Hybrid Energy System Research Articles

Optimization of the power output scheduling of a renewables-based hybrid power station using MILP approach: The case of Tilos island

Hybrid energy systems comprising renewables (mainly wind and solar) and storage systems are increasingly welcome to serve small communities or areas, such as small islands. In particular, the present study deals with the hybrid power station of Tilos, a little island located in the Greek Dodecanese, which includes a 800 kW wind turbine, a 160kWp PV field, and a 2.88 MWh NaNiCl2 battery; the system is also connected to the Kos-Kalymnos electrical network via a submarine cable. Currently, it is used to export its whole energy production under the management of the Greek company Eunice Energy Group. The agreement with the grid regulator is conceived to involve a remuneration for the energy output in three power levels (0 kW, 200 kW, 400 kW), with hourly dispatch provided the day before. Economic penalties will be applied in the near future for failure to respect power levels, whether in the form of excess or deficiency. This must be done in accordance with the available power to avoid surpluses or deficits, as well as excessive curtailment of renewable energy. In this work, a way to optimize energy fluxes of the island is proposed to better exploit the potential revenue, without excessively resorting to curtailments. The optimizations are performed in a Python environment through the “Gurobi” optimization solver, which is based on Mixed Integer Linear Programming (MILP). Scheduling emerges as a result of a rolling horizon approach. The new scheduling method reveals that there is potential for an increase in exported energy by 87.1% and potentially doubles the earnings over the current operation. Furthermore, novel scenarios are proposed to explore how different agreements with the grid operator would shift the optimal solution. Compared to an ideal optimized control under the current restrictions, a scenario that introduces the possibility of shutting down the wind turbine may increase the annual earnings by 10%, while a scenario that introduces a higher power band has the potential to increase annual earnings by 29.1%.

Hybrid energy storage system and management strategy for motor drive with high torque overload

The demand for small-size motors with large output torque in fields such as mobile robotics is increasing, necessitating mobile power systems with greater output power and current within a specific volume and weight. However, conventional mobile power sources like lithium batteries face challenges in surpassing the dual limitations of weight and output power due to constraints imposed by materials and other factors. Therefore, this paper references the approach of high-power hybrid energy systems in automobiles and proposes a battery–supercapacitor hybrid energy storage system (BSHESS) and energy management strategy. The motor is powered by the battery during low torque operating conditions, while the additional output power of the battery is used to charge the supercapacitor. In cases of torque overload, the rapid discharge of the supercapacitor provides the motor with a high current, ensuring instantaneous high output power. Furthermore, the proposed energy management strategy is used to control the charging and discharging processes of the supercapacitor, guaranteeing that the charging process of the supercapacitor does not interfere with the battery’s power supply to the motor, as well as maintaining controllability and stability of the current in the discharge process. The feasibility of the principle is verified through simulations, and we also design a complete prototype of the proposed BSHESS and conduct experiments on the motor. The results demonstrate that the maximum output current to the motor is increased by 150% compared to the original level, and the weight is reduced by 64.7% compared to a pure battery-powered system with same maximum current output. Additionally, the energy management strategy enables a more stable charging and discharging process compared to the unmanaged state.

Techno-economic analysis of a standalone hybrid energy system in Cambodia

This study aims to present an economically feasible and environmental-friendly hybrid energy system that does not connect to the grid. In Cambodia, many rural areas are facing insufficient power supply problems and need more electricity supply. So, the designed system in this research can supply electric power to a community with 30 households in Krong Kracheh, Kratie Province, Cambodia. Three different designs of hybrid systems are considered. The first design is a hybrid system with PV modules, a diesel generator, and a battery. The second design is a hybrid system including a wind turbine, PV modules, diesel generator, and battery, and finally, a hybrid system that contains a wind turbine, diesel generator, and battery as the third design. According to the simulation results, the first configuration is the best design compared to the other two scenarios as it is the most cost-effective. The Present Net Cost, Cost of Energy, and system operating cost is 46,866 $, 0.268 $/kWh, and 2,327 $/yr, respectively. Besides, it has a total of 4,496.29 kg/yr pollutants emitted, which is less than the third configuration but more than the second configuration. The production of electricity for the first configuration is 23,820 kWh/yr, with a renewable fraction of 65.2%.

