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With the consumption of fossil fuels and the impact of the greenhouse effect, renewable energies are ushering in a huge development opportunity, thus the optimal configuration of energy storage is essential to cope with the intermittence and fluctuation of renewable energies. This paper establishes a mathematical model for optimal sizing of energy storage in generation expansion planning (GEP) of new power system with high penetration of renewable energies. The objective function is to achieve the lowest total cost of investment and operation under the comprehensive consideration of various generation technologies and energy storage technologies. Carbon peaking and carbon neutrality goals are transformed into constraints of the GEP model to achieve high penetration of renewable energies in a power system. And 8760h operation curve are adopted to deal with the intermittence and fluctuation of renewable energies and obtains a more reasonable and realistic GEP results. Meanwhile, the optimal sizing of energy storage is solved in GEP model by detailed operation optimization and constraints of penetration rate and curtailment rate of renewable energies. Finally, the solving flow chart of GEP model and flow chart of optimal sizing of energy storage are given and the validity of this GEP model is proved in case analysis. In addition, carbon peaking goal may achieve in advance by vigorously developing wind power and PV power and configuring appropriate energy storage.

Nowadays, the shift towards renewable energies is happening at an exponential pace. Microgrids are an integral part in integrating renewable energies into the global energy mix. Due to the volatility of renewables, such as solar or wind, proper energy management is needed to avoid generation or load curtailment. This issue is addressed throughout the literature using a wide variety of strategies, ranging from classical linear to nature inspired metaheuristic optimization algorithms. This paper goes beyond the simulation phase of different optimization algorithms and addresses the optimal energy management problem by proposing a novel framework to integrate optimization strategies into the daily operation of microgrids. The proposed framework showcases 3 practical methods for controlling the distributed generators, as well as a communication scheme which facilitates the data transfer between the machine running the optimization strategy and the energy management system of the microgrid. The framework is demonstrated on a small-scale islanded microgrid setup, located at the Technical University of Cluj-Napoca. The microgrid setup consists of a photovoltaic array, a battery energy storage system and two dispatchable generators. A two-stage optimization strategy is used, consisting of a day-ahead stage, which uses the solar forecast provided by the Global Forecast System, prior to each day, to issue a working plan for the dispatchable generators, and an intra-day stage, which uses hourly solar forecasts, issued during the day, to adjust the operation of the microgrid and minimize the error between the day-ahead solar forecast and the actual weather conditions. Mixed integer linear programming is used to solve the optimization problem and validate the correct operation of the proposed framework over two case studies. The results show that the microgrid works as intended, in both scenarios, as well as the benefits of using an intra-day correction stage.

The increase in the feasibility of hydrogen-based generation makes it a promising addition to the realm of renewable energies that are being employed to address the issue of electric vehicle charging. This paper presents technical and an economical approach to evaluate a newer off-grid hybrid PV-hydrogen energy-based recharging station in the city of Jamshoro, Pakistan to meet the everyday charging needs of plug-in electric vehicles. The concept is designed and simulated by employing HOMER software. Hybrid PV-hydrogen and PV-hydrogen-battery are the two different scenarios that are carried out and compared based on their both technical as well as financial standpoints. The simulation results are evident that the hybrid PV- hydrogen-battery energy system has much more financial and economic benefits as compared with the PV-hydrogen energy system. Moreover, it is also seen that costs of energy from earlier from hybrid PV-hydrogen-battery is more appealing i.e. 0.358 $/kWh, from 0.412 $/kWh cost of energy from hybrid PV-hydrogen. The power produced by the hybrid PV- hydrogen - battery energy for the daily load demand of 1700 kWh /day, consists of two powers produced independently by the PV and fuel cells of 87.4 % and 12.6 %, respectively.

This study manages solar panels, wind turbines, and fuel cells to develop single- and three-phase Sinusoidal Pulse Width Modulation (SPWM) inverter circuits. The maximum power point tracking method in direct current (DC)-DC boost converters efficiently uses these renewable sources. Photovoltaic (PV), wind turbines, fuel cells, and bidirectional batteries are utilized in energy management. Efficiency, material cost reduction, and user convenience depend on energy management. The technology fully charges the standby battery when all sources are available. Other renewable sources will power the system if one fails. Before boost converter circuits, renewable energies generated 310 V for PV, 60 V for wind energy conversion, 215 V for fuel cells, and 25.9 V for bi-directional batteries. Proportional-integral (PI) controllers govern inverter switching to maintain high-quality sinusoidal outputs while decreasing total harmonic distribution (THD). Single-phase load voltage and current at resistive load have 0.65419 % THD. Load voltage and current root main square (RMS) values are 217.3617 (V) and 3.1052 (A), respectively. When connected to an R load, the three-phase inverter circuit provides 1.5146 % THD for load voltage and current. Load voltage and current RMS readings are 218.4261 (V) and 2.1843 (A). THD is 1.5969 % for load voltage and 1.2905 % for load current with an RL load. In this example, load voltage and current RMS values are 214.201 (V) and 2.0916 (A). Simulations demonstrate the successful integration of renewable sources to meet energy needs and maintain power supply. The above solutions use renewable energy efficiently and integrate with the grid.

