Off-grid Hybrid Renewable Energy System Research Articles

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.

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.

Multi-objective optimal sizing and techno-economic analysis of on- and off-grid hybrid renewable energy systems for EV charging stations

Integrating electric vehicle charging stations (EVCSs) with renewable energy systems requires the consideration of several factors during the planning stage, including environmental impact, economic viability, grid reliability, and self-sufficiency. Therefore, this study conducts a multi-objective optimal sizing of on- and off-grid hybrid renewable energy systems for EVCSs. The sizing problem is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II). Subsequently, the best suitable solutions from the obtained non-dominated solutions are selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, prioritizing the objective functions based on diverse interests of different stakeholders (large and small private investors and governmental entities). Finally, a techno-economic analysis is made considering payback period, profitability index (PI), and internal rate of return (IRR). The results show that on-grid systems show high economic viability with payback periods between 1.98 and 7.72 years, an average PI of 5.07 and an average IRR of 23.97%. Although off-grid systems present lower economic viability with payback periods between 8.77 and 22.42 years, an average PI of 1.68 and an average IRR of 4.91%, in certain cases they reach investable levels with payback periods below 10 years, PI above 2, and IRR above the interest rate.

A multiscale approach to optimize off-grid hybrid renewable energy systems for sustainable rural electrification: Economic evaluation and design

This article thoroughly investigates the design and optimization of an off-grid hybrid renewable energy system for a remote town in the province of Ankara, whose traditional power infrastructure is lacking. The goal is to provide an efficient and cost-effective energy system that can supply the village's power needs indefinitely. The optimization process entails selecting the best mix of renewable energy sources and sizing components to obtain the best economic and technical performance. To handle the complexity of the optimization problem, the Nelder-Mead simplex search method is used, taking into account the stochastic nature of renewable energy generation and the nonlinear features of RES-based power plants. The simulation results show that the suggested hybrid system outperforms traditional diesel power generators in terms of economic viability and environmental sustainability. The system assures consistent power supply by using reserve energy devices such as batteries, thereby minimizing the intermittent nature of renewable sources. With a competitive energy cost of €0.63/kWh, the optimized hybrid system ensures a dependable and continuous power supply, fulfilling the village's electrical requirement for an amazing 16 years.

Modified Harris Hawks optimization for the 3E feasibility assessment of a hybrid renewable energy system

The off-grid Hybrid Renewable Energy Systems (HRES) demonstrate great potential to be sustainable and economically feasible options to meet the growing energy needs and counter the depletion of conventional energy sources. Therefore, it is crucial to optimize the size of HRES components to assess system cost and dependability. This paper presents the optimal sizing of HRES to provide a very cost-effective and efficient solution for supplying power to a rural region. This study develops a PV-Wind-Battery-DG system with an objective of 3E analysis which includes Energy, Economic, and Environmental CO2 emissions. Indispensable parameters like technical parameters (Loss of Power Supply Probability, Renewable factor, PV fraction, and Wind fraction) and social factor (Human Developing Index) are evaluated to show the proposed modified Harris Hawks Optimization (mHHO) algorithm’s merits over the existing algorithms. To achieve the objectives, the proposed mHHO algorithm uses nine distinct operators to obtain simultaneous optimization. Furthermore, the performance of mHHO is evaluated by using the CEC 2019 test suite and the most optimal mHHO is chosen for sizing and 3E analysis of HRES. The findings demonstrate that the mHHO has achieved optimized values for Cost of Energy (COE), Net Present Cost (NPC), and Annualized System Cost (ASC) with the lowest values being 0.14130 $/kWh, 1,649,900$, and 1,16,090$/year respectively. The reduction in COE value using the proposed mHHO approach is 0.49% in comparison with most of the other MH-algorithms. Additionally, the system primarily relies on renewable sources, with diesel usage accounting for only 0.03% of power generation. Overall, this study effectively addresses the challenge of performing a 3E analysis with mHHO algorithm which exhibits excellent convergence and is capable of producing high-quality outcomes in the design of HRES. The mHHO algorithm attains optimal economic efficiency while simultaneously minimizing the impact on the environment and maintaining a high human development index.

