Renewable Energy Focus最新文献

{"title":"Assessment of Time-Based Demand Response Programs for Electric Vehicle Charging Facilities","authors":"Mehdi Nikzad ,&nbsp;Abouzar Samimi","doi":"10.1016/j.ref.2025.100693","DOIUrl":"10.1016/j.ref.2025.100693","url":null,"abstract":"<div><div>In this paper, we apply stochastic optimization techniques to manage the charging and discharging processes of Electric Vehicles (EVs) within parking lots, utilizing various Demand Response Programs (DRPs) like Time-of-Use (TOU), Critical Peak Pricing (CPP), and Real-Time Pricing (RTP). The optimization model aims to balance the interests of both the parking lot owner and EV owners, achieved through a weighted objective function. The primary goal for the parking lot operator is to lower costs related to charge EVs during DRP participation, managed via controlling vehicle charge and discharge cycles. Meanwhile, EV owners seek to mitigate battery degradation and extend battery life by avoiding excessive charging and discharging cycles. To quantify battery degradation, we utilize the Rainflow Counting Algorithm (RCA), assessing the number of charge/discharge cycles and depth of discharge (DoD). The model, based on Mixed-Integer Nonlinear Programming (MINLP), is solved using GAMS software with the BONMIN solver, integrated with MATLAB for executing RCA. Additionally, we employ probability distribution functions (PDFs) that closely match real-world data for modeling the stochastic nature of EV parameters, such as arrival/departure times and initial State of Charge (SOC). Compatibility of these models is validated using statistical tools available in MATLAB’s Statistics Toolbox. A simulation of a standard parking lot accommodating 30 vehicles is conducted to test the model, along with a sensitivity analysis of the weighting coefficient β in the objective function, which influences the prioritization between the parking lot owner’s and EV owners’ interests. Results show that at lower β values, benefits accrue more to the parking lot owner, favoring RTP programs. Conversely, higher β values prioritize EV owners’ objectives, resulting in stable energy consumption patterns without grid injections. A comparative analysis of the three DRPs is also provided, offering insights into their effectiveness and implications for both parties involved.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100693"},"PeriodicalIF":4.2,"publicationDate":"2025-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143534432","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon reduction and cost analysis in solar-biomass synergy for UAE’s 2030 energy transition","authors":"Neeraj Dhanraj Bokde,&nbsp;Jasmina Lazić,&nbsp;Carlo Fanara","doi":"10.1016/j.ref.2025.100691","DOIUrl":"10.1016/j.ref.2025.100691","url":null,"abstract":"<div><div>The United Arab Emirates faces a sharp rise in electricity demand, driven by the expansion of electric transportation, urban growth, and the increasing adoption of electric appliances. To address this, a strategic revision of the national energy policy is critical to achieve the UAE’s commitment at COP28 to triple renewable energy capacity by 2030. However, preliminary analyses suggest that relying solely on solar energy expansion, even with energy storage, may not be sufficient to meet the emissions target of 0.27 kg CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> per kWh by 2030. This study evaluates the integration of solar energy with two biomass sources: organic biomass and municipal solid waste (MSW)-based biomass, to address this gap. Organic biomass, despite higher fuel and capital costs, provides a stable and carbon-neutral energy source, while MSW-based biomass offers dual benefits of energy generation and urban waste management. Our findings indicate that combining solar and biomass significantly reduces the levelized cost of electricity and annual fuel costs while delivering substantial reductions in carbon emissions. For instance, incorporating biomass reduces the LCOE of the energy mix from $45.8/MWh in the baseline scenario to $38.1/MWh with organic biomass and $39.4/MWh with MSW-based biomass, while improving grid stability and enhancing storage utilization. This analysis highlights the critical role of a diversified renewable energy strategy in achieving the UAE’s sustainability goals. By integrating solar and bio-energy, the UAE can transition towards a cost-effective, resilient, and carbon-neutral energy system, paving the way for a more sustainable future.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100691"},"PeriodicalIF":4.2,"publicationDate":"2025-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143527499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Offering strategy of price-maker energy hubs in integrated local electricity and heat markets","authors":"Saba Norouzi ,&nbsp;Mojtaba Dadashi ,&nbsp;Sara Haghifam ,&nbsp;Hannu Laaksonen ,&nbsp;Kazem Zare","doi":"10.1016/j.ref.2025.100689","DOIUrl":"10.1016/j.ref.2025.100689","url":null,"abstract":"<div><div>Integrated energy systems are considered a promising solution for increasing the flexibility of energy systems and accommodating more renewable energy resources to achieve decarbonization targets. In the context of EU countries, power-to-heat technologies are useful for achieving sector-coupling aspirations. However, designing an appropriate