District heating networks with combined heat and power systems and renewable energies are one of the most promising solutions for efficient and sustainable energy supply. In many cases, however, especially for district heating networks prior to the 4th generation, significant renovations are required to meet decarbonization targets. In this paper a study is proposed to evaluate the integration of high temperature heat pumps in an existing combined heat and power - district heating plant to reduce fossil fuel consumption and increase the exploitation of renewable energy sources. The plant is currently operating in central Italy and connects more than 1250 users. The identified solution implies lowering the district heating networks operating temperature and supplying power peaks with a high temperature heat pump acting as a booster. Results showed significant improvements in system performance especially in the winter months, due to the greater impact of lowering the temperature level of the district heating network during these months. Overall, the updated scenario allows the overall demand and ground heat losses to be reduced annually by 5.3 % and 13.5 % respectively. This reduces natural gas consumption by 13.3 % and avoids the emission of about 836 tCO2. The analysis provides guidelines for the upgrade of 3rd generation district heating network that can be useful for planning improvements towards newest generation thermal networks.

The economic importance of the selection of alternative energies in the national scenario tends to be maintained with the optimistic forecast of an increase in production for the years to come in Tunisia. The problem of choosing multiple attributes for the selection of renewable energies is a set of concepts whose purpose is to help the user in a decision-making process. This help provided to the user is designed to be the most online with his preferences. The objective of this study is to answer the following question: How to decide to determine the optimal alternative energies from a large set of available outcomes for this case study according to the decision maker’s preferences? The purpose of this article was to solve multi-attribute choice problems by simultaneously using the choice to essentially define comparative superiority, inferiority, and the flow of non-inferiority as indicators of goodness/poverty evidence. We have developed a new method called Multi-Attribute Superiority, Inferiority and Non-Inferiority Selection Approach (MASINISA) based on the successive elimination Multi-Attribute Decision Making (MADM) to solve the selection of renewable energies in a certain environment: the case of the STEG Company in Tunisia. We can ascertain that the renewable energy technologies belonging to the screened set produced by the proposed MASINISA version were all judged admissible by the experts of the STEG.

Population growth and economic development have significantly increased global energy demand. Hence, it has raised concerns about the increase in the consumption of fossil fuels and climate change. The present work introduced a new approach to using carbon-free energy sources, such as nuclear and renewable, to meet energy demand. The idea of using the Nuclear-Renewable Hybrid Energy System (N-R HES) is suggested as a leading solution that couples a nuclear power plant with renewable energy and hydrogen-based storage systems. For this purpose, using a meta-heuristic method based on Newton's laws, the configuration of the N-R HES is optimized from an economic and reliability point of view. The optimal system is selected from among six cases with different subsystems such as wind turbine, photovoltaic panel, nuclear reactor, electrolysis, fuel cell, and hydrogen storage tank. Furthermore, the performance of hydrogen-based energy storage systems such as high-temperature electrolysis (HTE) and low-temperature electrolysis (LTE) is evaluated from technical and economic aspects. The results of this work showed that using nuclear energy to supply the base load increases the reliability of the system and reduces the loss of power supply probability to zero. More than 70 % of the power is produced by nuclear reactors, which includes more than 80 % of the system costs. The key findings showed that despite HTE's higher efficiency, using LTE as a storage system in N-R HES is more cost-effective. Finally, due to recent developments and the safer design of nuclear reactors, they can play an important role in combination with renewable energies to support carbon-free energy sectors, especially in remote areas, for decades to come.

Nowadays, a progressive increase in the penetration of dispersed renewable energies in electricity markets has imposed many serious challenges, such as congestion of lines, customer dissatisfaction, and disassembly of nodal prices. To address these challenges, this paper looks into commercial cryogenic energy storage (CES) and electric vehicles (EV) in conjunction with distributed generations with the aim of congestion management while taking distribution locational marginal pricing (DLMP) into account. Additionally, a unique reconfiguration strategy has been considered in the formulation to maximize the efficiency of the CES and EV integration in the DLMP smoothing and ultimately social welfare maximization. An effective extension of risk-constrained stochastic programming is used to deal with uncertainty related to renewable energy sources. A conditional value-at-risk metric is employed to establish a substantial balance between anticipated gains and the susceptibility to uncertainties, offering a valuable framework for decision-making. The effectiveness of the suggested strategy was ultimately proved by the simulation on the IEEE 33-bus distribution system. The advocated reconfiguration strategy incorporating CES and EV has resulted in a 37.5% reduction in distribution line congestion compared to the initial case.

