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A new technique is suggested in this paper for optimal electrical power energy production and demand forecasting in China. The paper provides a new improved design of the Search and Rescue algorithm for better optimization of the forecasting models. This study is performed based on three scenarios on the electrical power energy production and demand in the period 2020–2050. The study utilizes linear and quadratic models for electricity energy production and demand prediction of the analyzed scenarios. The improved Search and Rescue algorithm in the study is designed based on import and export, gross domestic product (GDP), and population. All of the models based on the scenarios are applied for optimal prediction of electrical power energy generation and demand. The results show that the proposed optimal quadratic models based on the Improved Search and Rescue algorithm provides the fittest results with economic indicators.

A techno-economic study has been proposed for an off-grid combined renewable energy system (HRES) by photovoltaic (PV) and fuel cell (FC) systems. The proposed HRES has been studied to provide electricity for a remote area in Jiaju Tibetan Village, Danba, Sichuan Province China The main idea is formulated according to the Total Annual Cost (TAC). The study uses a new improved metaheuristic, called Amended Water Strider Algorithm (AWSA) to optimal estimation of the photovoltaic panels’ number, electrolyzer, fuel cells, and hydrogen storage tanks to get the minimum value of the overall net present value (ONPV). For increasing the system efficiency, the loss of power supply probability (LPSP) has been considered. Sensitivity analysis is used on the changing of the proposed HRES according to Levelized cost of energy (LCOE). Also, a comparison of the algorithm with several techniques from the literature is performed to illustrate its effectiveness. The results showed that the proposed method has further proper results than the other algorithms.

The use of fossil fuels leads to depletion of fuel reserves and environmental pollution. One way to achieve a sustainable future in urban areas and remote communities is to use the independent renewable energy systems. Meanwhile, solar energy is one of the most common sources of energy generation that has attracted of the world. The present study provides the comprehensive examine the performance of two parabolic dish collector and flat-plate collector from energy, exergy, Enviroeconomic and Exergoenviroeconomic view of points. To examine the performance of solar systems, the climatic conditions of two different cities in Asia (Beijing and Tehran) have been used. In addition, the performance of the systems is investigated under different parameters and using different working fluids and MWCNT nanoparticle. It was found that the both solar systems have better overall performance in Tehran than in Beijing. Moreover, in the months when the solar collector has lower exergy efficiency, its use in Tehran compared to that Beijing has a better exergy performance than other months. In addition, the lowest and highest Levelized Cost of Energy are belong to dish collector (in Tehran with water) and flat plate collector (in Beijing with Dowtherm Q), respectively. For Tehran, LCOE of dish collector increases more than 5.5-fold when using water/MWCNT nanofluid instead of water.