market-based platform that facilitates efficient cooperation and interaction among various power and heat units is crucial. Integrated energy systems in the form of energy hubs play an important role in this market-based framework as interface agents among different energy carriers. To this end, the paper proposes a market design based on a simultaneous market clearing in local power and heat markets, in which a price-maker energy hub participates in an attempt to maximize its revenue by offering in the joint markets. Hence, a bi-level programming method is used, in which, at the upper level of the problem, the focus is on maximizing the entity’s profit, while the lower level addresses the local integrated market-clearing process. Second-order stochastic dominance constraints are also imposed on the problem to mitigate the studied energy hub’s market participation risks. The problem is solved in two different sections, including the risk-neutral and risk-averse perspectives of the energy hub operator. The results of the proposed risk-averse bi-level scheme are demonstrated to be appropriate for each EH to promote its benefit in the joint power and heat markets while controlling the profit distribution and the risk of market participation based on the operator’s market preference. The results indicate that implementing the proposed approach allows EH’s owner to adjust its day-ahead offers in real time using flexible units in both power and heat forms. Also, imposing second-order stochastic dominance constraints enables the EH’s operator to adjust its profit in the worst scenario based on its preference in a wide range, 873 € to 1737 €, which is not possible in other risk-management methods like CVaR.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100689"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143474278","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Solar photovoltaics adoption and its impacts on energy consumption: evidence from Japanese households","authors":"Merhaba Memtimin (Mairehaba) (Maimaitiming) ,&nbsp;Nan Wang ,&nbsp;Gento Mogi","doi":"10.1016/j.ref.2025.100690","DOIUrl":"10.1016/j.ref.2025.100690","url":null,"abstract":"<div><div>This study provides an in-depth analysis of solar photovoltaics (PV) adoption behavior in Japanese households using data from a five-year survey spanning 2014–2020. Through logistic regression, we investigate the relationship between socio-demographic characteristics, energy-saving behavior, and solar radiation and solar PV adoption. Furthermore, this work examines behavioral differences between households with and without solar PVs, focusing on the rebound effect in electricity consumption and spillover effects in the adoption of related technologies and other energy consumption patterns. Our findings reveal that larger households, residents of newly constructed, detached homes, and those with higher solar radiation exposure are more inclined to adopt solar PV systems. Conversely, lower-income households are less inclined towards solar PV installation, with little impact from energy-saving behaviors. The findings suggest a possible rebound effect, as solar PV households tend to use more electricity than non-PV households, while showing reduced reliance on other energy sources except gasoline. These households benefit from reduced total electricity costs by selling back excess solar-generated power. We also identify potential spillover effects in related technology adoption. This study sheds light on the complex dynamics of solar PV adoption and its broader impact on household energy behavior, providing valuable insights for promoting sustainable energy solutions.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100690"},"PeriodicalIF":4.2,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143520174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of micro-hybrid energy systems for rural electrification, challenges and probable interventions","authors":"Likonge Makai,&nbsp;Olawale Popoola","doi":"10.1016/j.ref.2025.100687","DOIUrl":"10.1016/j.ref.2025.100687","url":null,"abstract":"<div><div>Micro-hybrid energy systems (MHES) are essential for meeting the energy needs of end users. However, their implementation in mitigating energy deficit, especially in Sub-Saharan African rural, remains low. To substantially achieve sustainable development goal seven 7 (SDG7), Sub-Saharan African (SSA) countries must tackle the various risks, challenges, and barriers that hinder the rapid adoption and implementation of MHES. This research comprehensively reviews MHESs in SSA through the lenses of twenty selected countries while zeroing in on six countries, specifically focusing on rural Zambia using an elimination approach. The research analyzed micro-grids in these countries, drew lessons, addressed barriers and limitations, and provided possible mitigation strategies for the challenges. The study findings showed an insufficient focus on load assessment, prioritization, and behavioral change in rural areas to enhance the implementation and utilization of micro-grid renewable energy systems (MHRES). Another finding was the intermittent supply from one energy source, especially solar and wind; combining more than one energy source gives reliable, affordable, and sustainable energy to meet end users’ energy demands. These deductions are crucial for developing countries’ rural areas, particularly in SSA, where most of the population resides, lack access to electricity, and the low-key rural activities that impact economic development (gross domestic product -GDP). Integrating load assessment, prioritization, and behavioral tendencies for energy utilization of MHRES can lead to cost-effective implementation and utilization of renewable energy resources in rural areas. This research is vital for supporting sustainable energy access. Adopting mitigation strategies will guide addressing the challenges associated with sustainable MHRES implementation and the strategic planning level for rural electrification in Sub-Saharan African countries.