Author
Yong Wang
Other affiliations: Electric Power University
Bio: Yong Wang is an academic researcher from Electric Power Research Institute. The author has contributed to research in topics: System identification & Hybrid algorithm. The author has an hindex of 1, co-authored 1 publications receiving 82 citations. Previous affiliations of Yong Wang include Electric Power University.
Topics: System identification, Hybrid algorithm
Papers
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TL;DR: An optimized improved Elman neural network based on a new hybrid optimization algorithm is proposed for increasing their efficiency in the next designs of the proton exchange membrane fuel cell.
132 citations
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TL;DR: The proposed ASSA is utilized for minimizing the sum of squared error (SSE) between the empirical stack voltage and the calculated stack voltage by optimal selection of the mentioned parameters in the PEMFC stack.
115 citations
TL;DR: A newly developed model of the Sunflower Optimization Algorithm (DSFO) is proposed for minimizing the sum of squared error (SSE) value between the estimated and the actual output voltage of the PEMFC stack.
102 citations
TL;DR: In this article, a multi-objective technique has been proposed for optimal analysis of three different candidate heat pump solutions including the vapor compression cycle (VCC), trans-critical R744 cycle, and Peltier device to determine which one gives the best configuration and better performance on a hybrid heat pump and fuel cell-based micro-CHP system.
98 citations
TL;DR: In this article, an off-grid combined renewable energy system (HRES) by photovoltaic (PV) and fuel cell (FC) systems is proposed 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).
96 citations
TL;DR: In this article, a matching model of energy supply and demand of the integrated energy system in coastal areas in the United States was constructed by using the matching relationship between energy supply-demand, so as to complete the matching of the matching.
Abstract: Zhao, X; Gu, B; Gao, F, and Chen, S, 2020 Matching model of energy supply and demand of the integrated energy system in coastal areas In: Yang, Y; Mi, C; Zhao, L, and Lam, S (eds), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering Journal of Coastal Research, Special Issue No 103, pp 983–989 Coconut Creek (Florida), ISSN 0749-0208Due to the uncertainty of the selection range of the main equipment capacity of the distributed energy system in coastal areas, the matching ability of energy supply and demand is relatively low From the two directions of “power by heat” and “heat by electricity”, the operation and output modes of energy in the system are studied; the selection range of the main equipment capacity of the distributed energy system is determined by calculating the load of energy supply and demand; according to the selection range, the necessary mapping conditions of the matching relationship between energy supply and demand are analyzed, and the matching model of energy supply and demand is constructed by using the matching relationship between energy supply and demand, so as to complete the matching of energy supply and demand of the integrated energy system in coastal areas The experimental results show that the total energy output of the integrated energy system in coastal areas reaches 1867 kJ in unit time, but the proportion occupancy rate between the output nodes is the lowest, which has a good matching ability of energy supply and demand
84 citations