the LCOE, a lower EE corresponds to an economically and environmentally preferable energy system. In a comparative framework, the developed method is applied to two different case studies, namely, (i) to an energy system in Vega de Valcerce in Spain and (ii) to an energy system in Bèli Bartoka in Poland. The average EE of the RPZ energy system in 2022 is 0.15 per kWh, while the average EE of the Polish and Spanish energy systems are 1.48 and 0.36 per kWh, respectively. When analyzing four selected weeks, both the LCOE and CF of the RPZ energy system are driven by the consumption of the Belgian electricity grid mix. In contrast, due to the very low LCOE and CF of the renewable energy sources, in particular wind turbines, the RPZ energy system’s EE benefits and lies below the EE of the Belgium electricity grid mix. Full article

Network virtualization is a technology proven to be a key enabling a family of strategies in different targets, such as energy efficiency, economic revenue, network usage, adaptability or failure protection. Network virtualization allows us to adapt the needs of a network to new circumstances, resulting in greater flexibility. The allocation decisions of the demands onto the physical network resources impact the costs and the benefits. Therefore it is one of the major current problems, called virtual network embedding (VNE). Many algorithms have been proposed recently in the literature to solve the VNE problem for different targets. Due to the current successful rise of artificial intelligence, it has been widely used recently to solve technological problems. In this context, this paper investigates the requirements and analyses the use of the Q-learning algorithm for energy-efficient VNE. The results achieved validate the strategy and show clear improvements in terms of cost/revenue and energy savings, compared to traditional algorithms. Full article

To limit climate change, decarbonization of the transportation sector is necessary. The change from conventional combustion vehicles to vehicles with electric drives is already taking place. In the long term, it can be assumed that a large proportion of passenger cars will be battery–electric. On the one hand, this conversion will result in higher energy and power requirements for the electricity network; on the other hand, it also offers the potential for vehicles to provide energy for various systems in the future. Battery–electric vehicles can be used to shift grid purchases, optimize the operation of other components and increase the self-consumption rate of photovoltaic systems. An LP model for the optimal energy management of the neighborhood consisting of buildings with electricity and heat demand, a PV system, a BEV fleet, a heat pump and thermal storage was formulated. The potential of the BEV fleet to provide energy via V2B in the neighborhood was investigated, considering electricity tariff models and individual charging/discharging efficiencies of vehicles and stochastic mobility profiles. The vehicle fleet provides between $4.8$$\mathrm{kWh}$⁻¹$\mathrm{sqm}$⁻¹$\mathrm{a}$ (flat-fee) and $25.3$$\mathrm{kWh}$⁻¹$\mathrm{sqm}$⁻¹$\mathrm{a}$ (dynamic tariff) per year, corresponding to 6.7, 9.5% and 35.7% of the annual energy demand of the neighborhood. All tariff models lead to optimization of self-consumption in summer. Dynamic pricing also leads to arbitrage during winter, and a power price tariff avoids peaks in grid draw. Due to individual charging efficiencies, the power supplied by the fleet is distributed unevenly among the vehicles, and setting limits for additional equivalent full cycles distributes the energy more evenly across the fleet. The limits affect the V2B potential, especially below the limits of 20 yearly cycles for flat and power tariffs and below 80 cycles for a dynamic tariff. Full article

Along the roadmap to a Sustainable Real Estate-Scape, energy retrofit campaigns on wide city compartments represent a pivotal task, where the importance of the collaboration between the public and private sectors is crucial. Energy retrofit programs on building assets are subject to multiple uncertainty factors (e.g., climate, energy-economy forecasts, etc.) that act as a primary barrier to investment in this field. This paper aims to discuss risk management techniques to understand better how to deal with this kind of uncertainty. The research specifically addresses the techniques of sensitivity analysis and Monte Carlo simulation, focusing first on the phase of variables selection and their probability definition, including climatic, environmental, energy, economic, financial, and stochastic parameters. In this article, it is suggested to include correlation coefficients in the input variables of risk analysis, preferring the two-dimension Monte Carlo simulation to its simple version, since the results are more reliable when separating aleatory from epistemic uncertainty; thus, the results are more reliable. Moreover, it is seen how a sensitivity analysis based on percentile variations of the inputs provides a more accurate representation of risk if compared to the most common sensitivity analysis based on percentage deviations of the inputs. Conducting a sensitivity analysis using percentile variations gives realistic and reliable results, reflecting the tailored definition of uncertainty around the inputs on the basis of specific market analyses or historical series. Full article

Power generation from Renewable Energy Sources (RESs) is unpredictable due to climate or weather changes. Therefore, more control strategies are required to maintain the proper power supply in the entire microgrid. This paper presents a simulation scheme utilizing a solar system instanced by Photovoltaic (PV) panels coupled to the grid, loads, and an energy storage device. At first, modeling the PV panels cell and their operation were analyzed. The synthesis of the adaptive notch filter was designed to compensate for the input currents. The power converter’s/inverter’s efficiency and control facility allowed us to link the energy storage system with an electrical grid. Several simulations were accomplished consistently with nonlinear control techniques for the simple inverter, multi-variable filter, notch filter, and without a filter. Finally, the performances of the nonlinear controller with various filters were carried out to regulate the DC bus of the proposed grid. The advantage of these controllers is compensating the reactive power and harmonic currents to obtain a disturbance-free power network. The overall installations and simulations were established using the Matlab/Simulink software. Full article