Latin America and the Caribbean is a region that has grown enormously in public policies and especially in the implementation of renewable energy generation plants, which is why it deserves to study its growth to provide long-term deep decarbonization routes. It has approximately 634 million inhabitants, and it is expected that by 2050 it will reach 784 million inhabitants, which worries researchers to establish a new model of energy supply in accordance with future demand. The concern does not end here, the new energy supply must be friendly to the environment and renewable energies are the appropriate option to avoid the increase in global temperature. The challenge of this research is to provide an adequate option for the decarbonization of Latin America and the Caribbean to achieve 100 % renewable energy by 2050. For this purpose, the energyPLAN tool is used, a flexible tool, very useful to transform large energy systems based on fossil fuels and achieve comprehensive 100 % renewable markets. Power systems are considered a challenging task and are widely studied around the world to avoid the great negative effects of altering the climate. Modeling the zero carbon energy system was implemented using the concept of smart energy. The combination shows that it is necessary to use a wide variety of energy sources and that no energy source more than 35 % stake, to increase energy security. The historic hydroelectric technology will continue to be an essential part of the Latin American energy mix. However, in 2050, the technologies that are destined to have the greatest participation will be wind turbines and solar photovoltaic with 32.7 % and 31 % respectively. Technologies with less participation such as renewable thermal and geothermal are also identified. Achieving a 100 % renewable energy mix by 2050 will prove to be economically beneficial. Based on the results obtained, it will be effective to achieve a 100 % renewable scenario when Latin America and the Caribbean form a solid regional alliance exclusive to fight for the environment and legislate favorably so that its member countries contemplate important budgets in a conscious, responsible and supportive way.

This study investigates the relationship between oil prices and global CO2 emissions under an instrumental variable research design. In the first stage, we take advantage of the global oil market model developed by Baumeister and Hamilton (2019) to produce exogenous shocks to the oil supply and global economic activity. In the second stage, we use these shocks to compute impulse responses to observed oil prices and CO2 emissions. Finally, based on the latter computations, we obtain the dynamic multiplier that measures the shock-specific effect driving a 1% increase in the oil price on the cumulative CO2 emissions. Our results reveal a nuanced relationship: not all increases in oil prices uniformly lead to a reduction in CO2 emissions. Reductions in CO2 emissions are predominantly observed when increases in oil prices are supply-driven, revealing a substitution effect from fossil fuel to renewable energies in the energy market. However, CO2 emissions increase when oil prices are higher during times with positive shocks to global economic activity.

Renewable energy systems have garnered increasing attention as a viable solution to global warming and climate change. A key challenge in advancing renewable energies lies in ensuring energy stability, a concern effectively addressed through hybridization. Wastewater treatment plants, with their high energy consumption and potential for renewable energy integration, offer an opportune platform for implementing these systems. This paper introduces a flexible model for a hybrid energy system encompassing solar, wind, and biogas energy, seamlessly connected to the grid. The system is designed with three primary objectives: meeting the energy demand of the treatment plant, supporting the grid by selling excess energy during power outages, and generating green hydrogen. The treatment plant's average daily consumption is 10.28 MWh. Optimization using HOMER Pro resulted in the selection of System A as the most efficient configuration, comprising 1924 kW solar panels, two 1.5 MW wind turbines, a 500 kW biogas generator, a 578 kW converter, and a 1270 kW electrolyzer, with an initial cost of USD 2.41 million. The Net Present Cost (NPC) and Cost of Energy (COE), without factoring in hydrogen sales revenue, were determined to be USD 4.88 million and USD 0.057 per kWh, respectively. During the power blackout periods in July, August, and September, which are the main outage months, the system significantly improved grid stability by selling a total of 1515 MWh of energy, thereby providing crucial support to the grid. On average, the system produces 82.45 tons/year of green hydrogen, with hydrogen sales reducing the NPC to USD 657,000.The carbon reduction achieved by this system amounts to 1792 tons/year. In conclusion, the proposed hybrid energy system demonstrates the potential of multi-task energy models, shaping a future where diverse facilities meet their energy needs, enhancing sustainability in both individual systems and the broader grid. This study offers valuable insights for policymakers, researchers, and activists striving to advance global clean energy and sustainable development goals.

Climate change is causing an increase in extreme weather events that can stress the electric grid as it was not originally designed to withstand them, and at the same time, new unexpected threats emerge such as cyberattacks making the grid more vulnerable. On top of that, situations such as the new pandemic of Covid-19 pose the grid under new scenarios of large load reduction where renewable energies gain importance and traditional sources are strongly curtailed. On this basis, the resilience of the electrical grid turns into a key feature to be analysed and strongly enhanced. Thus, the power grid is being analysed by researchers in recent years to assess such hazards along with what measures or resources are effective against them, such as distributed energy resources based on renewable energies. Based on these studies, this paper aims to explore which power grid resilience KPIs fit more to describe the scenarios of the disruptive events for the consequent discussion of the installation of renewable sources to prioritize investments in order to minimize impacts. Furthermore, a geographic information system based model is developed to analyse a static study case of flooding in the city of Barcelona. Results show that the city’s power grid is vulnerable to the scenario, but it has the potential of renewable energies to mitigate its consequences.