AN EFFICIENT STUDY OF PV/WIND/BATTERY/ELECTROLYZER/H2-TANK/FC FOR A REMOTE AREA ELECTRIFICATION

With the rapid development of the use of renewable energy systems, it is becoming more and more important to combine different sources into hybrid renewable energy systems. Many parameters in hybrid renewable energy systems must be optimized to effectively size hybrid system components to achieve economic, technical, and design goals practically. This paper focuses on the optimal configuration of off-grid hybrid renewable energy systems (HRES). The system consists of a photovoltaic (PV), wind turbine (WT) and battery bank (BB), fuel cell (FC) with hydrogen tank (H2-tank), and electrolyzer (Elect). The optimal size of the proposed HRES component is achieved using a novel meta-heuristic technique called the whale optimization algorithm (WOA). WOA improves the optimal configuration of HRES to produce the best minimum value of the fitness function, which converges to the global optimal solution after several iterations. The proposed WOA is used to solve the multi-objective optimization problem of the cost of energy (COE) in $/kWh and the total net present cost (TNPC) in $. Two recent algorithms, particle swarm optimization (PSO) and gray wolf optimizer (GWO), have also been implemented in this work to demonstrate the effectiveness of the proposed algorithm.

Optimization of off-grid hybrid renewable energy systems for cost-effective and reliable power supply in Gaita Selassie Ethiopia

This paper explores scenarios for powering rural areas in Gaita Selassie with renewable energy plants, aiming to reduce system costs by optimizing component numbers to meet energy demands. Various scenarios, such as combining solar photovoltaic (PV) with pumped hydro-energy storage (PHES), utilizing wind energy with PHES, and integrating a hybrid system of PV, wind, and PHES, have been evaluated based on diverse criteria, encompassing financial aspects and reliability. To achieve the results, meta-heuristics such as the Multiobjective Gray wolf optimization algorithm (MOGWO) and Multiobjective Grasshopper optimization algorithm (MOGOA) were applied using MATLAB software. Moreover, optimal component sizing has been investigated utilizing real-time assessment data and meteorological data from Gaita Sillasie, Ethiopia. Metaheuristic optimization techniques were employed to pinpoint the most favorable loss of power supply probability (LPSP) with the least cost of energy (COE) and total life cycle cost (TLCC) for the hybrid system, all while meeting operational requirements in various scenarios. The Multi-Objective Grey Wolf Optimization (MOGWO) technique outperformed the Multi-Objective Grasshopper Optimization Algorithm (MOGOA) in optimizing the problem, as suggested by the results. Furthermore, based on MOGWO findings, the hybrid solar PV-Wind-PHES system demonstrated the lowest COE (0.126€/kWh) and TLCC (€6,897,300), along with optimal satisfaction of the village's energy demand and LPSP value. In the PV-Wind-PHSS scenario, the TLCC and COE are 38%, 18%, 2%, and 1.5% lower than those for the Wind-PHS and PV-PHSS scenarios at LPSP 0%, according to MOGWO results. Overall, this research contributes valuable insights into the design and implementation of sustainable energy solutions for remote communities, paving the way for enhanced energy access and environmental sustainability.

On–off-Grid Optimal Hybrid Renewable Energy Systems for House Units in Iraq

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement.

Enhancing Off-Grid Hybrid Renewable Energy System

Enhancing Off-Grid Hybrid Renewable Energy System

Multi-objective optimization and long-term performance evaluation of a hybrid solar-hydrogen energy system with retired electric vehicle batteries for off-grid power and heat supply

This paper presents a novel off-grid hybrid renewable energy system integrated with hydrogen production and retired electric vehicle (EV) batteries for combined power and heat supply to a small rural community. The system consists of photovoltaic (PV) panels, evacuated tube solar collectors, a proton exchange membrane fuel cell (PEMFC), an alkaline electrolyzer, compressed hydrogen storage tanks, and reused lithium-ion batteries from EVs. A new battery model is developed in the Transient System Simulation Program (TRNSYS) to capture the capacity degradation of retired batteries. A two-stage energy management strategy is proposed to regulate power flow and maximize solar energy utilization. The system is optimized for minimum power supply disruption, hot water supply disruption, energy waste, and annualized costs over a 20-year lifetime using a multi-objective NSGA-II algorithm coupling MATLAB and TRNSYS. Optimization results reveal tradeoffs between the competing objectives. Dynamic simulations show the water tank temperature fluctuates between 20 and 100 °C with mean values dropping slightly in later years due to battery degradation. Energy waste from components rises in later years for the same reason. The replacement interval for a retired EV battery module is around 2.5 years. The integrated system proves feasible for off-grid combined power and heat supply using solar energy and retired EV batteries as storage, though battery degradation impacts long-term performance.