Multi-objective optimization, comparison of using different biomass fuels in hybrid energy system for electricity-distilled water production based on supercritical CO2 and humidification and dehumidfication cycles

Biomass-derived power generation presents various potential benefits compared to conventional fossil fuel-based power generation. Also, efficient integration of energy systems leads to higher sustainability and effectiveness. This paper presents a biomass-fueled energy system with two open and closed Brayton cycles in the waste heat, of which a humidification and dehumidification system is implemented. The usage of four different biomasses as the fuel of the gasifier is tested and put to comparison from the aspects of thermodynamics, economics, and environment. The Grassman diagram for each layout is presented to signpost the exact point of highest exergy destruction and irreversibility. The optimization based on machine learning techniques is conducted to pinpoint the exact optimum operational conditions. The results indicate that wood offers more sustainability compared to other biomasses, and the amount of energy efficiency, exergy efficiency, and freshwater flow rate produced for Wood biomass in the proposed system are 75.81 %, 36.98 %, and 0.4091 kg/s, respectively. Also, two optimization scenarios have been done for this study. In the initial optimal solution finding, effectivness, unit product cost, and carbon dioxide emission index are equal to 45.9 %, 12.6 $/GJ, and 0.7161 kg/kWh, correspondingly. In the latter scenario, the effectiveness, net power production, and production unit cost of products are equal to 45.9 %, 6580 kW, and 12.61 $/GJ, respectively.

Energy management and sizing of a stand-alone hybrid renewable energy system for community electricity, fresh water, and cooking gas demands of a remote island

Research into the off-grid hybrid energy system to provide reliable electricity to a remote community has extensively been done. However, simultaneous meeting electric, freshwater, and gas demands from the off-grid hybrid energy sources are very scarce in literature. Power- to-X (PtX) is gaining attention in recent days in the energy transition scenarios to generate green hydrogen, the primary product of the process as an energy carrier, which is deemed to replace conventional fuels to reach absolute carbon neutrality. In this study, renewable–based hybrid energy is developed to simultaneously meet the electricity, freshwater, and gas (cooking gas via methanation process) demands for a remote Island in Bangladesh. In this process, an energy management strategy has been developed to use the excess energy to generate both freshwater and the hydrogen, where hydrogen is then converted to natural gas via methanation process. The PV, wind turbine, diesel generator, battery, and fuel cell have been optimized using non-dominating sorting algorithm-II (NSGA-II) to offer reliable, cost-effective solutions of electricity, freshwater, and cooking gas for the end users. Results reported that the PV/WT/DG/Batt configuration has been found the most economic configuration with the lowest COE (0.1724 $/kWh) which is 9 % lower than PV/WT/Batt configuration which has the second lowest COE. The cost of water (COW) and cost of gas (COG) of the PV/WT/DG/Batt system are also the lowest among all the four configurations and have been found 1.185 $/m3 and 3.978 $/m3, respectively.

Large-scale offshore wind integration by wind-thermal-electrolysis-battery (WTEB) power system: A case study of Yangxi, China