The objective of this paper is to derive, for the first time, decarbonization roadmaps for the ten nations of ASEAN. This study first presents a regional view of ASEAN’s fossil and renewable energy usage and energy-related CO2emission. Results show that renewable energies have been losing ground to fossil energies in the last two decades and fossil fuels will likely continue to be an important part of ASEAN’s energy mix for the next few decades. Therefore, decarbonizing efforts should focus not only on increasing the share of renewable energies in electricity generation, but also on technologies to reduce CO2emission from fossil power and industrial plants. This study next performs a technology mapping exercise for all ten ASEAN countries to determine decarbonization technologies that have high impact and high readiness for individual countries. Besides installing more sustainable renewable energies, common themes coming from these roadmaps include switching from coal to gas for power generation, using carbon capture and storage (CCS) technologies to decarbonize fossil and industrial plants, replacing internal combustion vehicles by electric vehicles, and for countries that have coal and natural gas resources, upgrading them to blue hydrogen by chemical processes and using CCS to mitigate the emitted CO2. Blue hydrogen can be used to decarbonize hard-to-decarbonize industries. Policy implications of these roadmaps include imposing a credible carbon tax, establishing a national hydrogen strategy, intergovernmental coordination to establish regional CCS corridors, funding research and development to improve carbon capture efficiency on a plant level and resolving sustainability issues of hydropower and bioenergy in ASEAN.

The quality of the electrical energy produced from renewable energies is a preponderant need sought by electricity producers. It is in this vision that this present article tries to design a control that combines two control algorithms in order to improve the operation of a variable speed wind energy conversion system (VSWECS). Interestingly, combined control brings together fuzzy field oriented control (FFOC) with direct power control (DPC). The complete conversion chain includes the 1.5 MW permanent magnet synchronous generator (PMSG) and two full-scale mounted back-to-back power converters. Compared to FOC method based on the classical PI regulator, the proposed FFOC scheme is employed to guarantee a better performance between the effect of artificial intelligence (AI) and the simplicity of the standard regulator. This is because the FFOC smart control algorithm is used to control the machine-side-converter (MSC). The DPC control algorithm which uses a relatively low sampling frequency of around 5 kHz is proposed to estimate the active and reactive powers injected into the grid through the grid-side converter (GSC). In addition to the simplicity of implementation and the reduced simulation time, the combination of the FFOC-DPC control algorithm is very reassuring in terms of stability, robustness and tracking of set-points. The overall control scheme is simple to implement and the simulation results clearly show that the proposed control system offers very good performance in terms of total harmonic distortion (THD), which does not exceed 1.49%, a wave of well-balanced injected electric current, and a power factor almost equal to unity. Therefore, the proposed solution is finally compared with other alternatives to validate the results developed by the MATLAB/Simulink platform and consequently guarantee the improvement of the variable speed direct drive WECS.

With the clear adverse impacts of fossil fuel-based energy systems on the climate and environment, ever-growing interest and rapid developments are taking place toward full or nearly full dependence on renewable energies in the next few decades. Estonia is a European country with large demands for electricity and thermal energy for district heating. Considering it as the case study, this work explores the feasibility and full potential of optimally sized photovoltaic (PV), wind, and PV/wind systems, equipped with electric and thermal storage, to fulfill those demands. Given the large excess energy from 100% renewable energy systems for an entire country, this excess is utilized to first meet the district heating demand, and then to produce hydrogen fuel. Using simplified models for PV and wind systems and considering polymer electrolyte membrane (PEM) electrolysis, a genetic optimizer is employed for scanning Estonia for optimal installation sites of the three systems that maximize the fulfillment of the demand and the supply–demand matching while minimizing the cost of energy. The results demonstrate the feasibility of all systems, fully covering the two demands while making a profit, compared to selling the excess produced electricity directly. However, the PV-driven system showed enormous required system capacity and amounts of excess energy with the limited solar resources in Estonia. The wind system showed relatively closer characteristics to the hybrid system but required a higher storage capacity by 75.77%. The hybrid PV/wind-driven system required a total capacity of 194 GW, most of which belong to the wind system. It was also superior concerning the amount (15.05 × 109tons) and cost (1.42 USD/kg) of the produced green hydrogen. With such full mapping of the installation capacities and techno-economic parameters of the three systems across the country, this study can assist policymakers when planning different country-scale cogeneration systems.

