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In this paper optimal designing of two hybrid photovoltaic/wind turbine (PV/WT) systems with different storage include battery and hydrogen is presented with objective of minimising cost of energy generation (COEG) and considering reliability constraint as deficit power probability of the system using improved salp swarm optimisation algorithm (ISSOA) for commercial centre area, for Iran country. Different hybrid systems are compared in view of cost and reliability and the optimal size is determined. The results show that the PV/WT with battery storage has lower COEG than PV/WT with hydrogen storage to supply the commercial centre and also its reliability is better than the system integrated with hydrogen. The average cost of per kW of load supply for the PV/WT system with battery and hydrogen storage is 0.216$ and 0.610$, respectively. Superiority of ISSOA is confirmed in comparison with conventional SSOA and particle swarm optimisation in hybrid systems designing. [ABSTRACT FROM AUTHOR]

The depletion of fossil fuel sources has encouraged the authorities to use renewable resources such as wind energy to generate electricity. A backup/storage system can improve the performance of wind turbines, due to fluctuations in power demand. The novelty of this study is to utilize a hybrid system for a wind farm, using the excess electricity generated by the wind turbines to produce hydrogen in an alkaline electrolyzer (AEL). The hydrogen storage tank stores the produced hydrogen and provides hydrogen to the proton-exchange membrane fuel cell (PEMFC) to generate electricity once the power demand is higher than the electricity generated by the wind turbines. The goal of this study is to use the wind profile of a region in Iran, namely the Cohen region, to analyze the performance of the suggested integrated system on a micro scale. The output results of this study can be used as a case study for construction in the future, based on the exact specification of NTK300 wind turbines. The results indicate that, with the minimum power supply of 30 kW from the wind turbines on a lab scale, the generated power by the PEMFC will be 1008 W, while the maximum generated hydrogen will be 304 mL/h. [ABSTRACT FROM AUTHOR]

This paper proposes an optimal operational scheduling framework to integrate the distributed generators (DGs) in the distribution network. This framework is used to maximize the benefit of DG owner and distribution network operator (DNO). In this paper, two optimization model has been proposed to optimum emission and economic operation performance of distribution network in the presence of demand response program (DR). DR under time of use (TOU) pricing is utilized to promote both DG owner and DNO benefits from economic operation issue. The mixed-integer programming (MIP) is used to model a multi-objective problem in General Algebraic Modeling System (GAMS). Then, the problem is solved by employing weighted sum and fuzzy decision making methods. The obtained results reveal that due to positive implementation of DR program, dependency of the distribution network to the upstream network is decreased and load curve become smoother. The under study systems are IEEE 33-bus test system and 101-bus Khoy-Iran actual distribution system which compose electric vehicle parking lot (PL), battery storage, hydrogen storage system (HSS), and local dispatchable generators (LDG). • Optimal scheduling of HSS. • Benefit maximization of DG owner and DNO. • Employing TOU based DR program. • Implementing sum weighted method and fuzzy decision making method. [ABSTRACT FROM AUTHOR]

Much attention has been paid to the deployment of Hydrogen storage systems (HSSs) and Hydrogen vehicles (HVs) in the modernized energy system. However, a research gap exists in the literature about optimal probabilistic planning of microgrids (MGs) equipped with HSS, considering the uncertainties of renewable energy resources and electric vehicle (EV) and HV owners' behaviors. The main purpose of this research is to fill such a gap by developing a new probabilistic optimization problem to determine the capacity of Hydrogen-based MGs' sub-systems. Another contribution is to consider the reliability constraints and loss of energy cost (LOEC) in the MGs' total net present cost (TNPC). The Monte Carlo simulation (MCS) and Flower Pollination Algorithm (FPA) are used to model stochastic behaviors and solve the proposed probabilistic optimization problem. This paper studies different actual climates of Iran based on historical data, while various coordinated/uncoordinated charging modes of EVs and HVs are examined. Test results infer that a significant inaccuracy (more than 4.66% depends on the climate conditions and vehicle scenarios) occurs due to neglecting the uncertainties. The sensitivity analyses imply that the reliability constraints, LOEC, and their interactions might affect the MGs' optimal design. [Display omitted] • A novel optimal probabilistic planning for hydrogen-based microgrids. • Considering the reliability constraints in the proposed stochastic method. • Studying the proposed method in various climates. • Investigating the EVs and HVs impacts on the optimal planning of MGs. • More than 4.66% accuracy improvement by applying the proposed method. [ABSTRACT FROM AUTHOR]

In this paper optimal and cost-effective design of a photovoltaic/wind turbine/fuel cell (PV/WT/FC), the renewable energy system is proposed with the objective of lifespan cost of hybrid system (LSCS) minimisation and considering reliability constraint as a maximum of load interruption probability (LIP) as LIPmax to supply the demand of residential-commercial centres (RCC) located in Iran based on real data of irradiance and wind speed of this region. A new hybrid meta-heuristic algorithm named hybrid grey wolf optimiser-sine cosine algorithm (HGWOSCA) based on the exponential decreasing function (EDF) with high accuracy and speed of optimisation in achieving to the global solution is applied to determine the optimal size of system components. The superiority of the proposed HGWOSCA is compared with SCA, GWO and particle swarm optimisation (PSO) methods in designing of different combinations of the hybrid system and under varying reliability constraint. The results showed that the PV/WT/FC combination is the best combination in view of LSCS and LIPmax for supplying the RCC as a cost-effective and reliable combination. The superiority of the HGWOSCA in designing different combinations of the hybrid system is proved with fewer LSCS and LIP than the other methods with more convergence speed and accuracy. The results clearly showed that the use of hydrogen storage as a reserve power has well compensated the fluctuations in renewable sources production for meeting the RCC load to achieve optimal reliability. The results cleared that the cost of per kW of RCC supply for LIPmax = 1% and LIPmax = 5% is 0.853 and 0.764 $. The results indicated that increasing the failure rate of the components increases the system cost and weakens the reliability. In addition, the results showed that increased FC efficiency has reduced the level of reserve hydrogen, reduced the LSCS, and improved reliability. [ABSTRACT FROM AUTHOR]

The techno-economic and environmental performance of hybrid solar hydrogen energy systems was investigated to provide combined cooling, heating and power (CCHP) demands of a standalone greenhouse in Iran to achieve sustainable agriculture based on an optimization procedure. From the environmental point of view, by deploying hybrid energy systems, 83%, to 100% of emissions can be avoided. Also a sensitivity analysis was performed on the hybrid energy systems in order to study the effect of major parameter variation on the systems justification. It was concluded that hybrid solar systems are economically competitive with conventional systems, for high solar intensity locations with high diesel fuel prices and decreased prices for PV and hydrogen storage technology. [ABSTRACT FROM PUBLISHER]