Offshore wind power integration is a grand challenge due to the volatility, randomness and intermittency This work presents a wind-thermal-electrolysis-battery (WTEB) hybrid energy system designed to integrate large-scale offshore wind energy and reduce curtailment. The system composes of offshore wind farms (OWF), thermal power plants (TPP), electrolysis station, battery bank. The Qingzhou (geographic name) I-VII offshore wind farms (5000 MW) and the Yangxi (geographic name) coal-fired power plant units #5, #6 (2 × 1240 MW) are taken as a case study. The OWF is the indispensable generator and the renewable fraction increases with integration level. The TPP adjusts the load ratio to meet the changing net load. The electrolysis station consumes the excess electricity and the battery bank time-shifts the electricity to reduce the electrolyzer downtime. The recommended wind-thermal (W-T) capacity ratio is 1.452:1 in the studied case, namely 3600 MW OWF. The WTEB system breaks the trade-off relationship between renewable fraction (50.11%) and curtailment rate (1.48%) compared to traditional wind-thermal (WT) bundled system. The WPEB system improves the electricity shortage rate (4.74%), transmission line capacity factor (61.79%), load following precision (91.79%). The internal rate of return (IRR), levelized cost of electricity (LCOE), levelized cost of hydrogen (LCOH) of WTEB-W3600 are 34.70%, 0.5172 ¥/kWh, 29.76 ¥/kg. The WTEB hybrid energy system for a large-scale offshore wind power integration is first proposed and the techno-economic feasibility analysis proves the feasibility and forward-looking of the system. Collaborative capacity optimization of OWF, TPP, electrolysis station, battery can improve the system performance and economy. The wind-photovoltaic-thermal-electrolysis-battery (WPTEB) system co-locating the OWF and floating photovoltaic (PV) is an important development direction.

Risk-averse energy management of hydro/thermal/pumped storage complementarily operating with wind/solar: Balancing risk, cost and carbon emission

Large-scale grid integration of variable renewable energy is crucial for achieving decarbonized development. However, this integration requires frequent regulation of flexible power sources for complementary operation, which can lead to wear-and-tear and fatigue damage to key components. This poses potential risks to flexible power sources. Existing studies have primarily focused on limiting unit startups, while have neglected the risk of frequent power regulation. Thus, this work proposes a risk-averse short-term scheduling method for a Wind-Solar-Cascade hydro-Thermal-Pumped storage hybrid energy system to balance frequent regulation risk, cost, and carbon emission: (1) a risk-averse short-term scheduling model is proposed, considering multilayer constraints; (2) a multi-objective hybrid African vulture optimization algorithm is proposed to effectively solve the scheduling problem including continuous and discrete variables. A case study in the Songhua River basin, China shows that: (1) compared with traditional models, the proposed model reduces the risk by 31.4% and enhances the comprehensive performance in balancing the three objectives by 22.4%; (2) the proposed algorithm performs robustness and search capability advantages, with improvements of 33.01% and 21.44% respectively, in solving the problem of challenging constraints and mixed decision variables. Overall, this work contributes to enhancing the management of large hybrid energy systems.

Technical assessment of a stand-alone hybrid renewable system for energy and oxygen optimal production for fishes farming in a residential building using HOMER pro

Electricity holds both economic significance and strategic importance in many regions globally. Persistent challenges related to electricity generation, encompassing aspects like availability, quality, and cost, have impeded the progress of nations for an extended period. While conventional electrochemical storage systems have been the benchmark, they are plagued by issues such as high expenses, technical limitations in power output, and restricted storage capacity. Power generation facilities come with their own array of problems, including noise pollution, environmental impacts, and suboptimal performance, exacerbating the existing concerns of reliability and maintenance. To navigate the path of sustainable global development amidst a sharp upswing in energy consumption, it becomes imperative to foster innovative energy solutions. Independent renewable energy systems (RES) represent a promising avenue for reshaping the prevailing reliance on conventional power grids. The Hybrid Renewable Energy System (HRES) deserves careful calibration, particularly considering the considerable load fluctuations and the need for cost efficiency. The study considers a standalone HRES in a residential area on Manoka Island, where fish farming is a primary activity. This dwelling exhibits a daily electricity consumption averaging at 9.28 kWh, with peak demand hitting 0.88 kW. To evaluate the suitability of the Hybrid Optimization Model for Electric Renewable (HOMER) program, the study investigates the optimal energy generation mix for both sustaining the fish farming industry and fulfilling the energy requirements of the chosen building. The optimization process identifies four key parameters that undergo thorough assessment in this analysis. Delving into the specifics, the study attains an impressive renewable fraction (RF) of 92.5% and achieves a Deficit of Power Supply Probability (DPSP) of 0%. Furthermore, the production of 50 kg of O2 and the emission of 1.69 kg of carbon annually prove adequate for constructing a reliable and environmentally sound energy system. In a broader sense, this research serves as a compelling case study, elucidating the concept of hybrid energy systems within the framework of eco-friendly and sustainable power generation. The study not only underscores the substantial potential of RES for the country but also constitutes a significant stride for researchers active in this field.