Urban borders are expanding in cities, solar photovoltaic and wind energy are being used and decentralized more and more, while the electrification of transport systems is in permanent progress. Users trust more in the modernization of electrical systems giving rise to various applications. The efforts made by both the public and private sectors are isolated and are not framed within comprehensive planning. For this reason, cities must be fully planned and contemplated in their land use plans. This article presents a long-term roadmap for the comprehensive electrification of mobility. To achieve a proper approach, it is based on the EnergyPLAN tool that uses the concept of smart energy and determines the long-term scenarios, the case of study is for the City of Cuenca in Ecuador. It seeks to take advantage of the potential of renewable energies available in the territory, which are evaluated and provide the necessary energy to feed future decentralized transport systems with a view to 2050. The long-term results show that the energy mix would be composed of wind with 37.3%, followed by solar photovoltaic with 33.9% and hydroelectric with 25.4%. There are others technologies such as biomass that do not exceed 3.4%.

Balancing services are traded on the balancing market, which has undergone major shifts in recent years due to external factors like the growing share of renewable energies in electricity production and the progressing electrification of society, especially in the mobility sector. This trend increases the demand for balancing services. However, market design is also changing to lower overall expenses for grid stability, which influences price volatility and overall costs for balancing services. Shorter provision times, low capacity limits, and a smaller gap between gate closure time and delivery time enable more flexible market participation of balancing service providers. This article provides an overview of the common European balancing market with a focus on Germany, including recent and upcoming regulatory changes and market design. Recent price trends highlight the importance of market design, especially provision times and price limits. The reduction of the provision time for Frequency Containment Reserve increased offered capacity per bid, and the end of the mixed price procedure in August 2019 led to a less concentrated price range for balancing energy. The introduction of the energy-only market in November 2020 shifted demand from tertiary to secondary control reserve. However, high energy prices in 2021 and 2022 have revealed the limited responsiveness of the balancing energy market. This effect will be reinforced with the exiting of coal-fired and nuclear plants from the pool of balancing service providers in the current decade. Additionally, the future development of the market depends on the integration of energy storage systems such as stationary batteries and electric vehicle batteries, including the regulatory framework.

During the heating season, cities in northeast China primarily emphasize the implementation of large-scale CHP central heating systems. However, the heat-electricity constraints associated with these heating units hinder the integration of clean energy sources such as wind power, photovoltaic, and other renewable energies. Despite efforts to reduce carbon emissions and address concerns related to urban haze formation, energy conservation, and emission reduction, coal remains the predominant energy source for heating.

Irregular nature of renewable energies namely solar and wind entails making use of storage units to improve the reliability of the designed systems and enhance the overall performance and output. In conditions of applying thermal energy technologies like solar thermal power plants and solar collectors, storage systems with ability of storing energy in thermal form are employed. In general, due to some advantages of latent heat thermal energy storage mainly known as Phase Change Material (PCM), like high heat capacity, these types of storage materials are widely used in thermal systems. In addition to energy storage, PCMs are utilizable for some other purposes namely device thermal management like solar PV/Thermal systems. In spite of benefits of PCMs in term of capacity of storage, low thermal conductivity is one the main disadvantages of them. Some techniques and approaches like utilization of nanomaterials, fins and foams are suggested to resolve this issue. The aim of current study is to review the research works on the simultaneous applications of fins and nanomaterials in PCMs. With respect to the findings of the research works it can be stated that there is significant potential in improvement of phase change rate by simultaneous usage of both fins and nanomaterials. The rate of phase change in these cases can be affected by the type of nanomaterials and the characteristics of the fins.

Energy price hikes and the pollutant nature of fossil fuels have led energy producers to focus on the development of renewable energies. In the last few decades, the design of hybrid renewable energy systems presented itself as a difficult task because of its interference, uncertainty and especially unpredictable nature. However, scientific progress has enabled several solutions to be found to the problems associated with them. The aim of this article is to provide industries with satisfactory energy that respects the demand and supply balance with excellent energy quality, reduced losses and improved efficiency. To achieve these objectives, an energy management system based on fuzzy logic is proposed and applied to the hybrid photovoltaic hydroelectric system coupled to the DC link through electronic switches. The proposed method is based on the error in the output voltage at the AC link. On the basis of the error and its variations, 81 fuzzy rules are established and offer the advantage that they do not take in to account the mathematical model of the system. In addition, the proposed algorithm is seen at the DC link as a controlled current source which has the advantage of automatically compensating the power deficit required by the loads. Under the strong influence of non-linear loads, and in comparison with the Artificial Ant Colony (ACO) and Proportional Integral (PI) control techniques, simulation results in the Matlab/Simulink environment present satisfactory results for the proposed algorithm in terms of robustness to disturbances, good response and compensation speed, excellent energy balance and quality, with total harmonic distortion values well below the standards. Quantitatively, the proposed algorithm averagely improves the response speed of the system by 12.72%, the root-mean-square error by 31% and the total harmonic distortion by 30% as compared to the other two methods.