Energy shortage has always been a problem that the world needs to face. The combined cooling, heating, and power (CCHP) system, as a multi-level energy utilization system that can provide cooling, heating, and electric energy simultaneously, is considered to have good development prospects in alleviating energy problems. In addition, because of the rapid development of electric vehicles (EVs), using EVs as power supply devices has become a hot topic of research. In this paper, EVs are combined with the CCHP system as new power supply equipment, and the influence of the season on the user’s cooling, heating, and power demand is considered. Aiming at the minimum economic cost, the system is optimized by using the PSO algorithm in two operating modes: following electricity load (FEL) and following thermal load (FTL). The final results show that the participation of EVs can reduce costs in both operating modes, especially in FTL mode, which can reduce costs by 4.58%, 13.61%, 12.74%, and 3.57% in spring, summer, autumn, and winter, respectively. In addition, the FEL mode is more economical in spring and winter, and the FTL mode is more economical in summer and winter. In addition, the $C{O}_2$ emissions in FEL mode are always less than in FTL mode. Full article

This article focuses on determining the optimum structure for a hybrid generation and storage system designed to power a single-family housing estate, taking into account the different number of electric vehicles in use and an assumed level of self-consumption of the generated energy. In terms of generation, two generation sections—wind and solar—and a lithium-ion container storage system will be taken into account. With regards to energy consumption, household load curves, determined on the basis of the tariff for residential consumers and modified by a random disturbance, will be taken into account, as well as the processes for charging electric cars with AC chargers, with power outputs ranging between 3.6 and 22 kW. Analyses were carried out for three locations in Poland—the Baltic Sea coast (good wind conditions), the Lublin Uplands (the best insolation in Poland) and the Carpathian foothills (poor wind and insolation conditions). The mathematical and numerical model of the system and the MOPSO (multiobjective particle swarm optimisation) algorithm were implemented in the Matlab environment. The results include Pareto fronts (three optimisation criteria: minimisation of energy storage capacity, minimisation of energy exchanged with the power grid and maximisation of the self-consumption rate) for the indicated locations and three electromobility development scenarios with determined NPVs (net present values) for a 20-year lifetime. The detailed results relate to the inclusion of an additional expert criterion in the form of a coupled payback period of no more than 10 years, a maximum NPV in the last year of operation and a self-consumption rate of at least 80%. The economic calculations take into account the decrease in PV installation capacity as a function of the year of operation, as well as changes in electricity and petrol prices and variations in energy prices at purchase and sale. Full article

Quality, reliability, and durability are the key features of photovoltaic (PV) solar system design, production, and operation. They are considered when manufacturing every cell and designing the entire system. Achieving these key features ensures that the PV solar system performs satisfactorily and offers years of trouble-free operation, even in adverse conditions. In each cell, the quality of the raw material should meet the quality standards. The fulfillment of the quality management system requires every part that goes into the PV solar system to undergo extensive testing in laboratories and environments to ensure it meets expectations. Hence, every MWh of electricity generated by the PV solar system is counted, the losses should be examined, and the PV system’s returns should be maximized. There are many types of losses in the PV solar system; these losses are identified and quantified based on knowledge and experience. They can be classified into two major blocks: optical and electrical losses. The optical losses include, but are not limited to, partial shading losses, far shading losses, near shading losses, incident angle modifier (IAM) losses, soiling losses, potential induced degradation (PID) losses, temperature losses, light-induced degradation (LID) losses, PV yearly degradation losses, array mismatch losses, and module quality losses. In addition, there are cable losses inside the PV solar power system, inverter losses, transformer losses, and transmission line losses. Thus, this work reviews the losses in the PV solar system in general and the 103 MWp grid-tied Al Quweira PV power plant/Aqaba, mainly using PVsyst software. The annual performance ratio (PR) is $79.5\%$, and the efficiency $\left(\eta \right)$ under standard test conditions (STC) is $16.49\%$. The normalized production is 4.64 kWh/kWp/day, the array loss is 1.69 kWh/kWp/day, and the system loss is 0.18 kWh/kWp/day. Understanding factors that impact the PV system production losses is the key to obtaining an accurate production estimation. It enhances the annual energy and yield generated from the power plant. This review benefits investors, energy professionals, manufacturers, installers, and project developers by allowing them to maximize energy generation from PV solar systems and increase the number of solar irradiation incidents on PV modules. Full article

The demand for a reliable, cheap and environmentally friendly source of energy makes the integration of renewable energy into power networks a global challenge. Furthermore, reliability, as one of the core elements of efficient and cost-effective energy management options, is still among the dominant factors/techniques that receive more attention for realistic penetrations of renewable energy into the electricity grid. This paper proposes an efficient way of energy management for a grid-connected microgrid. The grid-connected microgrid used in the analysis consists of solar photovoltaic (P.V.) and battery. In this microgrid configuration, oftentimes, the output power might not be equal to the system demand; in this regard, it is expected that the mismatch between these output powers is not zero. However, to reduce the mismatch between demand and supply to be close to zero, this paper proposes strategies of increasing the rated power of solar, battery and grid separately and combining them with a view of finding the cheapest option among these strategies. The results have shown that the cost increment for different options is USD 280.792, 84.48 and 48.204 for storage, P.V. and grid, respectively. These have shown that the storage option is the most expansive option for improving P.V. grid-connected microgrids. This is followed immediately by the P.V. option, which is weather dependent. On the other hand, the grid option is the cheapest option for system reliability improvement. This paper is expected to be useful to both new researchers and experts who are working in energy management with an emphasis on the reliability aspect. Full article

The transition towards climate neutrality will result in an increase in electrical vehicles, as well as other electric loads, leading to higher loads on electrical distribution grids. This paper presents an optimisation algorithm that enables the integration of more loads into distribution grid infrastructure using information from smart meters and/or smart meter gateways. To achieve this, a mathematical programming formulation was developed and implemented. The algorithm determines the optimal charging schedule for all electric vehicles connected to the distribution grid, taking into account various criteria to avoid violating physical grid limitations and ensuring non-discriminatory charging of all electric vehicles on the grid while also optimising grid operation. Additionally, the expandability of the infrastructure and fail-safe operation are considered through the decentralisation of all components. Various scenarios are modelled and evaluated in a simulation environment. The results demonstrate that the developed optimisation algorithm allows for higher transformer loads compared to a P(U) control approach, without causing grid overload as observed in scenarios without optimisation or P(U) control. Full article