Investigating the sustainability of urban energy generation with techno-economic analysis from hybrid energy systems

With the growing need for sustainable energy solutions in urban areas, a strategic integration of energy supply, public transport modernization, and energy demand reduction for residential and commercial buildings has become crucial. While numerous efforts have showcased technological advancements and examined the functionality of energy systems, urban applications have not received adequate attention. To address this gap, this research proposes a feasibility analysis of hybrid energy systems in urban settings. The study incorporates a well-defined research purpose, a robust methodology, and a comprehensive approach to data collection, enabling a thorough investigation of technological, scientific, and industrial developments. There is a requirement for a total of 20,349 k Wh of energy per year in the study area, and it can be met with a PV array having a production capacity of 5591 k Wh per year and a capacity of 14,758 k Wh per year. It also explains that 27 % of the required energy can be harnessed from photovoltaics, and 73 % from a domestic diesel generator. The system emits 13,428 kg of Carbon dioxide (CO2), 33.4 kg of carbon monoxide (CO), 3.71 kg of unburned hydrocarbon, 2.52 kg of particulate matter, 26.7 kg of Sulphur dioxide, 298 kg of Nitrogen oxides. The study encompasses a comprehensive review of past, present, and future trends in energy system design, development, and implementation, providing valuable insights for urban planners and policymakers.

Technoeconomic analysis of hybrid energy system for health clinic in Salalah Oman

Diesel generators are being employed as a means of generating electrical power in various regions across the globe. Considering the imperative to foster environmental sustainability, it appears that conventional electric-producing systems may not be economically viable or environmentally sound, necessitating their replacement with renewable energy alternatives. This study examines the viability of utilizing hybrid electric systems powered by renewable energy sources in health clinics located in Salalah, Oman. The HOMER software, which is utilized for the analysis of system configurations, was employed to examine the application and functional constraints of each hybridized setup. The results indicated that the renewable energy system exhibited the lowest cost of energy in contrast to both the generator set and hybridized energy systems. Renewable energy has superior power generation capabilities in comparison to hybridized energy and standalone generator set systems, rendering it the most economically feasible option and a more favorable choice for meeting the electrification requirements of health clinics.

Hybrid PV/PRC energy system for thermal management of photovoltaics and nocturnal radiative cooling

Under high climatic conditions and intense sunlight, the efficiency and reliability of photovoltaic (PV) systems can rapidly deteriorate due to elevated temperatures. Passive radiative cooling (PRC) technology is a common solution for the thermal optimization of PV systems, as it offers an energy-efficient and environmentally conscious cooling process. This research proposes an advanced hybrid energy system that integrates a radiative cooler, in the form of a photonic structure, with a C-Si solar cell. The photonic structure consists of a multilayer design with a SiO2 grating surface positioned on top. This configuration reduces the operating temperature of the solar cell and preserves its transmissivity within the conversion bandgap range.Numerical results, based on thermal diffusion theory, demonstrate that the hybrid design can generate a very high diurnal electricity output of 83w/m2, with a nighttime cooling capacity of 147w/m2. This represents a 10 % and 40 % improvement compared to bare silicon. Furthermore, when the proposed cooler is applied to the front surface of the solar panel, it induces a PRC effect, resulting in a temperature decrease of approximately 3 K. We believe that the radiative cooler can also be applied to other types of solar cells, including those based on thermoelectric generators, to extract electricity from the radiative cooler during nighttime.