The high-frequency standard magnetic links were recently considered viable candidates for construction of the medium-voltage power converters, rather than link with the common dc specialized magnetic materials, like nano-crystalline and the amorphous materials. This provides a new route of portable and lightweight incorporation of renewable systems into the direct grid, stepping-up transformer. The main objective is to propose an ideal design approach for magnetic links and to validate their viability by the evaluation of a sample. This will discuss a specific approach to design, research, and implementation. The predicted result is that the proposed architecture strategy will be implemented effectively in the future with clean energy generation schemes and intelligent grids. The current approaches have some critical disadvantages, including voltage mismatch, minimum overall power extraction, and general mode problems because of several direct grid and common dc connections. With emphasis on implementing renewable energies, exploring different forms of configuring structures for efficiency and output is becoming increasingly relevant. Both technologies employ grid-based voltage converters, but conventional equipment poses several problems in terms of voltage balance and maximum power output. Magnetic connections are a viable solution to minimize the costs, reliability, and consistency of the network. Instead of several dc links, these can be solved. Thus, the plan will depend on its optimal design to monitor system costs while improving efficiency by adding a new magnet-powered voltage converter. Particularly the voltage mismatch and typical mode problems of converter systems are minimized. The electromagnetically designed common magnetic links are, however, a multi-physics challenge, affecting device performance and costs. The paper objectives are to propose an ideal design approach for magnetic links and to validate their viability by the evaluation of a sample.

Nowadays, global warming and fossil fuel depletion are two unsolved problems. Research is underway on renewable energies, which are new energy sources. This study aims to improve the performance of microbial fuel cells (MFCs), a renewable energy generation method. Urethane was used as the electrode material for MFC. Urethane is an excellent material suitable for use as MFC electrodes because of its durability, porosity, and other properties. However, urethane itself is not conducive. This study used conductive urethane, which is coated with activated carbon powder, as the electrode material. This material is used in deodorizing filters, air conditioning filters, and air cleaner filters. To improve the performance of MFC, carbon nanotubes and activated carbon powder were added to the urethane electrodes. PTFE was also used to improve cathodic function. PTFE is used as a binder in many microbial fuel cells. The performance of the electrodes was compared. The analysis included power density measurements and discharge characteristics. It was confirmed that the use of PTFE improves the power density by a factor of two or more. The MFC generated a maximum power density of 28.27 μW/cm2. SEM image analysis of the electrode after the experiment confirmed that PTFE could reduce the adhesion of microorganisms on the cathode surface. These results imply that the use of conductive urethanes as electrodes in MFCs is effective. The addition of carbon nanotubes, activated carbon powder, and PTFE has enabled the use of urethane as an electrode material for microbial fuel cells.

China is pushing ahead with the development of the electricity market based on renewable energies. Electricity futures and options are an important trading instrument in the electricity market, and margins in the electricity market are often used to measure the value at risk of derivatives such as options on electricity futures, which are usually calculated based on the SPAN system. However, traditional SPAN systems do not take into account the integrity of electricity (IoE) derivatives, which would affect the risk valuing and capital usage efficiency. This paper proposed an improved margin calculation method that considers the IoE and gave an example for explanation. Compared with the previous calculating method, the method can effectively control the sharp fluctuations in electricity prices when renewable energy sources are traded in the electricity market, and effectively control the default risk in the market.

In recent years, many projects have been developed to reduce the energy consumption of buildings, both from the point of view of energy efficiency and the integration of renewable energies. However, few projects are related to the problem of integrating DER in environments dominated by high-tech equipment, the so-called ”critical loads”: data centers, railroad stations, airports, and hospitals. The European Interreg Sudoe IMPROVEMENT project aim is to renovate existing public buildings where critical loads predominate, converting them into nearly zero-energy buildings (NZEB), and for this purpose, it integrates combined cooling, heat, and power (CCHP) microgrid with renewable and other distributed energy resources (DER) like hybrid energy storage systems (ESS). With still one year to go before the end of the project, the consortium partners present in this position paper the latest progress of their respective work packages to date.

