The main contributions of this study are to (i) incorporate tidal power into a hybrid PV/wind/battery renewable energy system and (ii) introduce a new metaheuristic technique named crow search algorithm (CSA) for opti...
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The main contributions of this study are to (i) incorporate tidal power into a hybrid PV/wind/battery renewable energy system and (ii) introduce a new metaheuristic technique named crow search algorithm (CSA) for optimisation of the PV/wind/tidal/battery system. For this aim, power equations of the different components are introduced and an objective function is defined based on the economic analysis of the system. The proposed CSA is then used to optimally size the PV/wind/tidal/battery system. On the case study, simulation results show that using tidal energy decreases the total cost of the system. Moreover, the proposed CSA produces better results in comparison with two well-known metaheuristic methods, namely, particle swarm optimisation and genetic algorithm in terms of accuracy and run time.
In this study, an economic model is proposed to simulate the optimal operation of a grid-connected microgrid regard to the uncertainties of microgrids' components. In this study, the wind farms are considered as r...
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In this study, an economic model is proposed to simulate the optimal operation of a grid-connected microgrid regard to the uncertainties of microgrids' components. In this study, the wind farms are considered as renewable resources and an innovative technology of advanced rail energy storage (ARES) is deployed as a storage unit. In the optimization model, the stochastic nature of wind energy and the intermittency of loads are contemplated in the model by employing scenario-based Monte Carlo approach to simulate the implication of uncertainties The objective function of the optimization problem is defined subject to maximize the profit of microgrid's components, and the problem is solved by employing crow search algorithm (CSA). Ultimately, the results of the numerical study are presented and discussed which confirm the effectiveness of the model and appropriate performance of the selected storage technology.
For compensating reactive power, shunt capacitors are often installed in electrical distribution networks. Consequently, in such systems, power loss reduces, voltage profile improves and feeder capacity releases. Howe...
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For compensating reactive power, shunt capacitors are often installed in electrical distribution networks. Consequently, in such systems, power loss reduces, voltage profile improves and feeder capacity releases. However, finding optimal size and location of capacitors in distribution networks is a complex combinatorial optimisation problem. In such problem, an objective function which is usually defined based on power losses and capacitor installation costs should be minimised subject to operational limitations. In this study, a newly developed metaheuristic technique, named crow search algorithm (CSA), is proposed for finding the optimal placement of the capacitors in a distribution network. CSA is a population-based technique inspired by the greedy behaviour of crows in finding better food sources. The main reasons of using CSA are its easy implementation, few parameters to adjust, fast convergence speed and high efficiency. In the case studies, simulated results indicate that the proposed CSA produces more accurate results than the other studied search methods.
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