Optimal Sizing and Techno-Economic Analysis of a Hybrid Power System for Postville

Providing reliable and sustainable electricity to remote communities poses a significant challenge. Techno-economic feasibility of an off-grid hybrid renewable energy system for Postville, a remote Northern Labrador, Canada community, is presented in this paper. The study integrates solar photovoltaic panels, wind turbines, battery storage, and diesel generators into a hybrid system, analyzing various components and optimizing using advanced Homer Pro software. Simulation results demonstrate that the most optimized hybrid structure ensures a stable power supply while minimizing diesel generator operation, reducing fuel consumption. Economically, this system offers substantial cost savings, alleviating the financial burden on the community. The designed system consists of 435 kW PV, 500 kW wind turbine, 455 kW diesel generator, and 815 kWh batteries. The proposed system will generate power with a net present cost of $5.57 million. This research also contributes to the broader goal of creating sustainable energy solutions and improving the quality of life in remote communities.

Technoeconomic, environmental and multi criteria decision making investigations for optimisation of off-grid hybrid renewable energy system with green hydrogen production

The current study presents a comprehensive investigation of various energy system configurations for a remote village community in India with entirely renewable electricity. Excess electricity generated by the systems has been stored using two types of energy storage options: lithium-ion batteries and green hydrogen production through the electrolysers. The hybrid renewable energy system (HRES) configurations have been sized by minimising the levelised cost of energy (LCOE). In order to identify the best-performing HRES configuration, economic and environmental performance indicators has been analysed using the multi-criteria decision-making method (MCDM), TOPSIS. Among the evaluated system configurations, system-1 with a photovoltaic panel (PV) size of 310.24 kW, a wind turbine (WT) size of 690 kW, a biogas generator (BG) size of 100 kW, a battery (BAT) size of 174 kWh, an electrolyser (ELEC) size of 150 kW, a hydrogen tank (HT) size of 120 kg, and a converter (CONV) size of 106.24 kW has been found to be the best-performing system since it provides the highest relative closeness (RC) value (∼0.817) and also has the lowest fuel consumption rate of 2.31 kg/kWh. However, system-6 shows the highest amount of CO2 (143.97 kg/year) among all the studied system configurations. Furthermore, a detailed technical, economic, and environmental analysis has been conducted on the optimal HRES configuration. The minimum net present cost (NPC), LCOE, and cost of hydrogen (COH) for system 1 has been estimated to be $1,960,584, $0.44/kWh, and $22.3/kg, respectively.

Evaluating the impact of industrial loads on the performance of solar PV/diesel hybrid renewable energy systems for rural electrification in Ghana

Access to reliable electricity remains a significant challenge in many rural communities worldwide. Off-grid solar PV hybrid renewable energy systems (HRES) have emerged as a viable option for rural electrification. However, rural communities' lack of productive load often limits their effectiveness. This study aimed to assess the impact of agro-processing productive loads on the performance of off-grid solar PV HRES for rural electrification. Hybrid Optimization Multiple Energy Resource (HOMER) software was used to perform a techno-economic analysis of a solar PV/diesel HRES. The study findings showed improvement in the rural community's load factor and solar load correlation with the integration of the productive load. Subsequently, increasing the renewable energy fraction in solar PV/diesel HRES reduces the levelized cost of energy (LCOE), making electricity generation more cost-effective for rural electrification in Ghana. Comparatively, the improved LCOE was found to be substantially higher than the End User Tariff of all residential consumers on the national grid, even under high PV penetration and full capital cost subsidy cases. The study provides valuable insights into the role of agro-based productive loads in enhancing the performance of rural off-grid solar HRES.

Evaluation of stand-alone hybrid renewable energy system with excess electricity minimizer predictive dispatch strategy