Researchers are becoming more interested in renewable energies as a viable answer for today’s energy needs due to the rising demand for energy and climate changes brought on by the use of fossil fuel resources. One of the most significant sources of renewable energy is solar energy. Photovoltaic systems are used to convert the received solar radiation to electricity. Low overall performance throughout the operational time caused by raising the solar cells’ temperature is one of the most significant problems with the use of photovoltaic systems. In this experimental work, the influence of optical filters on the performance of photovoltaic panels was studied under Sharjah meteorological conditions. In this study, a 50 W solar PV module’s outdoor performance characteristics were analyzed. This case study employed a Plexiglas sheet, a box filled with air and water, and affixed it directly to the top surface of the PV panel to demonstrate the impact of the Plexiglas as an optical filter on the electrical productivity of the PV panel in relation to the variation in temperature caused by the filters. By imposing optical filters, and therefore lowering the temperature of the system, this work shows promising results in boosting the performance of the PV module. Module current drops dramatically as solar irradiance is blocked, yet panel voltage rises for filter-covered panels compared to the reference panel. In terms of fill factor and electrical efficiency, there has been a noticeable improvement. The voltage at maximum power, electrical efficiency, and maximum output power increased significantly. The average efficiencies of a reference PV module, a plexiglass-sheet-covered PV module, and a plexiglass-air-box-covered PV module are 7.02%, 7.5%, and 8.12%, respectively. In comparison to the reference module’s average efficiency of 6.66%, the covered PV module with plexiglass water box averages 6.74%

The environmental awareness and rising costs of marine fuel led research activities to focus on eliminating the dependence on fossil fuels as a traditional source of energy. Clean and renewable energies, such as hydro energy for instance, could be used onboard to enhance the ship energy efficiency.

AC & DC hybrid power grid is an important trend of the future renewable energy based new-type power system. Power electronic transformer with multi AC and DC ports is the key device for renewable energy conversion and transmission. Global concerns are growing about the power electronic transformer and its control in the academic and industry communities. The existing topologies have disadvantages such as large volume, too many power conversion stages, difficult power balancing among submodule units, and complicated circulating control. On the other side, the lack of inertial of common power converter control strategies brings potential instability for renewable energies. TP-MMC has a compact structure and provides two independent AC ports and one DC port. It is suitable for the interconnection among AC & DC power grids. A voltage source control strategy is proposed in this paper for one of the AC ports in TP-MMC. The inertial link is added in the phase lock loop and the inner impedance is added in the dual loop control strategy. Thus, the proposed control strategy provides virtual inertial and brings self-synchronous ability. The AC port works as a voltage source with flexible virtual impedance. Active and reactive power can be controlled by frequency and voltage respectively. The proposed voltage source control strategy is validated by simulation results.

In addition to a massive expansion of renewable energies, a successful change towards a decarbonized energy system requires the flexibilization of consumers and the integration of storage and sector coupling technologies. Bidirectionally chargeable electric vehicles (EVs) represent such a consumer flexibility. They are able to charge when there is an electricity generation surplus and to discharge when there is a shortage in electricity generation. Therefore, they can act as a storage from the perspective of the energy system. This paper analyzes different modeling approaches of bidirectionally chargeable EVs in large-scale energy systems and evaluates the impact of bidirectionally chargeable EVs on the future European energy system design. We compare the modeling of discrete EV profiles, clustered EV profiles as well as an aggregated EV profile with simplified constraints. Aggregation of EV profiles per country leads to significantly lower computation times, while still achieving results close to the reference case. The number of bidirectionally chargeable EVs in a cost optimal future European energy system increases from 6 million EVs in 2025 to over 60 million EVs in 2050. We show that bidirectionally chargeable EVs lead to a better integration of PV generation, to lower installed capacities of gas- and hydrogen-fired power plants as well as stationary battery storages. They also lead to decreasing electricity prices and total European energy system costs.

Wind power forecast is becoming more and more important as the ever-increasing penetration of renewable energies brings uncertainties to the power systems. Although the numerical weather prediction (NWP) has already been widely applied on wind power forecast, it involves high computational burden with complex meteorological models, which has great uncertainty in real environment, so machine learning methods are the significant supplement for accurate wind power forecast. This paper proposes a deep learning model to improve the prediction accuracy based on the NWP data. Variational Mode Decomposition (VMD) is applied to extract time-series information. Furthermore, an encoder–decoder structure consisting of a dual attention-long short term memory (LSTM) neural network is constructed to enhance the forecasting accuracy. The comparison between the proposed model and several benchmark models, show the superiority of proposed model in effectively enhancing the prediction performance.

Using renewable energies such as wind and solar energy, two types of renewable energy, we may adjust the structure of the energy system, addressing both energy and environmental challenges at the same time. As a result of its impact on the environment, wind and solar energy generation are inherently unreliable sources of energy. Lithium batteries, a technology that is becoming increasingly mature in terms of energy storage, are a critical component of the answer to the problem of instability. In order to avoid waste and expense increases, the capacity should not be too large or too small, respectively. Power consumption restricts the amount of energy that may be stored, but industrial power usage is unpredictable and non-periodic. This is a significant task that needs the development of a model that can dispatch while still providing a reasonable amount of storage. In this paper, we develop a KNN classification model that considers the test cyclic of photovoltaic (PV) generation that includes battery installation, data on electricity consumption and data on PV generation in India. These metrics are used to develop an energy management model. The model aims at the reduction of operation cost and optimal storage of energy that should satisfy the grid demands. The results of simulation and the comparison of the theoretical results shows that the proposed model has higher optimisation of energy in the storage devices in case of distributed systems.