Snow avalanches algorithm (SAA): A new optimization algorithm for engineering applications

This paper proposes a novel efficient inspired algorithm based on snow avalanches in nature which is named the Snow Avalanches Algorithm (SAA), for solving the benchmark and engineering optimization problems and determining the global solution. The proposed algorithm is modeled using four phases including avalanche due to mountain slope, human factors, weather in the region as well as normal conditions and it has only one control parameter. The advantages of this algorithm are low control parameters, simple structure and also easy implementation. The effectiveness of the SAA algorithm is examined on 23 classic benchmark test functions. Then, the effectiveness of the SAA to achieve accurate results in different aspects is examined and proved on engineering problems including six different cases. The superiority of the SAA to solve the classic benchmark test functions is compared with spotted hyena optimization (SHO), particle swarm optimization (PSO), Aquila optimizer (AO), differential evolution (DE), bat algorithm (BA), dwarf mongoose optimization (DMO), genetic algorithm (GA), artificial bee colony (ABC), and ant colony optimization (ACO). The simulation results provide evidence for the well-organized and efficient performance of the SAA in solving a great diversity of engineering problems. The results demonstrated that the SAA can be more effective than other algorithms to solve the test functions in terms of optimization accuracy and convergence rate. Moreover, the results proved that the SAA obtained more competitive results than the previous methods to solve constrained engineering optimization problems, especially hybrid energy system design as well as economic load dispatch problems.

A novel distributed approach for event-triggered economic dispatch of energy hubs under ramp-rate limits integrated with sustainable energy networks

This paper investigates a new consensus-oriented distributed approach for the event-triggered (ET) economic dispatch problem (EDP) over a smart grid under ramp-rate limits (RRLs) integrated with green power sources (GPSs) such as solar and wind energy for demand response strategies over hybrid energy power systems. To address the RRL condition, the authors have transformed the RRLs as minimum and maximum bounds on the derivative of generation for a generator. Then, a Karush–Kuhn–Tucker (KKT) condition and a more practical approximate KKT condition are developed for determining the optimality conditions. A practical ET protocol is proposed over a topology between generators by application of the proposed approximate KKT condition. In contrast to existing distributed optimization methods, this paper provides both optimally condition and distributed optimization scheme for dealing with RRLs integrated with sustainable hybrid energy systems. In addition, a computationally efficient ET mechanism, eliminating Zeno behaviour, has been considered for dealing with the efficient utilization of communication resources. This study incorporates the real-time input data from thermal production plants and GPSs for experimental analysis. RETScreen software having data-set of over 6,700 local meteorological stations is applied to obtain input data for GPSs. Furthermore, Weibull and Beta distribution functions have been applied for dealing with uncertainty in wind and solar energy sources. Two case studies are examined (with and without GPSs), and simulation results demonstrated the suitable performance of the proposed distributed ET EDP approach.

Energy management strategies of hybrid renewable energy systems: A review

Burning fossil fuels results in more emissions than generating electricity from renewable sources. The transition to renewable energy from fossil fuels, which currently produce the majority of emissions, is essential to preventing the climatic disaster. Hybrid energy generation systems are still in their infancy. It is envisaged that future technology developments would lead to greater application and more economical goods. There will be more standardised designs, which will make it easier to select a system that is suitable for a certain application. The components will communicate more with one another. As a result, control, monitoring, and diagnosis will be made simpler. The hybrid energy system (HES), also known as hybrid power, is expected to be the long-term power solution for microgrid (MG) systems. This study compares and contrasts several theories and conventional approaches to controlling HRES’s control and energy consumption. A successful energy management strategy has been created using a variety of methods and procedures. The effectiveness of an EMS is determined by its control architecture and the solution approach used; common topologies include hierarchical, decentralised and centralised EMS. Supply side management and demand side management, two EMS components, will be discussed later. The three EMS control architectures are examined in this section. In order to determine the most practical and dependable solution with the lowest Net present cost (NPC), COE and realistic environmental consequences, various hybridisation cases of a PV panel, wind turbine, battery storage and diesel generator are designed, analysed and compared using DSM. The results of taking into account DSM indicated a reduction in CO2 emissions of 25%, NPC emissions of 14.8%, COE emissions of 14% and an increase in RF emissions of 8.5%. Two fundamental metrics – the DSM Quality Index for technical benefits and the DSM Appreciation Index for economic advantages – are used to assess the technical and economic benefits of DSM.