The prioritization of economic and reliability objectives in the optimization of stand-alone microgrids and off-grid hybrid renewable energy systems (HRES) has led to optimum systems with high excess electricity and low self-consumption indexes. Managing surplus power after charging the storage bank without imposing a negative impact on energy cost (COE) and environmental factors is a challenge for off-grid applications. In recent years the development of predictive dispatch strategies (PD), improves the energy efficiency in HRES compared to conventional dispatches such as load following (LF). However, the mismatch between renewable power production and demand profiles prohibits high excess electricity reduction. In this study, a novel dispatch strategy, entitled modified predictive dispatch (MPD), is developed by integrating a proactive approach to charging/discharging the battery bank and demand-side management (DSM) based on the upcoming short-term excess electricity profile. The results showed that with the participation of an average of less than 20 % deferrable components and the possibility of load shifting for less than 3 h, the excess electricity can be reduced to about 7.5 %, compared to 41 % and 18.5 % for LF and PD strategies, respectively. Furthermore, the self-utilization index of surplus power improved from less than 25 % to about 90 %. These improvements were achieved through the MPD strategy, which reduced COE by more than 10 %, reaching about 0.12 $/kWh without any significant effect on emission factors. The sensitivity analysis indicated that achieving an excess electricity self-utilization index of over 80 % requires a load-shifting possibility of more than 2 h and a deferrable load participation of about 10 % in the DSM approach. Therefore, results approved the effectiveness of the proposed dispatch strategy in high renewable penetration systems, even with low levels of participation by power consumers.

MPPT DC-DC Buck-Boost Converter for Off Grid Hybrid Solar-Wind-Battery System in Ikuza Island, Tanzania

Ikuza Island in Tanzania faces lack of electricity. Therefore, this paper undertakes to design hybrid renewable energy sources for the island by specifically focusing on the buck-boost converter for the energy conversion from these renewable resources. The design of the bidirectional buck-boost converter for maximum power point tracking in off-grid hybrid renewable energy systems is multifaceted due to the inhomogeneity nature of the renewable energy sources. The bidirectional buck-boost converter, solar PV, wind-based generator, and energy storage system were designed and simulated in MATLAB/Simulink software. The designed system was tested with varying solar irradiance (750 to 1000 W/m2), temperature (20 to 25°C) and wind speed (150 to 157.5 radians/s) at constant load of 260 A while load variation involved varying the load current from 0 to 260 A at solar irradiance, temperature, and wind speed of 1000 W/m2, 25 °C and 157.5 radians/s, respectively. The variation of DC link bus voltage at different load conditions was reported. The simulation results show that the designed converter is able to maintain DC link voltage at 600 V. Moreover, the DC link voltage showed a maximum drop of approximately 0.67% during the constant load condition. Contrarily, a significant improvement is observed when the designed converter operates with the hybrid system of solar PV, PMSG-based wind generator and with energy storage system.

Optimum Design, Socioenvironmental Impact, and Exergy Analysis of a Solar and Rice Husk-Based Off-Grid Hybrid Renewable Energy System

This study examines the optimal sizing of an off-grid hybrid system comprising solar photovoltaic (PV), rice husk-based biomass, and lead-acid battery for meeting the electric demand of a rural community. Considering a selected remote village in Bangladesh as a case study, the proposed optimized system is primarily compared with the diesel generator and the micro gas turbine (MGT)-based options in techno-economic and environmental terms. The potential social benefits, such as the employment creation and the improvement in the human development index in the locality, have been investigated in this study. Moreover, the impacts of operational greenhouse gas emissions on the human health damage and the surrounding ecosystem have been examined. Additionally, an exergy analysis of the hybrid system and the components has been carried out. Results indicate that in addition to being the environmentally preferable option, the proposed PV/biomass/battery system offers a lower cost of energy of 0.314 $/kWh compared to the MGT-based system (0.377 $/kWh). Although the diesel-based system offers a marginally better economy (9.55% less energy cost), it comes with the expense of probable damages to human health and the ecosystem worth of $15,211 and $6,608, respectively, making biomass the best option with no such damages. Exergy analysis reveals higher loss from PV than biomass and 13.09% system exergy efficiency. The assessment of the social indicators testifies to the potential of promoting the human development index from its current value and the formation of 1.41 jobs to as high as 15.15 full-time permanent jobs with the installation of hybrid systems in the community.

Prioritization of Off-Grid Hybrid Renewable Energy Systems for Residential Communities in China Considering Public Participation with Basic Uncertain Linguistic Information

In recent years, the adoption of Hybrid Renewable Energy Systems (HRESs) is rapidly increasing globally due to their economic and environmental benefits. In order to ensure the smooth implementation of HRESs, it is important to systematically capture societal preferences. However, few studies focus on the effective integration of public opinion into energy planning decisions. In this study, a decision-making approach for public participation in HRES planning is proposed to optimize the configuration of off-grid HRESs. First, an HRES evaluation index system considering public participation was constructed; to address the situation where the public from different backgrounds may have limited and inconsistent understanding of indicators, the basic uncertain linguistic information (BULI) is introduced to express evaluations and associated reliability levels. The indicator weights were then determined through the evaluation of both the public and the expert opinions. Second, the BULI-EDAS decision approach was developed by extending the EDAS method to the BULI environment to optimize HRES planning. Finally, the proposed model was applied to identify the optimal configuration in rural China. The comparative analysis results show that the proposed method can avoid misunderstandings and facilitate realistic public judgments. The selected optimal plan has a standardized energy price of 0.126 USD/kWh and generates 45,305 kg CO2/year, resulting in the best overall performance. The proposed HRES planning method provides a practical approach for decision makers to conduct HRES planning in a public participation environment to promote clean energy transitions.