With the increasing global population, fossil fuel resources still represent a main contributor to the energy supply, despite the progress made in the field of renewable energies. Large quantities of residual oil from mature reservoirs cannot be produced through primary and secondary recovery methods. Among alternative recovery techniques, chemically enhanced oil recovery methods are attracting considerable interest to increase the hydrocarbon recovery from oil-bearing geological formations. The wettability of any particular formation can be used to predict the oil recovery factor of a reservoir based on its wetting state. However, due to the complex nature of geological porous media, special treatments are required to control the wetting characteristics for improving the oil recovery. In this work, methyl orange (MO), a hazardous pollutant widely discharged in industrial wastewater, was used as a chemical agent for the purpose of altering the wettability. Initially, quartz substrates were aged with 10−2mol/L n-decane/stearic acid solution to mimic natural geological conditions; then, stearic acid-aged quartz substrates were treated in various concentrations of MO (10, 25, 50, 75, and 100 mg/L) for 7 days at 50 °C, followed by advancing and receding contact angle measurements at various physico-thermal geological conditions (temperature 25, 50 °C, pressure 10, 15, 20 MPa, and brine salinity 0–0.3 M). Our results demonstrate that increasing the temperature, pressure, and salinity of quartz aged with stearic acid has a negative effect on the wettability (resulting in a higher hydrophobicity). However, at any constant physio-thermal condition, MO significantly alters the wettability of the organic-aged quartz substrates from oil-wet to water-wet conditions, thus improving oil recovery. The concentration of MO plays a critical role, with increasing concentrations favouring the water-wet conditions. Quartz aged with MO at a concentration of 100 mg/L shows water-wet behaviour, with the lowest advancing and receding contact angles of 31° and 29°, respectively, at 25 °C, 20 MPa, and 0.3 M salinity. The findings of this study provide new insights that can be useful for disposing MO in deep underground reservoirs rather than discharging into the hydrosphere, thus mitigating climate change. In addition, the present data can be helpful for improving the oil productivity from sandstone reservoirs.

Smart grid systems help increase RWJ projects (RWJ) so that environmentally friendly energy production can be generated. However, efficient technologies should be implemented to ensure the sustainability of smart grid systems. This study aims to evaluate renewable-friendly smart grid technologies regarding distributed energy investment projects by using a hybrid picture fuzzy rough decision-making approach. Firstly, selected criteria are weighted using the multi stepwise weight assessment ratio analysis (M-SWARA) method based on picture fuzzy rough sets (PFRSs). Subsequently, different renewable-friendly smart grid technologies are ranked with the complex proportional assessment (COPRAS) technique by using PFRSs. It is determined that research and development play the most critical role with respect to the renewable-friendly smart grid technologies for distributed energy investment projects. On the other side, cost is another essential factor for this issue. It is also identified that direct current links are the most important renewable-friendly smart grid technology alternative. Priorities should be given to the development of research and development studies on renewable energies to increase the efficiency of smart grid systems. In this context, private sector companies have a very important role. Similarly, incentives provided by governments to RWJ research and development studies should be increased. Within the scope of these studies, new technologies for RWJ types should be emphasized. In this context, new technologies for all RWJ alternatives should be followed comprehensively. Increasing research and development for such investments will also make smart grid systems more successful.

The Green Pact signed by the European Union establishes a trend towards renewable energies to combat the greenhouse gas emissions. Among the technologies used to produce this type of energy, wind power generation technology stands out, which, in countries such as Spain, already has significant installed power. The main problems posed by this technology plans are the uncertainty intervals of wind power and its inclusion in the electricity market, due to the complex price system that does not always favor the producers. The main purpose of this research is to promote the installation of more wind power plants. For this, the installation of cryptocurrency mining equipment is proposed, which will be powered by the generation produced by these wind power plants. The article analyzes the production of cryptocurrencies is a growing business. In the research process, the latest cryptocurrency mining equipment is evaluated. It is analyzed which equipment is the most suitable for its installation in the wind power plant and an economic study is made for the construction project of a large wind power plant. Finally, it will be seen that in this way the amortization time of the facilities decreases and also the project is more attractive for the investor since they can decide between injecting energy into the electrical network or mining cryptocurrencies. If a wind power plant invests in cryptocurrency mining in parallel to the production of electrical energy for the grid, it can decide when to enter the electricity market pool or engage in mining. In this way, the idea of building many more wind power plants becomes more attractive. This would lead to a market where this renewable energy would be much more abundant and the price curve would shift to a lower price, as well as a significant reduction in greenhouse emissions.