Two-stage robust optimal capacity configuration of a wind, photovoltaic, hydropower, and pumped storage hybrid energy system

The hybrid energy system of hydro-powers, pumped storages and renewable energies has become a new topic direction in modern power system developments. Consequently, it is essential to realize a rational and efficient allocation of different energy source capacities. Nevertheless, there is still a gap between the available studies and the requirement for further hybrid energy system development. This paper focuses on the optimal capacity configuration of a wind, photovoltaic, hydropower, and pumped storage power system. In this direction, a bi-level programming model for the optimal capacity configuration of wind, photovoltaic, hydropower, pumped storage power system is derived. To model the operating mode of a pumped storage power station, two 0-1 variables are introduced. To handle the nonlinear and nonconvex lower level programing problem caused by the two 0-1 variables, it is proposed that the 0-1 variables are treated as some uncertain parameters. Also, by treating the 0-1 variables as some uncertain parameters, a two-stage robust optimization problem to decompose the original bi-level programing one into a master problem and a subproblem is finally introduced. The Karush-Kuhn-Tucker (KKT) conditions are then applied to simplify and linearize the min-max problem and nonlinear terms in the master problem. This results in both the master problem and the subproblem being formulated as mixed integer linear programming (MILP) problems. By utilizing the powerful Column-and-Constraint Generation (C&CG) algorithm, the two-stage robust optimization model is decomposed into an iterative procedure of solving the master problem and the subproblem sequentially. This approach eliminates the need for intricate optimization algorithms as commonly used in existing bi-level planning problems in hybrid energy systems. Finally, the effectiveness and advantages of the proposed model is verified by the numerical results on a case study.

Parametric study of the effects of clump weights on the performance of a novel wind-wave hybrid system

This paper presents a novel catenary mooring system incorporating multiple clump weights (CWs) designed for a SPIC-Wavestar wind-wave energy hybrid system. To enhance the performance of the hybrid system, a parametric analysis was performed on mooring CWs. The motions of the SPIC platform, along with the power absorbed by the Wavestar wave energy converters (WECs), specifically in response to the operational regular wave, were simulated. The hydrodynamic analysis program AQWA was used for the analysis. The results indicated that the surge and pitch motions of the platform comprised low-frequency and wave-frequency components, whereas the heave motion only comprised a wave-frequency component. However, the low-frequency responses of the surge and pitch motions were substantially smaller than their wave-frequency counterparts. In addition, the properties of the CW exerted notable influence on both platform motion and the overall power absorption by the WEC array. The variation trends with respect to the CW weight, location, and number were complex. Overall, the results of this study provide valuable insights into the mooring design of ocean energy hybrid systems.

Assessing metaheuristic algorithms in determining dimensions of hybrid energy systems for isolated rural environments: Exploring renewable energy systems with hydrogen storage features

Hydrogen presents a clean energy avenue capable of addressing the impending energy crises and environmental challenges. Given Turkey’s vast renewable energy potential, it can effectively meet its escalating electricity demand. In regions where grid connectivity is limited or costly, Hybrid Energy Systems (HRES) integrate a blend of energy matrices, thereby diminishing reliance on conventional sources. This study offers an intricate framework focusing on HRES optimization and energy flow management, emphasizing energy modules, such as wind, solar, biomass gasification, and fuel cells. Excess energy is converted to hydrogen for storage and is; subsequently utilized in fuel cells. The Annual Cost of the System (ACS) is a pivotal criterion during the optimization phase. This optimization encompasses variables such as power from wind turbines, energy output from solar panels, and hydrogen gas storage capacity, streamlined with Atom Search Optimization (ASO) methodology. Based on the consumption and meteorological data from 2022, a rigorous comparison of ten distinct optimization algorithms was conducted. The core objective is to satisfy the energy demand of the proposed hybrid system at a minimal cost. The results indicate that the advocated off-grid HRES emerges as the most cost-effective solution for the demarcated region, with the ASO algorithm demonstrating superiority in the convergence metrics for the objective function. The algorithms were implemented in a MATLAB simulation environment.

