Renewable Energy Systems Research Articles

Approach Proposal for Energy-Efficient Retrofit of Historic Buildings with Comparative Analysis of EU Research Projects

Within the framework of the building section, the existing building stock is a research area with a high potential for energy savings, as it is a crucial energy consumption source. Studies are being carried out on many existing building stocks to prevent and reduce the increasing energy consumption and negative situations due to climate change and global warming. It is seen that parameters such as energy efficiency are considered as a whole with conservation in intervention methods, especially in European countries, since only conservation is insufficient for historical buildings, which are one of the primary sources of important existing building stock. Preserving cultural identity values and energy efficiency are the primary intervention criteria. By considering these two intervention criteria in balance and as a whole, the permanence and sustainability of the buildings for future generations is ensured. In this regard, comprehensive, large-scale, and multinational projects supported by the European Union (EU), especially in European countries, are carried out. In line with the conclusions drawn from the detailed and systematic analysis, comparison, and evaluation of the projects, the study proposed an approach and intervention model for future studies. The determined projects were examined in detail regarding purpose, scope, target, strategy, content, and project outcome outputs. Systematic inferences were made through the analysis in line with the data obtained. Comparisons and evaluations were made on approach information, objectives, analysis methods, technology and software used, active-passive and renewable energy systems, monitoring and tracking systems, and project output data obtained at the project's end to make the intervention's effects sustainable. As a result, a comprehensive approach model for energy-efficient retrofitting intervention approaches has been proposed in line with the conclusions obtained from the analysis, comparison, and evaluations of energy-efficient retrofitting of historic buildings. Thus, the approach model obtained with the study will guide the creation of intervention models for the studies to be carried out on energy-efficient retrofits in historical buildings.

Design of PV Battery Hybrid Inverter.

This research explores a hybrid renewable energy system integrating solar and additional renewable sources with energy storage for a resilient, eco-friendly power solution. Through adaptive control algorithms, the system autonomously optimizes energy flow based on environmental and grid conditions, ensuring uninterrupted power. Simulations under varying demand scenarios demonstrate enhanced reliability and a reduced carbon footprint. The findings highlight the system's potential as a sustainable model for future energy infrastructure.

The Recycling of Lithium from LiFePO4 Batteries into Li2CO3 and Its Use as a CO2 Absorber in Hydrogen Purification

The growing adoption of lithium iron phosphate (LiFePO4) batteries in electric vehicles (EVs) and renewable energy systems has intensified the need for sustainable management at the end of their life cycle. This study introduces an innovative method for recycling lithium from spent LiFePO4 batteries and repurposing the recovered lithium carbonate (Li2CO3) as a carbon dioxide (CO2) absorber. The recycling process involves dismantling battery packs, separating active materials, and chemically treating the cathode to extract lithium ions, which produces Li2CO3. The efficiency of lithium recovery is influenced by factors such as leaching temperature, acid concentration, and reaction time. Once recovered, Li2CO3 can be utilized for CO2 capture in hydrogen purification processes, reacting with CO2 to form lithium bicarbonate (LiHCO3). This reaction, which is highly effective in aqueous solutions, can be applied in industrial settings to mitigate greenhouse gas emissions. The LiHCO3 can then be thermally decomposed to regenerate Li2CO3, creating a cyclic and sustainable use of the material. This dual-purpose process not only addresses the environmental impact of LiFePO4 battery disposal but also contributes to CO2 reduction, aligning with global climate goals. Utilizing recycled Li2CO3 decreases the demand for virgin lithium extraction, supporting a circular economy. Furthermore, integrating Li2CO3-based CO2 capture systems into existing industrial infrastructure provides a scalable and cost-effective solution for lowering carbon footprints while securing a continuous supply of lithium for future battery production. Future research should focus on optimizing lithium recovery methods, improving the efficiency of CO2 capture, and exploring synergies with other waste management and carbon capture technologies. This comprehensive strategy underscores the potential of lithium recycling to address both resource conservation and environmental protection challenges.