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100687"},"PeriodicalIF":4.2,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143463279","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Grey Wolf Algorithm-Enhanced Sensor-Less Integral Sliding Mode Control of DFIG on Wind Turbine Systems under Real Variable Speeds using ANN/MRAS","authors":"Lakhdar Saihi,&nbsp;Fateh Ferroudji,&nbsp;Khayra Roummani,&nbsp;Khaled Koussa","doi":"10.1016/j.ref.2025.100688","DOIUrl":"10.1016/j.ref.2025.100688","url":null,"abstract":"<div><div>This study presents a robust Sensor-Less First Order Integral Sliding Mode (SL/FOISM) strategy, incorporating an innovative observer known as Artificial Neural Network with Model Reference Adaptive System/Adaptive (ANN/MRAS), specifically designed for wind turbine systems. The proposed model is implemented on a Doubly Fed Induction Generator (DFIG) operating under real variable speed conditions in the Adrar region of Algeria. The primary control objective is to independently regulate the reactive and active power of the DFIG stator. This is achieved through decoupling using the field-oriented control technique and control application via FOISM/C. An interesting feature of this methodology is the reduction in both the cost of the control scheme and the size of the DFIG by eliminating the need for a speed sensor. To enhance the Model Reference Adaptive System with Proportional-Integral (MRAS/PI), an ANN is introduced to replace the conventional PI controller in the adaptation mechanism of MRAS. The rotor position estimation is thoroughly examined across various load conditions, encompassing low, zero, and high-speed regions. The optimal parameters for the controller are determined through the application of Grey Wolf Optimization (GWO). The simulation results demonstrate the compelling performance of the proposed observer (ANN/MRAS), with rotor speed estimation errors reduced to less than 0.05% across all speed regions. The methodology ensures finite-time convergence, robust tracking of rotor speed with high accuracy, and resilience against parameter variations and load disturbances. Furthermore, the proposed control scheme achieves stable operation under variable speed conditions, showcasing adaptability and improved performance compared to the conventional MRAS/PI. Consequently, the estimated rotor speed converges to its actual value, demonstrating the capability to accurately estimate position across different speed regions (low/zero/high) while maintaining a maximum estimation error below acceptable thresholds.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100688"},"PeriodicalIF":4.2,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143444468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel deep learning based digital twin model for mitigating wake effects in wind farms","authors":"Abdollah Kavousi-Fard ,&nbsp;Morteza Dabbaghjamanesh ,&nbsp;Morteza Sheikh ,&nbsp;Tao Jin","doi":"10.1016/j.ref.2025.100686","DOIUrl":"10.1016/j.ref.2025.100686","url":null,"abstract":"<div><div>Wind energy plays a significant role in sustainable power generation in power systems such as energy hubs, microgrids, smart grids and smart cities. On the other hand, some challenges such as wake effects in wind farms can lead to reduced efficiency and increased maintenance costs for the wind farms. This paper presents a cutting-edge approach to tackle these challenges through the development of a novel deep learning-based digital twin model. The proposed model integrates advanced deep learning algorithms with digital twin technology to accurately simulate and predict wake effects within wind farms. By leveraging data from various sensors and weather forecasts, the model can dynamically adjust turbine settings and optimize energy production in real-time. Key features of the digital twin include a convolutional neural network (CNN) for spatial analysis of wake patterns, a recurrent neural network (RNN) for temporal modelling of wind behaviour, and a reinforcement learning (RL) framework for autonomous decision-making. Through extensive simulations and validation against field data, the model demonstrates superior performance in mitigating wake effects and improving overall wind farm efficiency. This research contributes to the advancement of renewable energy technologies by providing a robust and scalable solution for optimizing wind farm operations and maximizing energy output.