Power Management Optimization of HES Connected to the Grid-Based IEMS

This paper presents a study of a grid-connected hybrid energy system (HES) consisting of photovoltaic/wind/fuel cell/battery/supercapacitor (SC). The purpose of using SC with the battery is to create a hybrid energy storage system (HESS) with high energy density. To prevent overcharging of the latter, a discharge load was employed (in our case, a resistance). The objectives of this research are to operate the photovoltaic generator and the wind power generator at their maximum power points by applying the perturbation and observation (P&O) technique and the tip speed ratio (TSR) technique, respectively. On the other hand, the energy management of the proposed system aims to achieve an energy balance between the grid and the HES despite climate changes and changes in energy demand to which the system is exposed, and to lengthen the life cycle of the HESS by keeping the state of charge (SOC) within a limited range. This management is accomplished by using a classical energy management strategy. To achieve optimal power management of the proposed system, a new intelligent energy management strategy (IEMS) based on the FLC-FOPI is proposed. A comparative analysis was also conducted between the classical strategy and the proposed strategy. As for the grid-side converter, direct power control based on SOSMC technique (DPC-SOSMC) has been proposed to regulate the flow of active and reactive power according to grid demand based on HRES. To demonstrate the effectiveness of the proposed controllers, simulation results evaluating the proposed system under variable conditions are presented using the Matlab-Simulink platform.

A risk‐averse framework for techno‐economic analysis and size optimization of an off‐grid hybrid energy system

AbstractIn the power system, optimal sizing of hybrid energy systems (HESs) is a vital and challenging issue. Optimal sizing leads to designing a cost‐effective and reliable power generation system. In such a problem, modelling the load uncertainty helps the planner to make appropriate decisions for optimizing the performance of HESs against possible changes of the electrical load. In this paper, techno‐economic and optimal sizing of an off‐grid photovoltaic‐diesel generator‐fuel cell (PV‐diesel‐FC) HES is investigated in two frameworks, risk‐neutral strategy and risk‐averse strategy, where the load uncertainty is modelled by information gap decision theory. To size the HES, objective function is defined as the total net present cost and with respect to a desirable loss of power supply probability, size of the system components is optimally determined. In the risk‐averse framework, the sizing problem is solved with different critical tolerance levels of the objective function and the results are evaluated. Over the case study, simulation results show that at risk‐averse framework, optimal combination of PV, diesel generator and FC leads to a cost‐effective and reliable HES.

Energy management and capacity planning of photovoltaic-wind-biomass energy system considering hydrogen-battery storage

This article proposed a Salp Swarm nature-inspired metaheuristic optimization algorithm (SSA) for the energy management and capacity planning of a standalone hybrid photovoltaic wind-biomass-hydrogen-battery energy system. The SSA is used to determine the optimum system configuration that will fulfill the demand reliably considering technical (loss of power supply probability (LPSP)) and economical (annualized system cost (ASC)) aspects. The energy management system (EMS) of the energy system is implemented using a rule-based algorithm to effectively manage the power flow of the devised hybrid energy system components. The comparative evaluation of the algorithms shows that EMS-SSA produces a better result as it offers the least levelized cost of energy (LCOE), of $0.939737/kW h, as compared to the EMS-LFA, EMS-GA and HOMER, which offer LCOE of $0.949737/kW h, $0.958660/kW h and $1.075351/kW h, respectively. Similarly, for the optimal system configuration, the annualized system cost (ASC) is found to be 1.887995 M$. This research presents a viable and environmentally sustainable electrification solution, serving as a valuable reference for making electricity investments in the energy-deficient Northeastern part of Nigeria.