Tuning the Morphology of Transition Metal Disulfides: Advances in Electrocatalysts for Hydrogen Evolution Reaction

The hydrogen evolution reaction (HER) in the renewable energy system has gained a lot of attention from researchers as hydrogen is assumed to be a clean and renewable carrier. Transition metals and their compounds have been used as promising alternatives to precious noble metals for the HER, offering low cost, more availability, and high activity. In this work, we discussed the mechanisms of the HER and how morphology influenced the catalytic performance of transition metal disulfide (TMD), focusing on structures that range from zero-dimensional (0D) to three-dimensional (3D) TMD materials. Notably, two-dimensional (2D) TMDs, like nanosheets, exhibit the lowest overpotential and a very small Tafel slope, which can be ascribed to their inherent layered structure and large surface area. According to recent research reports, the efficacy and efficiency of the HER process are influenced by surface chemistry, electrochemical characteristics, and the existence of active sites.

Techno-economic analysis of hybrid renewable energy systems for cost reduction and reliability improvement using dwarf mongoose optimization algorithm

The global energy crisis, particularly in isolated and remote regions, has increased interest in renewable energy sources (RESs) to meet growing energy demands. Integrating RESs with energy storage systems offers a promising solution to mitigate fluctuations and intermittency, but concerns about cost and reliability remain. This study explores the optimal design of various microgrid configurations, combining photovoltaic (PV), wind turbine (WT), battery energy storage system (BESS), and diesel generator (DG) systems for Najran city, Saudi Arabia, via real-world meteorological and load demand data. The Dwarf Mongoose Optimization Algorithm (DMOA), alongside the salp swarm algorithm (SSA) and whale optimization algorithm (WOA), was applied to minimize the levelized cost of energy (LCOE) while improving system reliability. The results demonstrate that the PV/BESS configuration, although cost-effective with an LCOE of 0.038 USD/kWh, fail to meet reliability constraints with a loss of power supply probability (LPSP) of 0.679. In contrast, the PV, WT, BESS, and DG configurations achieved an LPSP of 1.9 × 10^--8% with an LCOE of 0.199 USD/kWh, offering a robust and reliable solution for the region's energy needs. This paper presents a novel application of the DMOA for optimizing hybrid renewable energy systems, demonstrating its effectiveness in achieving a balance between cost and reliability. This strategy provides a viable approach for sustainable energy planning in similar regions facing energy challenges.

A Novel Development of Soft Computing based Hybrid Power Point Tracking Controllers for Hydrogen Vehicle Application with New Wide Source DC-DC Converter

From the present power generation scenario, most of the power production companies are focusing on renewable energy systems because their merits are easy to install, more reliable power sources, free from atmospheric pollution, and better adaptable to all weather conditions. In this article, a Polymer Electrolyte Membrane Fuel Cell (PEMFC) module is selected in the first objective to produce constant and continuous power to the hydrogen-based electrical vehicle systems. This fuel module provides fast power production and gives good energy density. However, the demerits of this module are more current production and low-level voltage generation. A new single-switch DC-DC circuit is introduced in the second objective of this work for optimizing the current levels of the fuel module thereby reducing the source power loss of the proposed system. Here, another problem of the fuel module is nonlinear power production which is linearized by proposing the Cuckoo Search Optimization (CSO)-based Adaptive Network-based Fuzzy Inference System (ANFIS) in the third objective to extract the maximum voltage from the fuel module. The merits of this introduced Maximum Power Point Tracking (MPPT) Controller are better tracking speed, low-level disturbances in the consumer load power, high robustness, more sustainability, and easy operation. The entire proposed system is investigated by selecting the MATLAB Simulink tool. The introduced converter circuit is analyzed by selecting the programmed DC supply.

Tying energy resiliance and digital upgradation of technology transformation of electric power system: Does financial flexibility matters?