The main objective of this paper is to propose two innovative monitoring methods for electrical disturbances in low-voltage networks. The two approaches present a focus on the classification of voltage signals in the frequency domain using machine learning techniques. The first technique proposed here uses the Fourier transform (FT) of the voltage waveform and classifies the corresponding complex coefficients through a multilayered neural network with multivalued neurons (MLMVN). In this case, the classifier structure has three layers and a small number of neurons in the hidden layer. This allows complex-valued inputs to be processed without the need for pre-coding, thus reducing computational cost and keeping training time short. The second technique involves the use of the short-time Fourier transform (STFT) and a convolutional neural network (CNN) with 2D convolutions in each layer for feature extraction and dimensionality reduction. The voltage waveform perturbations taken into consideration are: voltage sag, voltage swell, harmonic pollution, voltage notch, and interruption. The comparison between the two proposed techniques is developed in two phases: initially, the simulated data used during the training phase are considered and, subsequently, various experimental measurements are processed, obtained both through an artificial disturbance generator and through a variable load. The two techniques represent an innovative approach to this problem and guarantee excellent classification results. Full article

The ERTMS/ETCS is the newest automatic train protection system. This is a system that supports the driver in driving the train. It is currently being implemented throughout the European Union. This system’s latest specifications also provide additional functions to increase the energy efficiency of train driving in the form of ATO (automatic train operation). These functions of the ETCS will be valuable, provided they operate without failure. To achieve errorless configuration of the ETCS, a methodology for automatic system verification using the IMDS (Integrated Model of Distributed Systems) formalism and the temporal tool Dedan was applied. The main contribution is asynchronous and timed verification, which appropriately models the distributed nature of the ETCS and allows the designer not only to analyze time dependencies but also to define the range of train velocities in which the operational scenario is valid. Additionally, the novelties of the presented verification methodology are the graphical design of the system components and automated verification freeing the designer from using textual design. We express the verified properties as observer automata rather than in temporal logic. Moreover, we check partial properties related to system fragments, which is crucial in distributed systems. This paper presents the verification of an example ETCS system application. The verification results are presented as sequence diagrams leading to a correct/incorrect final state. Full article

Community energy projects have gained popularity in recent years, and encouraging citizens to form local energy communities (LEC) is considered an effective tool for raising awareness about renewable energy. Since no single universal method exists for operating LECs, this study investigated the impact that different business models and asset dispatch methods have on LECs’ economic and energy-related indicators. We carried out a case study, which included the development, modelling, and simulation of seven scenarios using mixed-integer linear programming (MILP). To measure and compare the prospective performance of the LECs in each scenario, six key metrics were evaluated and assessed. The authors find that simple, rule-based control systems might be well suited for LECs with a limited number of controllable assets that aim to provide increased levels of self-consumption of up to 3%. We also conclude that when the LEC utilises an energy cooperative business model, the selected asset dispatch method provides only minor differences in LEC performance, while for prosumer communities, the importance of selecting a suitable asset dispatch method is higher. We also conclude that LECs have the potential to significantly increase their economic performance by more than 10% by acting as aggregators and providing grid services directly to system operators. Full article

Operation modes of rolling stock at mining enterprises are considered and analyzed. The justification of the need to replace it with a modern specialized electric locomotive for quarry railway transport, equipped with an asynchronous traction electric drive and an on-board energy storage system, is presented. The determination of the parameters and structure of the on-board energy storage system, based on the condition of power compensation with limited power consumption from the traction network and ensuring the autonomous movement of the electric locomotive, is considered. This study was carried out by modeling the processes of energy exchange in the traction system of an electric locomotive. The use of lithium cells and supercapacitors in energy storage is considered. Variants of the hybridization of energy storage were studied from the standpoint of minimizing the weight, size, and cost indicators. It was established that reducing the mass of the energy storage device, which includes lithium cells and supercapacitors, leads to an increase in the cost of one kilowatt-hour of energy storage capacity, which reduces the attractiveness of capital expenditures for the creation of such an energy storage device. Hybridization of the energy storage device by combining lithium cells of different types practically does not improve its weight, size, and cost indicators. The recommended option is a storage capacity of energy based on LTO elements, for which it is necessary to select elements in order to minimize weight, size, and cost indicators. Full article

Self-consumption of the energy generated by photovoltaics (PV) is playing an increasingly important role in the power grid. “Prosumer” systems consume part of the produced energy directly to meet the local demand, which reduces the feed-in into as well as the demand from the grid. In order to analyse the effects of PV self-consumption in the power grid, we introduce a stochastic bottom-up model of PV power generation and local consumption in the control area of the German transmission system operator TransnetBW. We set up a realistic portfolio of more than 100,000 PV/prosumer systems to generate representative time series of PV generation and consumption as a basis to derive self-consumption and feed-in. This model allows for the investigation of the time-dependent behaviour in detail for the full portfolio whereas measurements are presently only available as aggregated feed-in time series over a nonrepresentative subset of systems. We analyse the variation of self-consumption with PV generation and consumption at the portfolio level and its seasonal, weekly and diurnal cycles. Furthermore, we study a scenario of 100% prosumers as a limiting case for a situation without subsidized feed-in tariffs and local energy storage. Full article