Reliability index based optimal sizing and statistical performance analysis of stand-alone hybrid renewable energy system using metaheuristic algorithms

Integration of renewable energy systems can provide reliable, environmentally sustainable, and cost-effective alternatives for meeting the demand for electricity in remote locations. In this study, recently developed meta-heuristic techniques are explored to find the optimal design for two combinations of off-grid hybrid renewable energy systems. To evaluate the performance, the Tasmanian devil Optimization (TDO) was compared to three meta-heuristic algorithms, called the COOT bird optimization algorithm (COOT), the Grey wolf algorithm (GWO), and the Beluga whale optimization (BWO), and determined the optimal design of the proposed off-grid energy system in terms of best and worst-case solutions. The system consisting of a solar-battery is more cost-effective, with the lowest total annual cost (TAC) of 36,859 $ and the lowest levelized cost of electricity (LCOE) of 0.0930 $/kWh for 0% LPSPmax level as compared to the wind turbine-battery-diesel generator with the highest TAC (102580 $) and LCOE (0.2589 $/kWh). Hence, a solar-battery hybrid system is more viable for producing clean energy with effective storage and better power system reliability enhancement. Also, the obtained simulation results reveal the supremacy of the TDO compared to the other three meta-heuristic algorithms, where it achieved the optimal solution with a quick convergence time and fewer oscillations.

Analysis of Optimal Load Management Using a Stand-Alone Hybrid AC/DC Microgrid System

Typically, diesel or other fossil fuel-based related applications meet electricity demand. Nonetheless, as the cost of fossil fuels rises, as do their harmful emissions, there is a sudden transition toward stand-alone hybrid renewable energy systems (HRESs). The proposed project proposes electrifying VIT University in Vellore, Tamil Nadu, India, using an off-grid HRES. The goal of enhancing hybrid energy system (HES) regulation, size, and component selection is to provide society with a cost-effective power supply. This article’s primary purpose is to show how to utilize HOMER Pro Software to reduce total net present cost, cost of energy, and CO2 emissions. After that, the findings were compared to four different HRES configurations. The efficient solution for transmitting power at the lowest energy cost is configuration 1 (solar + fuel cell + battery + wind + diesel generator) which is found to be the optimal solution for supplying energy with 0% unmet load at the least cost of energy, which is at 24.91 Rs/kWh. These data are used to calculate the optimal size of energy storage components based on long-term system behavior using HOMER and to forecast short-term generation and demand changes while maintaining system dependability and grid voltage. Using and incorporating model predictive control (MPC) for an interlinking converter (ILC), the proposed HRES design is validated for the study area in a novel way that sequentially applies HOMER and MATLAB simulations.

Off-Grid Hybrid Renewable Energy System Operation in Different Scenarios for Household Consumers

Off-grid hybrid renewable energy systems represent the most modern and flexible solutions that can cover a wide range of energy efficiency needs for household consumers. In the current context, these systems must be taken into account by most household consumers, given the fact that the price of energy has increased. This paper proposes an experimental analysis of the behavior of such a system, in real operating conditions, considering two renewable energy sources, wind and photovoltaic sources, using an experimental stand. It can be considered a testing platform for hybrid energy production systems, in that the power installed in the two sources can be scaled up. The platform has the advantage of allowing the implementation of different load and wind curves through a programmable logic controller; in this way, it is possible to evaluate the degree of coverage of the energy consumption produced from renewable sources, in the north-east of Romania, in the Suceava County region. The experimental study also involves an analysis of the storage capacity in relation to the consumption and the electricity produced by the two renewable sources. In this regard, three scenarios differentiated by the state of charge (30%, 50% and 70%) have been established. The results indicate that, for each of the imposed scenarios, the energy required to cover consumption is produced by renewable energy sources (42%, 47% and 53%), to which the energy stored in batteries (39%, 28% and 18%) is added.