As the energy sector undergoes rapid technological transformation, the resilience of electric power systems has become a focal point in the context of climate change and energy security. This paper examines the interplay between energy resilience and the digital upgradation of electric power systems in China, with a particular emphasis on the role of financial flexibility. Using panel data from 2005 to 2023 across 30 provinces in China, we employ the Generalized Method of Moments (GMM) model to investigate how financial flexibility—measured through capital access and adaptive financial strategies—affects the integration of digital technologies such as smart grids, renewable energy systems, and advanced monitoring infrastructures. Our findings demonstrate that financial flexibility significantly enhances the resilience of electric power systems by facilitating quicker adoption of digital technologies and enabling systems to better withstand external shocks, such as fluctuating energy demands and environmental stressors. The study offers policy insights, underscoring the importance of supportive financial mechanisms to accelerate the digital transformation and sustainability of China's energy infrastructure. This research contributes to the ongoing discourse on energy resilience by highlighting the critical role of financial flexibility in enabling technological advancements within the power sector.

Short‐term energy forecasting using deep neural networks: Prospects and challenges

AbstractThis study presents an in‐depth overview of deep neural networks (DNN) and their hybrid applications for short‐term energy forecasting (STEF). It examines DNN‐based STEF from three perspectives: basics, challenges, and prospects. The study compares recent literature using metrics like mean absolute error (MAE), mean average percentage error (MAPE), and root mean square error (RMSE). Findings indicate that combining automated data‐driven models with enhanced DNNs effectively addresses forecasting challenges. It also highlights the role of DNNs in integrating energy prosumers, renewable energy systems, microgrids, big data, and smart grids to improve STEF.

Performance analysis of hybrid off-grid renewable energy systems for sustainable rural electrification

Delivering sustainable power to rural communities in sub-Saharan Africa, particularly in Somalia, where many areas are far from the electrical grid and suffer from energy shortages, necessitates the deployment of appropriate technologies. This study evaluates the techno-economic and environmental viability of a hybrid renewable energy system (HRES) comprising a 15 kWp photovoltaic (PV) generator, 10 kW wind turbine (WT), 25 kW diesel generator (DG), and a 72-kWh battery energy storage system (BESS). The HRES is proposed to supply sustainable power to a rural community in Somalia. The techno-economic assessment of the proposed HRES and a comparative analysis of other configurations—namely the PV/WT/BESS and PV/DG/BESS systems is conducted using HOMER and MATLAB software. The results indicate that the proposed PV/WT/DG/BESS HRES demonstrates superior techno-economic performance compared to the other configurations. The lowest net present cost of $96,899.16 and the levelized cost of energy (LCOE) of $0.090/kWh were achieved. This system attains 25 % excess electricity, maintains a 0 % unmet electric load, and demonstrates robust environmental performance with a renewable penetration rate of 91.8 %. Approximately 53.34 % of greenhouse gas emissions are reduced compared to the PV/DG/BESS configuration. The study confirmed the significant impacts of all sensitivity parameters on operational costs, LCOE, fuel prices, fuel intake, and renewable fraction. The overall results indicate superior performance in the optimal system case, offering a feasible and suitable choice for the sustainable electrification of rural communities.

Salt Hydrates in Renewable Energy Systems: A Thorough Review

Salt Hydrates in Renewable Energy Systems: A Thorough Review

Design of a hybrid solar and biomass-based energy system integrated with near-zero energy building: Techno-environment investigation and multicriteria optimization

The current research aims to meet the energy needs of a group of residential buildings in Norway with the least amount of carbon dioxide emission and the greatest amount of renewable energy. The supply side based on the renewable renewable-based energy system is planned and scaled using the real-time data use of domestic hot water (DHW), heating and electricity necessary for the buildings. PVT panels are used in the hybrid solar and biomass-based energy systems to produce both the DHW requirements and the electricity production. The digester is used with the heat pump, which generates heat. A double-effect absorption refrigeration system is also utilized to provide the necessary cooling requirements. On the supply side, the management of the heat streams and the redirection of flows are done using a rule-based regulating system. The whole plant's size is supplied, and the dynamic energy simulation is run. The primary deciding criteria for heating the buildings are the costs of electricity and biomass. The whole system is then optimized depending on operating circumstances, and the outcomes are compared to the design point. PVT may be used to create more than 80% of the yearly DHW. Furthermore, summertime radiation accounts for 64.8% of cooling output since it is more intense and may be converted into cooling energy. Digester/CC also contributes 66.55% of the building's heating, showing that the designers should rely on biomass as wintertime energy costs are higher. The parametric study demonstrates that increasing PVT time and tank capacity has varied effects on efficiency and emissions. Also, On winter days, there was a significant drop in renewable energy generation from summer to autumn, from 82.7 MWh to 28.52 MWh. The optimization results show that at the TOPSIS point, the total cost, efficiency, and emission index are 9.73 $/hr, 36.8%, and 7.75kg/MWh, respectively.