A reliable power grid system based on renewable energy sources is a crucial step to restrict the climate crisis. Stationary battery energy storage systems (BESS) offer a great potential to repel power fluctuations in the grid at different timescales. However, for a reliable operation and cost estimation, the degradation in the batteries needs to be understood. We present an accelerated battery degradation study, on single as well as multi-service applications, of NCM532/Gr lithium-ion battery cells. Frequency regulation (FR) was the least harmful for the battery, with an expected lifetime of 12 years, while peak shaving (PS) resulted in an expected lifetime of 8 years. The combined cycle (FRPS) accelerated the capacity loss, and degradation of the positive electrode was induced from the start of cycling, causing power limitations after only 870 equivalent full cycles (EFC). Tracking the 1C-rate discharge capacity was proven to be a good indication of the accelerated cell polarization, and it can serve as a useful method to evaluate the internal battery state of health (SOH). Full article

In this study, biomass–specific gasification data is experimentally collected for numerical simulations of fixed–bed reactors. Since biomass properties vary, it is crucial to have characteristic biomass data. Extensive data is collected to determine an appropriate description of specific biomass behavior, including basic data (e.g., heating value, size, densities, ultimate and total analysis etc.), biomass pyrolysis and heterogeneous gasification reaction data. Heterogeneous reactions were comparatively investigated in the forms of powder, particles, and a fixed–bed. The powder was investigated in depth with CO₂, O₂, and H₂O (gas fraction 5–20 vol.%; temperature CO₂, O₂ and H₂O, respectively, at 730–790 °C, 360–405 °C, 720–780 °C), while particle reactions and fixed–bed reaction were only studied with CO₂. A model description for a fixed–bed batch reactor was applied, modified, and compared to experimental fixed–bed batch reactor results. This study concludes that determining the appropriate characteristic particle size and parameters for the porous structure of specific biomass char is essential for simulation based on preliminary biomass characterization. Therefore, in future investigations, the description for biomass-specific differences between powder, single particles, and bulk of biomass char may be of greater focus, also taking into consideration O₂ and H₂O. Full article

In electrical grids with a high renewable percentage, weather conditions have a greater impact on power generation. This can lead to the overproduction of electricity during periods of substantial wind power generation, resulting in shutoffs of wind turbines. To reduce such shutoffs and to bridge periods of lower electricity production, three thermal energy storage systems (TESs) have been developed for space heating and domestic hot water. These include a water-based thermal system (WBTS), a thermally activated building system (TABS), and a high-temperature stone storage system (HTSS). The paper explains the development of computer models used to simulate the systems and their successful verification using field measurements. Target values to cover about 90% of building heating demand with excess electricity were found to be achievable, with performance ratios depending on storage size, particularly for WBTS and HTSS. The TABS’ storage capacity is limited by building geometry and the available inner ceilings and walls. Full article

Employment of a battery energy storage system to compensate for the generation-consumption mismatch is a vital element for a resilient microgrid. However, the frequent (i.e., short-term) cyclic activity and the abrupt current variations (i.e., high di/dt) have adverse effects on the energy-type battery’s lifespan. On the other hand, the power-type supercapacitor energy storage system (SCES) has almost zero lifetime degradation when it is subjected to irregular charging/discharging patterns. Therefore, the hybridization between them can reduce battery stress levels. This study proposes a droop control algorithm with multiple segments for a SCES/battery hybrid energy storage system (HESS) that is employed in a solar/wind DC microgrid. The presented control scheme is decentralized since it avoids the central controller (CC) and the communication links between the controllers of SCES and battery units. To eliminate the short-term cyclic operation of the battery, the SCES regulates the bus voltage inside a narrow zone with a droop curve that exploits all its available energy capacity. Inside this zone, the battery is kept inactive. As soon as the bus voltage deviates from this band, the SCES enters the idle mode, and the battery is triggered following a droop curve different for charging or discharging mode to stabilize the bus voltage. To evaluate the effectiveness of the proposed system over a battery-only system and a hybrid SCES/battery system controlled with the classical droop method, a comparative analysis under different scenarios is presented. Full article

Over the three-day gasification test of a large coal block with oxygen in atmospheric pressure conditions, the yield and composition of the tar collected was investigated. The tar was sampled approximately every 7 h into sorption tubes directly from the reactor outlet. Sand, with a moisture content of 11%, was used as an insulating material to simulate the environment of the gasified coal seam. Light aromatic hydrocarbons (BTEX), phenols, and polycyclic aromatic hydrocarbons (PAHs) were determined in the tar. The results that were obtained were recalculated into the concentrations of the individual components of the tar and its mass stream in the process gas. The residence time of the tar in the reactor, its molar mass, and the H/C ratio were also calculated. As the reaction progressed, the water that was contained in the wet sand started to react with the gasified coal, which significantly affected the composition and amount of the obtained process gas and the produced tar. Due to an increase in the amount of generated gases and steam, the residence time of the tar vapours in the reactor decreased as the gasification progressed, ranging from approximately 1 s at the beginning of the process to 0.35 s at the end. The obtained tar was characterised by a high average content of BTEX fractions at approximately 82.6%, PAHs at 14.7%, and phenols at 2.7%. Benzene was the dominant BTEX compound, with a concentration of 83.7%. The high content of the BTEX compounds, especially benzene, was a result of secondary processes taking place in the tar (hydrocracking and steam reforming), and as a result of which, in the presence of hydrogen and steam, the heavier components of the tar were transformed into lighter ones. The total yield of the tar from this UCG (underground coal gasification) process—calculated per 1 ton of gasified coal—was 1.8% (counted on the basis of the analysed tar composition). Comparing this result to the efficiency of the classic coking process, the tar yield was about three times lower. Full article