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100686"},"PeriodicalIF":4.2,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143421871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal control strategy for enhancing energy efficiency of Pelamis wave energy converter: a Simulink-based simulation approach","authors":"Alireza Vakili ,&nbsp;Ali Pourzangbar ,&nbsp;Mir Mohammad Ettefagh ,&nbsp;Maghsoud Abdollahi Haghghi","doi":"10.1016/j.ref.2025.100685","DOIUrl":"10.1016/j.ref.2025.100685","url":null,"abstract":"<div><div>Wave energy is a promising renewable resource due to its predictability, consistency, and low environmental impact, making it an efficient solution for electricity generation in marine environments. Among various wave energy converters, the Pelamis stands out for its simplicity and scalability; however, its energy conversion efficiency can be further improved through advanced control strategies. This research aims to enhance the energy extraction efficiency of a Pelamis wave energy converter by implementing an optimal control strategy to regulate the production torque within the power take-off (PTO) system between the Pelamis cylinders. A dynamic model of the system interacting with regular waves is developed, and optimal control theory is applied to compute the PTO torques in real-time, maximizing the energy captured. The Pelamis energy converter and its control system were simulated in MATLAB’s Simulink environment. The results indicate that applying the optimal control method leads to a threefold increase in energy capture compared to the Proportional-Integral-Derivative (PID) control approach and a tenfold increase compared to the uncontrolled system. Additionally, frequency analysis of the average power output demonstrates that the energy gain with the optimal controller is achieved across all wave frequencies.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100685"},"PeriodicalIF":4.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402853","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Management and control strategy of multiple frequency powers in multifrequency microgrid","authors":"Rajdip Dey,&nbsp;Shabari Nath","doi":"10.1016/j.ref.2025.100681","DOIUrl":"10.1016/j.ref.2025.100681","url":null,"abstract":"<div><div>Multifrequency microgrid (MFMG) is a unique microgrid which has more than one frequency component superimposed on the bus is examined in this paper. There are three basic ideas behind MFMG which are orthogonal power flow theory, superposition theorem, and frequency selectivity criteria. It overcomes various disadvantages of traditional AC and DC microgrids and has many new features.</div><div>In MFMG, several frequency currents and voltages are superimposed on the multifrequency (MF) bus. The customers can select any available frequency currents at the load side. In MFMG, power is absorbed in different frequencies at load side and it creates different active and reactive power imbalance situations in MFMG. In existing literature, there is no analysis of the power imbalance of MFMG and the existing power control methods of microgrids cannot solve this problem. This paper bridges the gap by analyzing different power imbalance cases due to frequency selectivity criteria and proposes new control strategies to balance different frequency active and reactive powers in islanded and grid connected modes. The power balancing strategies are verified with 7 bus primitive MFMG structures in the Matlab Simulink environment.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100681"},"PeriodicalIF":4.2,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Trends in Active Distribution Network Fault Detection","authors":"Veronica A. Rosero-Morillo ,&nbsp;F. Gonzalez-Longatt ,&nbsp;Juan C. Quispe ,&nbsp;Eduardo J. Salazar ,&nbsp;Eduardo Orduña ,&nbsp;Mauricio E. Samper","doi":"10.1016/j.ref.2025.100684","DOIUrl":"10.1016/j.ref.2025.100684","url":null,"abstract":"<div><div>Electrical systems are constantly transforming to achieve global decarbonization and address the climate emergency. This process involves a substantial modernization of the distribution network that includes the integration of distributed energy resources, particularly those using inverter interfaces. Given the inevitability of faults, it is crucial to strengthen the infrastructure of protection systems so they can handle the new challenges imposed by this evolution. This article explores the challenges associated with protecting active distribution networks, caused by the incorporation of technologies such as rotary machines and power electronic converters. Special attention is given to critical issues such as changes in short-circuit currents, the bidirectional flow of currents, and the response times of protection relays. Current practical solutions are examined, and their limitations identified, highlighting the urgent need to develop more sophisticated and tailored protection schemes for the particularities of these networks. Additionally, the fault detection process is described in detail, breaking down the stages of parameter acquisition, signal processing, and fault classification, based on recent research. Finally, future trends in protection schemes are discussed, emphasizing the importance of continuously adapting and optimizing protection strategies in response to the dynamic evolution of electrical networks.</div></div>","PeriodicalId":29780,"journal":{"name":"Renewable Energy Focus","volume":"53 ","pages":"Article 100684"},"PeriodicalIF":4.2,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143181118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}