Enhanced thermochemical heat storage performance of CaO/CaCO3 via pyroligneous acid impregnation and Co/Mn co-doping

Calcium-based thermochemical heat storage (TCHS) is an economical and environmentally friendly technology for efficient heat storage. It can strengthen the flexibility in power systems of renewable energy and promote the recovery and storage of waste heat in energy-intensive industries. However, CaO/CaCO3 is extremely prone to sintering at operational temperatures. Consequently, a cost-effective approach was proposed to synthesize calcium-based TCHS materials modified by pyroligneous acid (PA) impregnation and co-doping with dual transition metals. The heat storage performance, physicochemical property, and anti-sintering mechanism of synthesized CaO were comparatively examined. The sample prepared with a molar ratio of Ca: Co: Mn = 100:3:7 (PACa-Co3Mn7) exhibited an initial energy storage density of 1.76 MJ/kg, which gradually rose to 1.88 MJ/kg. After 20 cycles, the value decreased by only 4.39 % from its peak, indicating outstanding TCHS performance. Characterization results indicated that the specific surface area and pore volume of PACa-Co3Mn7 were 10.48 m2/g and 0.035 cm3/g, which were 2.34 and 2.69 times those of CaO stemmed from the calcination of limestone, respectively. The fruitful pores provided pathways for CO2 diffusion within the CaO particles or CaCO3 product layer. The uniformly distributed Co and Mn elements combined to form Ca3CoMnO6. Ca3CoMnO6 could serve as the inert carrier that mitigated the grain-growth of CaO, thereby stabilizing the pore structure and resisting the sintering of PACa-Co3Mn7. Furthermore, density functional theory (DFT) calculations demonstrated that the free Mn and Co elements efficiently promoted the electrons transfer between CaO and CO2, which improved the reactivity of PACa-Co3Mn7. Therefore, CaO modified by PA impregnation and co-doping with dual transition metal is a promising candidate for the TCHS system.

Feasibility Assessment of Using Wavestar Energy Converter in a Grid-Connected Hybrid Renewable Energy System (a case study)

Renewable energies, as a sustainable alternative to fossil fuels, confront a twofold challenge characterized by intermittency and the imperative to enhance reliability. Hybrid energy systems (HES) emerge as a pragmatic solution with the potential to mitigate carbon emissions and foster self-sufficiency within local communities. This investigation primarily seeks to ascertain the optimal configuration of a HES integrated with Wavestar wave energy converter, considering economic, technical, and environmental factors, tailored to meet the electricity demands of two cities in Iran including Chabahar and Anzali alongside of the Caspian sea and Oman sea, respectively. For this purpose, HOMER software is used for modeling and optimization the energy systems. In both locations, the optimal system includes photovoltaic (PV), wind turbine (WT), Wavestar wave energy converter (WEC), diesel generator (DG), and batteries which results in cost of energy (COE) of 0.136 and 0.109 in Chabahar and Anzali, respectively. Sensitivity analysis reveals that wind speed significantly impacts COE and reliability, also grid electricity purchases play a vital role. Economic uncertainty highlights varying importance between capital costs for PV and WT in Anzali and Chabahar. Furthermore, this study delves into the limitations posed by the fuel dependency of diesel generators. Finally, by conducting a thorough assessment of solar energy potential by GIS software, the research identifies a favorable location for the establishment of a solar power plant, contributing to the overall feasibility of the proposed hybrid energy systems.