Microbial fuel cell (MFC) technology is anticipated to be a practical alternative to the activated sludge technique for treating domestic and industrial effluents. The relevant literature mainly focuses on developing the systems and materials for maximum power output, whereas understanding the fundamental electrochemical characteristics is inadequate. This experimental study uses a double-chamber MFC having graphite electrodes and an anion-exchange membrane to investigate the electrochemical process limitations and the potential of bioelectricity generation and dairy effluent treatment. The results revealed an 81% reduction in the chemical oxygen demand (COD) in 10 days of cell operation, with an initial COD loading of 4520 mg/L. The third day recorded the highest open circuit voltage of 396 mV, and the maximum power density of 36.39 mW/m² was achieved at a current density of 0.30 A/m². The electrochemical impedance spectroscopy analysis disclosed that the activation polarization of the aerated cathode was the primary factor causing the cell’s resistance, followed by the ohmic and anodic activation overpotentials. Full article

Internal combustion engines face increased market, societal, and governmental pressures to improve performance, requiring researchers to utilize modeling tools capable of a thorough analysis of engine performance. Heat release is a critical aspect of internal combustion engine diagnostic analysis, but is prone to variability in modeling validity, particularly as engine operation is pushed further from conventional combustion regimes. To that end, this effort presents a comprehensive open-source, zero-dimensional equilibrium heat release model. This heat release analysis is based on a combined mass, energy, entropy, and exergy formulation that improves upon well-established efforts constructed around the ratio of specific heats. Furthermore, it incorporates combustion using an established chemical kinetics mechanism to endeavor to predict the global chemical species in the cylinder. Future efforts can augment and improve the chemical kinetics reactions for specific combustion conditions based on the radical pyrolysis of the fuel. In addition, the incorporation of theoretical calculations of energy and exergy based on the change in chemical species allows for cross-checking of combustion model validity. Full article

The description of the functionality of a smart grid’s architectural concept, analyzing different Smart Grid (SG) scenarios without disrupting the smooth operation of the individual processes, is a major challenge. The field of smart energy grids has been increasing in complexity since there are many stakeholder entities with diverse roles. Electric Vehicles (EVs) can transform the stress on the energy grid into an opportunity to act as a flexible asset. Smart charging through an external control system can have benefits for the energy sector, both in grid management and environmental terms. A suitable model for analyzing and visualizing smart grid use cases in a technology-neutral manner is required. This paper presents a flexible architecture for the potential implementation of electromobility as a distributed storage asset for the grid’s capacity optimization by applying the Use Case and Smart Grid Architecture Model (SGAM) methodologies. The use case scenario of booking a charge session through a mobile application, as part of the TwinERGY Horizon 2020 project, is deployed to structure the SGAM framework layers and investigate the applicability of the SGAM framework in the integration of electromobility as a distributed storage asset into electricity grids with the objective of enhanced flexibility and decarbonization. Full article

Given the fundamental role of renewable energy assets in achieving global temperature control targets, new energy management methods are required to efficiently match intermittent renewable generation and demand. Based on analysing various designed cases, this paper explores a number of heuristics for a smart battery scheduling algorithm that efficiently matches available power supply and demand. The core of improvement of the proposed smart battery scheduling algorithm is exploiting future knowledge, which can be realized by current state-of-the-art forecasting techniques, to effectively store and trade energy. The performance of the developed heuristic battery scheduling algorithm using forecast data of demands, generation, and energy prices is compared to a heuristic baseline algorithm, where decisions are made solely on the current state of the battery, demand, and generation. The battery scheduling algorithms are tested using real data from two large-scale smart energy trials in the UK, in addition to various types and levels of simulated uncertainty in forecasts. The results show that when using a battery to store generated energy, on average, the newly proposed algorithm outperforms the baseline algorithm, obtaining up to 20–60% more profit for the prosumer from their energy assets, in cases where the battery is optimally sized and high-quality forecasts are available. Crucially, the proposed algorithm generates greater profit than the baseline method even with large uncertainty on the forecast, showing the robustness of the proposed solution. On average, only 2–12% of profit is lost on generation and demand uncertainty compared to perfect forecasts. Furthermore, the performance of the proposed algorithm increases as the uncertainty decreases, showing great promise for the algorithm as the quality of forecasting keeps improving. Full article

Stochastic power generation is the new reality in power system management. Voltage Control mechanisms based on physical assets of the power system are deemed inadequate and are not guaranteed to lead the energy transformation in a way that ensures system security as well as cost-effective operation. Many countries that recently attained deregulated Balancing Market environments are in need of regulatory provisions and rigorous extension of electricity market mechanisms. On 1 November 2020, the Greek Electricity Market commenced operations conforming to the European Target Model. Apart from the innate difficulties a transformation such as this contains, more challenges occur as Greece is bound by European law to design market-based incentive mechanisms to remunerate Ancillary Services provided to the power system. This paper aims to examine some of the technical and regulatory aspects linked with—future—Transmission System Operator (TSO) and Distribution System Operator (DSO) cooperation in overcoming local transmission system problems concerning Voltage regulation. The interaction between localized Voltage Control Market (VCM) and the Balancing Market, the incorporation and competition of Distributed Energy Resources (DER) and Transmission Energy Resources (TER) within the VCM along with the TSO - DSO procedures and products standardization are the focus points of the present research paper. Full article

This article explores the use of battery energy storage in a transactive energy approach for a heavily solar-penetrated community. We hypothesize that the efficient market interactions between independently acting, fully automated agents (some equipped with battery energy storage) can result in both bill savings and improvements in power flow, without explicitly optimizing for power flow ahead of time. A test setting of nine typical residential prosumers and one heavily loaded prosumer is used. The heavily loaded prosumer initially experiences multiple undervoltage violations, and a 13.5 kWh battery is installed to alleviate the problem. Two profile-shaping strategies are compared. The first scenario uses greedy control that maximizes self-sufficiency, while the second scenario uses a local market to enable energy trading between participants and a rule-based trading and management agent for control. The results show that the first scenario made minimal improvements to power flow, but the second scenario eliminated all occurrences of under-voltage violations. Furthermore, the total amount of energy from the grid is reduced by 24.3%, and the amount of energy injected into the grid is reduced by 39.2%. This results in lower bills for every participant and a bill reduction of 16.7% for the community as a whole. Full article