Hybrid renewable energy systems for sustainable power supply in remote location: Techno-economic and environmental assessment

Electricity supply is inconsistent and unreliable in many remote areas of India, where depending solely on a single renewable energy source is impractical. In this context, this study investigates the potential of off-grid hybrid renewable energy systems (HRES) to meet the energy needs of a village community in India. Techno-economic analysis and life cycle assessment have been employed to compare eleven HRES combinations which combine photovoltaic (PV), wind turbine (WT), battery (BAT), diesel generator (DG), biogas generator (BG), converter (CONV), and electrolyser (ELEC). By optimising the size and capacity of each component in HRES, this study aims to identify the combination with the lowest levelised cost of electricity (LCOE). This research aligns with United Nations Sustainable Development Goal No. 7 to seek “Affordable and Clean Energy”. The findings highlight that HRES comprising PV/WT/BAT/CONV/DG exhibits the lowest LCOE (0.319 $/kWh) and net present cost (6.81 M$) among all combinations. In systems with partial reliance on diesel, integrating both PV and WT could reduce diesel consumption and increase the renewable fraction to 87.4 %. For HRES involving PV, a significant contribution to greenhouse gas emissions occurs during the construction stage. The WT/DG combination, with its high diesel dependency, has the largest global warming potential. The efforts from this study provide valuable insights into determining the optimal HRES for remote communities by considering their economic and environmental factors.

Performance response analysis and optimization for integrated renewable energy systems using biomass and heat pumps: a multi-objective approach

The focus of this study is to optimize the exploration of biomass-driven multi-energy systems, which include combined heat, power, and gas generation. The objective is to enhance the thermal, environmental, and economic performance indicators of the system. The optimization objectives encompass the quantities of internal combustion engines and air source heat pumps, as well as the dimensions of tanks utilized for anaerobic fermentation. A mathematical model was developed to optimize multiple objectives for combined heat, power, and gas generation systems by employing multi-objective intelligent optimization algorithms. The validation and analysis were conducted using rural residences in Lanzhou, Gansu Province, China, as a case study. The sensitivity analysis of biomass gasification combined heat and power systems was conducted from both technical and cost perspectives, examining the dynamic impact characteristics on the outcomes of multi-objective optimization. The findings indicate that the annual energy-saving rate of the optimized combined generation system decreased from 3.62% to -6.78%, while the growth in carbon emissions reduction rate increased from 76.05 to 81.38%, and the annual cost-saving rate grew from 0.97 to 14.96%. The power generation efficiency of the cogeneration station and hydraulic retention time were found to have a significant impact on the multi-objective optimization results of the combined generation system among the technical parameters. The unit cost of anaerobic fermentation tanks had a more significant impact on the multi-objective optimization results in terms of cost parameters, compared to the price of biogas residue.

Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification

Developing hybrid renewable energy systems (HRES) is crucial for ensuring affordable, sustainable, and reliable energy access in remote rural and island regions. Rich and detailed data play a pivotal role in the optimal design of HRES. However, remote areas often face data limitations due to inadequate metering infrastructure, which further increases uncertainties in HRES design. This paper proposes a planning optimization method that quantifies multiple uncertainties, requiring only limited information for the optimal HRES design. First, uncertainties in HRES planning are classified into different types based on intrinsic randomness, data availability, and impact level. Then, by integrating uncertainty quantification with credibility theory, knowledge-based scenario generation models are developed to leverage limited available information to generate extreme and typical operating conditions for a tailored HRES design. Finally, a fuzzy credibility-constrained stochastic-robust optimization model is proposed to optimize the design of HRES. A practical case facing significant data scarcity and gaps is used to validate the effectiveness of the proposed method. The proposed approach reduces the loss of load probability for HRES to 0.02% and lowers the levelized cost of energy to $0.16/kWh—33% lower than that of the deterministic method and 79% lower than that of the traditional stochastic method.