Fiscal policy is an essential tool that policymakers use for guiding the economy. Thus, the effects of fiscal policy may affect many aspects of our lives, including the impact of carbon dioxide (CO₂) emissions. This article investigates the role of fiscal policy, in addition to gross domestic product (GDP), innovation, and financial development, in mitigating CO₂ emissions in the context of the Environmental Kuznets Curve theory in the Group of Twenty (G20) countries from 1995 to 2019. The study implied the autoregressive distributed lag of pooled mean group (ARDL-PMG) approach to analyze the suggested model. The results revealed the validity of the model for the G20 countries, as well as a long-run cointegration between the study variables. The results also showed that fiscal policy is associated positively with CO₂ emissions. Hence, we recommend reconsidering the applied financial policy, redirecting it to support clean energy projects, provide incentives for projects combating environmental degradation, and relying on environmentally friendly energy. Full article

For the offshore wind turbines (OWTs) located in a seismically active region, the occurrence of earthquakes combined with scour is a highly possible multi-hazard event. This study developed an alternative fragility analysis framework to assess the seismic performance of suction bucket-supported OWTs under the action of scour. First, the probabilistic approach was applied to calculate the occurrence probability of scour depth (SD) and earthquake events. Then, the possible combinations of these two events were considered in the analysis model to establish the fragility surface of the suction bucket foundation. Finally, by integrating the product of scour and earthquake hazard, as well as fragility curves, the suction bucket foundation failure probability was obtained. The developed framework provides a reliable approach to risk assessment for OWT-supporting structures in extreme event situations and can be applied to other complex natural hazards. Full article

The development of a country’s economy is directly related to the use of energy in that country’s economic sectors. Therefore, the energy–environmental Kuznets curve (EEKC) is often used when analysing a country’s potential and challenges in sustainable development, green economy, and green growth. This hypothesis tests whether there is an inverse “U”-shaped relationship between energy use and economic growth and is especially important when analysing developing countries to assess if, at a certain point, energy use begins to drop, resulting in fewer greenhouse gas emissions, environmental degradation, and the consumption of fossil-based fuels. This study aims to examine the relationship between energy consumption and economic growth in the Baltic States from 1995 to 2019, with a focus on the agriculture sector. The study uses the non-linear autoregressive distributed lag (NARDL) model for individual and panel time series. Total energy use, as well as electricity use, is included in the study, whereas gross value added is employed as a measure of economic growth. Research data analysis reveals that energy use in all three Baltic countries stabilises as gross value added increases. However, there is insufficient evidence to show that after a certain point, energy use begins to drop; thus, the hypothesis for the inverse “U”-shaped energy–environmental Kuznets curve (EEKC) is rejected. Research results have important practical implications regarding countries’ policies toward energy, including the use of electricity and sustainable development. Full article

Artificial intelligence (AI) techniques are increasingly used to address problems in electricity systems that result from the growing supply of energy from dynamic renewable sources. Researchers have started experimenting with data-driven AI technologies to, amongst other uses, forecast energy usage, optimize cost-efficiency, monitor system health, and manage network congestion. These technologies are said to, on the one hand, empower consumers, increase transparency in pricing, and help maintain the affordability of electricity in the energy transition, while, on the other hand, they may decrease transparency, infringe on privacy, or lead to discrimination, to name a few concerns. One key concern is how AI will affect energy justice. Energy justice is a concept that has emerged predominantly in social science research to highlight that energy related decisions—in particular, as part of the energy transition—should produce just outcomes. The concept has been around for more than a decade, but research that investigates energy (in)justice in the context of digitalized and data-driven electricity systems is still rather scarce. In particular, there is a lack of scholarship focusing on the challenges and questions that arise from the use of AI technologies in the management of electricity systems. The central question of this paper is, therefore: what may be the implications of the use of AI in smart electricity systems from the perspective of energy justice, and what does this mean for the design and regulation of these technologies? Full article

Recently, fuel cell combined heat and power systems (FC-CGSs) for residential applications have received increasing attention. The International Electrotechnical Commission has issued a technical specification (TS 62282-9-101) for environmental impact assessment procedures of FC-CGSs based on the life cycle assessment, which considers global warming during the utilization stage and abiotic depletion during the manufacturing stage. In proton exchange membrane fuel cells (PEMFCs), platinum (Pt) used in the catalyst layer is a major contributor to abiotic depletion, and Pt loading affects power generation performance. In the present study, based on TS 62282-9-101, we evaluated the environmental impact of a 700 W scale PEMFC-CGS considering cathode catalyst degradation. Through Pt dissolution and Ostwald ripening modeling, the electrochemical surface area transition of the Pt catalyst was calculated. As a result of the 10-year evaluation, the daily power generation of the PEMFC-CGS decreased by 11% to 26%, and the annual global warming value increased by 5% due to the increased use of grid electricity. In addition, when Pt loading was varied between 0.2 mg/cm² and 0.4 mg/cm², the 10-year global warming values were reduced by 6.5% to 7.8% compared to the case without a FC-CGS. Full article