Development of a Large-Scale Integrated Solar-Biomass Thermal Facility for Green Production of Useful Outputs

The present paper develops a new multigeneration plant to produce multiple commodities from two combined renewable energy sources, solar thermal and biomass and considers a specific case study administered for the city of Al Lith in the Kingdom of Saudi Arabia. The plant generates power, heating, refrigeration, hydrogen, chlorine, concentrated sodium hydroxide, ammonia, urea, and fresh water, which are commodities at high demand in the area. The energy efficiency is determined to be 53% with an annual generation of over 1036 GWh of power and cogenerated 858 GWh of heating, nearly 23 GWh of refrigeration effect, over 11,300 tons of ammonia, almost 1800 tons of urea, over 113,000 tons of concentrated sodium hydroxide and over 905,000 m3 of fresh water. The exergy contents of heating, refrigeration, power and commodity products represent a total of 45% of the sources, which leads to a multigeneration platform's exergy efficiency. The system includes an integrated biomass gasification combined cycle with a biomass oxy-gasifier. The Aspen Plus simulations of the oxy-gasifier determined that the oxygen-to-biomass weight fraction should be set to 0.15, whereas the steam-to-biomass weight fraction is around 0.1. The exhaust gas recirculation is applied to enhance power generation rate and efficiency. The recirculation ratio of exhaust gas is found to be 0.21 if power generation efficiency is to be maximized and 0.28 if the power generation rate is to be maximized. The fluctuating and intermittent nature of the solar energy resource causes poor economics when this energy is to be captured in isolation or itself only. The current paper demonstrates that the hybridization of solar and biomass energy together with integrated processes for multiproduct generation enhances the overall competitivity of the renewable energy system. To address this aspect, the objective of the paper is to develop and assess a new integrated flowsheet for hybrid renewable resource multigeneration.

Optimization Scheduling of Off-grid Hybrid Renewable Energy Systems Based on Dung Beetle Optimizer with Convergence Factor and Mathematical Spiral

With the rapid development of renewable energy and the increasing modernization demands in remote areas, off-grid hybrid renewable energy systems (HRES) have become a key technology for achieving sustainable development. This paper presents an improved Dung Beetle Optimization (DBO) algorithm that enhances step size by introducing six elementary functions as convergence factors. It combines polar coordinate expressions of three different mathematical spirals, multiplied by a zeroing factor related to the number of iterations, resulting in six distinct mathematical images that optimize the algorithm's dancing path, thereby enhancing global search capability. Experiments on the CEC2022 test functions demonstrate improved optimization performance of the algorithm. Furthermore, the algorithm is applied to the optimization design of off-grid HRES, integrating configurations such as photovoltaic panels, wind turbines, biomass generators and various battery types (Lead Acid battery/Lithium-Ion/Nickel-Iron), with lifecycle cost as the objective function while assessing energy costs. The results indicate that the nickel-iron battery system optimized by the improved DBO algorithm achieves the lowest lifecycle cost ($961,139) and energy cost ($0.3607/kWh), requiring a total of 1,329 PV panels, no wind turbines, and 268 nickel-iron battery units.

Current-Day and Future Dunkelflaute Risks for Belgium

Abstract Dunkelflautes, events of low renewable production and potentially high demand, are the most extreme examples of the susceptibility of a renewable energy system with respect to weather variability. Yet, these events currently lack a precise definition in the literature. Based on 41 years of weather data, we explore the resilience of the Belgian energy system with respect to the duration and extremeness of Dunkelflautes or energy drought. Although the hourly average load cannot be covered 89% of the time in our analysis, we find that Dunkelflaute occurrences are generally independent of the energy mix between photovoltaic (PV) panels and wind energy (WE) production (for fractions between 10% and 60% of PV). However, to cope with Dunkelflautes, a system with full PV or full WE provision is very ineffective. While the optimal mix is found to be independent of Dunkelflaute extremeness, it strongly depends on the Dunkelflaute duration: For subdaily or longer than two-daily events, a high WE fraction is optimal, while a high PV fraction is needed for durations of the order of days. More than 56% of Dunkelflautes over Belgium coincide with those in the surrounding countries. Finally, as opposed to weak changes in the climatological average, future climate projections reveal an increase in Dunkelflaute severity, mainly due to a reduction in WE production.

Stability Improvement of Hybrid Renewable Energy Systems by Using Virtual Inertia Controller Based on Optimized FOPID with Harris Hawk Optimization

Stability Improvement of Hybrid Renewable Energy Systems by Using Virtual Inertia Controller Based on Optimized FOPID with Harris Hawk Optimization