In this study, the technoeconomic feasibility of bioenergy production from sawdust under four different case scenarios is simulated and compared. These scenarios include: (1) heat and electricity generation from raw sawdust; (2) pellet production from sawdust; (3) and (4) integrated biorefinery approach for the simultaneous manufacturing of multiple products (steam-exploded and torrefied pellets) and co-products (furfural, hydroxy methyl furfural (HMF), acetic acid), along with heat and electricity generation. Economic assessments such as cost analysis, payback time (PBT), net present value (NPV) and internal rate of return (IRR) were determined for these scenarios. The results showed that the approach of producing torrefied pellets, furfural, and acetic acid, along with co-generated heat and electricity, in terms of multiproducts and profitability (NPV (at 7%): USD 38.29 M) was preferable over other alternatives. In terms of simplified technology and other economic indices (PBT: 2.49 year, IRR: 51.33%, and return on investment (ROI): 40.1%), the scenario for producing pellets from wood sawdust was more promising than others. If plant capacity was not a limiting factor, the optimal size for the combined heat and power (CHP) plant was between 250–300 kt for the main product. Additionally, untreated and treated pellet plants equipped with CHP had an optimal size of 150–200 kt of wood pellets per year. Full article

This study entailed a load evaluation for the tower design of a large floating offshore wind turbine system in accordance with the wave conditions. The target model includes the IEA 15 MW reference wind turbine and a semi-submersible VolturnUS-S reference floating offshore wind turbine platform from the University of Maine. The OpenFAST, which is an aero-hydro-servo-elastic fully coupled analysis tool, was used for load analysis. The DLC1.2 and 1.6 were used as the design load cases, and the environmental conditions suitable for the design load cases were cited in the VolturnUS-S platform report. Load evaluation was performed according to time series and FFT results. The findings of the study are as follows: first, in the correlation analysis, the tower-top deflection had the highest correlation, and this further affects nacelle acceleration. Second, the tower-base pitch moment increased with the significant wave height. However, the wave peak period increased until it matched the tower-top deflection frequency and decreased thereafter. Third, the comparison between the normal and severe sea state conditions revealed that the tower-base pitch moments for the two conditions are almost similar, despite the conditions wherein the wave spectral energy differs by a factor of 3.5. Fourth, the tower shape is changed while adjusting the diameter of the tower, and the tower-top and tower-base pitch moments are reviewed using a redesigned tower. Even if the mass is the same, adjusting the diameter of the tower reduces only the pitch moment. Full article

This paper presents work on a wave energy device with an on-board power take-off based on a magnetostrictively actuated deformable structure. Such devices potentially could be used in low-cost, short-term expeditionary operations. The paper discusses an analytical model that describes the heave oscillations of a buoy with two inclined, overhanging beams with magnetostrictive strips affixed to them. This work comprises the first steps toward an analytical model that would enable potential users to obtain quick power estimates at the planning stage. Here, the fully nonlinear magneto-mechanical-electrical constitutive relations are linearized about a desirable operating point, and a coupled dynamic model is derived using a variational formulation that includes buoy heave, flexural oscillations of the two beams, and the voltage response of the magnetostrictive strips. Energy conversion performance in wind-sea-dominated Pierson–Moskowitz spectra is found to be modest. However, present results also indicate that performance could be improved with suitable mechanical modifications. Full article

Tidal stream turbines may operate under yawed conditions due to variability in ocean current directions. Insight into the wake structure of yawed turbines can be essential to ensure efficient tidal stream energy extraction, especially for turbine arrays where wake interactions emerge. We studied experimentally the effects of turbines operating under varying yaw conditions. Two scenarios, including a single turbine and a set of two turbines in alignment, were configured and compared. The turbine thrust force results confirmed that an increasing yaw angle results in a decrease in the turbine streamwise force and an increase in the turbine spanwise force. The velocity distribution from the single turbine scenario showed that the wake deflection and velocity deficit recovery rate increased at a rate proportional to the yaw angle. The two-turbine scenario results indicated that the deployment of an upstream non-yawed turbine significantly limited the downstream wake steering (i.e., the wake area behind the downstream turbine). Interestingly, a yawed downstream turbine was seen to influence the steering of both the upstream and the downstream wakes. These systematically derived data could be regarded as useful references for the numerical modelling and optimisation of large arrays. Full article

The concept of local energy communities is receiving increasing attention. However, the question of how to distribute the benefit of a community among its members is still open. It is commonly desired that the benefit distribution is fair and stable. While benefit distribution schemes such as the nucleolus, Shapley value and Shapley-core are known to perform well in terms of fairness and stability, studies have shown that none of them can guarantee full fairness and stability at the same time. However, the existing studies neglect the temporal component. Hence, in order to gain more insights into the stability and fairness of the three aforementioned distributions in practice, we investigate their performance over time in simulation experiments on real-world data from Australian households. In about 90% of the cases, the Shapley value yielded a reasonably stable distribution, while the nucleolus yielded a reasonably fair distribution in about 75% of the cases. Furthermore, the experiments show an impact of the community size on the stability and fairness of the investigated distributions. One can conclude that for small communities, the Shapley value is the best choice, but that the nucleolus and Shapley–core become more and more attractive with increasing size of the community. Full article

The stochastic nature of renewable energy resources and consumption has the potential to threaten the balance between generation and consumption as well as to cause instability in power systems. The microgrid operators (MGOs) are financially responsible for compensating for the imbalance of power within their portfolio. The imbalance of power can be supplied by rescheduling flexible resources or participating in the balancing market. This paper presents a robust optimization (RO)-based model to maintain the balance of a portfolio according to uncertainties in renewable power generation and consumption. Furthermore, load reduction (LR) and battery energy storage (BES) are considered flexible resources of the MGO on the consumption side. The model is formulated based on the minimax decision rule that determines the minimum cost of balancing based on the worst-case realizations of uncertain parameters. Through the strong duality theory and big-M theory, the proposed minimax model is transformed into a single-level linear maximization problem. The proposed model is tested on a six-node microgrid test system. The main contributions of the proposed model are presenting a robust model for portfolio management of MGO and using BES and LR to improve the flexibility of microgrid. Simulation results demonstrate that using LR and BES could decrease the balancing cost. However, the optimal portfolio management to compensate for the imbalance of power is highly dependent on the risk preferences of MGO. Full article

This paper studies the stability impact of the alternate voltage controller’s (AVC) low-pass filter (LPF) in a wind turbine’s grid-connected voltage source converter (VSC). A small-signal model of the grid-connected converter is designed with a grid-following synchronization control. More specifically, the non-linear state-space model of the grid-connected converter was developed, including the dynamics of both the inner and outer control loops of the converter, the dynamics of the elements of the electrical system, as well as the digital time delay. An eigenvalue-based stability analysis gives insight into the stability impacts of the outer-loop controllers. It is proven that the cutoff frequency of the AVC’s LPF affects the phase-locked loop (PLL) and AVC bandwidths of instability, as well as the corresponding critical oscillation frequencies. This phenomenon is observed in both weak and strong grids. Consequently, the small-signal stability regions of the PLL and AVC bandwidth can be identified for the range of the AVC’s LPF cutoff frequency under study. The stability regions of the PLL and AVC, which are obtained from the small-signal model, as well as the determined critical oscillation frequencies, are validated through time domain simulations and fast-Fourier transformation (FFT) analysis. Full article

Firewood stoves are widespread and popular for renewable heat supply in Europe. Several new technological measures have been developed recently that aim at improving the appliance performance in terms of emissions and efficiency. In order to support the trend towards “(nearly) zero-emissions technologies”, the objective of this study was to provide a profound overview of the most relevant technical primary and secondary measures for emission reduction and to analyze their functionality, the relevant framework conditions for their application and their costs. Since user behavior is essential for emission and efficiency performance, the state of knowledge about user behavior is summarized and the latest measures for its optimization are evaluated as non-technical primary measures. Primary and secondary measures were analyzed separately, but also potentially promising combinations of primary and secondary optimization were evaluated using SWOT analysis. The results showed that complementary application of primary and secondary measures will be necessary in order to achieve “(nearly) zero-emission technologies”. The paper is useful for manufacturers and provides them with guidance and recommendations for future developments. They can specifically select appropriate measures for their products and applications not only based on technical aspects, but also with a strong focus on user behavior and user comfort. Full article

Solar heating and cooling (SHC) systems are currently attracting attention, especially in times of increasing energy prices and supply crises. In times of lower energy prices, absorption SHC systems were not competitive to compression cooling supported by photovoltaic (PV) modules due to the high investment costs and total energy efficiency. This paper aims to discuss the current changes in energy supply and energy prices in terms of the feasibility of the application of a small absorption SHC system in a mild Mediterranean climate. The existing hospital complex restaurant SHC system with evacuated tube solar collectors and a small single-stage absorption chiller was used as a reference system for extended analysis. Dynamic simulation models based on solar thermal collectors, PV modules, absorption chillers and air-to-water heat pumps were developed for reliable research and system comparison. The results showed that primary energy consumption in SHC systems designed to cover base energy load strongly depends on the additional energy source, e.g., boiler or heat pump. Absorption SHC systems can be price competitive to air-to-water heat pump (AWHP) systems with PV collectors only in the case of reduced investment costs and increased electricity price. To reach acceptable economic viability of the absorption SHC system, investment price should be at least equal to or lower than a comparable AWHP system. Full article

Many attempts are made worldwide to create cheap, efficient, and eco-friendly water desalination systems. Passive solar stills (SS) are considered to be such. This paper presents the results of the experimental and theoretical investigation of the effects of using phase-change materials (PCM) on the performance of SS. The experiments were conducted for two paraffin waxes, as PCM and 1.0, 2.5, and 5.0 kg of PCM were used. The results of the experimental studies were used to validate a mathematical model, which was based on the energy balance ordinary differential equations. The equations were solved numerically since the approximate solutions obtained numerically are sufficient and relatively simple as compared to the exact analytical solutions. A theoretical analysis was then carried out and a novel and detailed dependence on the water evaporation rate as a function of water temperature and the difference between water and cover temperature was determined. It was also found that the productivity of the SS with PCM strongly depends on the operating conditions. For uniform initial temperatures of the SS, its productivity decreases with an increasing PCM-to-water mass ratio, and the maximum decrease is 10.8%. If the SS is not thermally insulated, the PCM can take the role of a thermal insulator and increase productivity by 1.1%, but there is an optimal PCM-to-water mass ratio. The greatest increase in productivity, by up to 47.1%, can be obtained when the PCM is heated outside the SS and inserted into the SS when the water temperature starts to decrease. In this case, the productivity increases with the increasing PCM-to-water mass ratio. These outcomes fill a knowledge gap caused by a lack of justification for why in some cases, the application of PCM fails to improve the productivity of SS. Full article

In recent years, there has been a significant increase in investment in renewable energy sources, leading to the decarbonization of the electricity sector. Accordingly, a key concern is the influence of this process on future electricity market prices, which are expected to decrease with the increasing generation of renewable power. This is important for both current and future investors, as it can affect profitability. To address these concerns, a long-term analysis is proposed here to examine the influence of the future electricity mix on Iberian electricity prices in 2030. In this study, we employed artificial intelligence forecasting models that incorporated the main electricity price-driven components of MIBEL, providing accurate predictions for the real operation of the market. These can be extrapolated into the future to predict electricity prices in a scenario with high renewable power penetration. The results, obtained considering a framework featuring an increase in the penetration of renewables into MIBEL of up to 80% in 2030, showed that electricity prices are expected to decrease by around 50% in 2030 when compared to 2019, and there will be a new pattern of electricity prices throughout the year due to the uneven distribution of renewable electricity. The study’s findings are relevant for ongoing research on the unique challenges of energy markets with high levels of renewable generation. Full article