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Zhi Yuan

Bio: Zhi Yuan is an academic researcher from Xinjiang University. The author has contributed to research in topics: Renewable energy & Energy storage. The author has an hindex of 9, co-authored 16 publications receiving 247 citations.

Papers
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
TL;DR: An optimal stochastic scheduling problem of EH integrated with P2G storage, combined heat and power (CHP) unit, wind power, boiler, electrical storage, and thermal storage to meet electrical, heat, and gas demands considering demand response program (DRP).
Abstract: Reliable energy supply is a significant challenge for the power system operators. The increase of emerging resources, as well as multi-carrier consumers in energy systems, lead to the integration of multi-carrier energy systems. The energy hub (EH) is one of the central infrastructures which smooths the combination and interdependency of various energy carriers to increase the efficiency and reliability. A novel technology, such as power-to-gas (P2G) storage, is a great option for achieving a renewable resources-based integrated energy system with high efficiency. The P2G storage is regarded as a viable energy storage approach to cover ever-increasing renewable energy resources variability in power system operations. The contribution of this paper is to present an optimal stochastic scheduling problem of EH integrated with P2G storage, combined heat and power (CHP) unit, wind power, boiler, electrical storage, and thermal storage to meet electrical, heat, and gas demands considering demand response program (DRP). The load shifting based DRP is applied on the electrical loads to reduce the operation cost of the EH. Also, the P2G storage system is used as a new resource that makes a connection between electrical and natural gas networks by converting the power to hydrogen and after that to natural gas through two processes including electrolysis and mechanization, respectively. A scenario-based stochastic approach is applied to handle the uncertainties related to the electrical loads, wind power, and electricity price. The objective of the proposed problem is to minimize the total operation cost of EH, which is modeled as a mixed-integer linear programming (MILP) problem model. The numerical results are implemented for different cases which demonstrate the effectiveness of the integration of the P2G based multi-carrier energy storage and DRPs on the operation cost of EH. The achieved results confirm the proposed approach by demonstrating the considerable reduction in operating cost of the EHS by approximately 7%.

72 citations

Journal ArticleDOI
TL;DR: The final results declared a satisfying agreement between the proposed DCOA and the empirical data, and declared the excellence of the presented method toward the other compared methods.

62 citations

Journal ArticleDOI
TL;DR: A new methodology has been proposed for optimal allocation and optimal sizing of a lithium-ion battery energy storage system (BESS) and the results showed that using two BESS can reduce the total error of the distribution system.
Abstract: In this study, a new methodology has been proposed for optimal allocation and optimal sizing of a lithium-ion battery energy storage system (BESS). The main purpose is to minimize the total loss reduction in the distribution system. The optimization process is applied using a newly developed type of Cayote Optimization Algorithm (COA). The proposed technique includes two different approaches. In the first approach, the optimization for allocation and the sizing are performed one by one and in the second approach, the optimization has been done simultaneously. To analyze the proposed system, four different scenarios have been analyzed which include different conditions without/with PVs and also using single/two BESS. The results showed that using two BESS can reduce the total error of the distribution system. the results also showed that using PVs can also decrease the total losses. Finally, the proposed approach based on ICOA is compared with Firefly Algorithm (FA), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to show the proposed method's prominence efficiency.

49 citations


Cited by
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Journal ArticleDOI
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

Journal ArticleDOI
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

Journal ArticleDOI
TL;DR: In this article , a bibliometric analysis based on a comprehensive review of the highly cited articles on HydESS to provide a detailed insight into future directions and applications was performed by using the Scopus database search engine to look for filtered keywords in the HydESS and related research.

85 citations

Journal ArticleDOI
TL;DR: This paper proposes an on-line method based on the fusion of incremental capacity and wavelet neural networks with genetic algorithm (GA-WNN) to estimate SOH under current discharge to estimate battery's SOH.
Abstract: Accurate state of health (SOH) is a crucial factor for the regular operation of the electric vehicle. Compared with the equivalent circuit methods, the data-driven methods do not rely on the battery model and do not need to measure the open-circuit voltage. This paper proposes an on-line method based on the fusion of incremental capacity (IC) and wavelet neural networks with genetic algorithm (GA-WNN) to estimate SOH under current discharge. Firstly, IC curves are acquired, and the important health feature variables are extracted from IC curves using Pearson correlation coefficient method. Second, The GA is used to optimize the initial connection weights, translation factor and scaling factor of WNN; then, the GA-WNN model is applied to estimate battery's SOH. Third, the established model is verified by battery data. Finally, the experiment results show that the SOH estimation error of this method is less than 3%.

65 citations

Journal ArticleDOI
TL;DR: A novel decomposition method, which guarantees near-global-optimal solutions with low computational effort, is proposed for solving the operation problem and is validated and tested on an 11-node test system from the specialized literature.
Abstract: This paper presents a methodology for the optimal location, selection, and operation of battery energy storage systems (BESSs) and renewable distributed generators (DGs) in medium–low voltage distribution systems. A mixed-integer non-linear programming model is presented to formulate the problem, and a planning-operation decomposition methodology is proposed to solve it. The proposed methodology is separated into two problems (planning and operation problems). The planning problem is related to the location and selection of these devices, and the operation problem is responsible for finding the optimal BESS operating scheme. For solving the planning problem is used a simulated annealing algorithm with a defined neighborhood structure that uses a sensitivity analysis based on the Zbus matrix. A novel decomposition method, which guarantees near-global-optimal solutions with low computational effort, is proposed for solving the operation problem. The effectiveness and accuracy of the proposed decomposition method is validated and tested on an 11-node test system from the specialized literature, and the robustness of the proposed method is assessed and tested on a modified version of an IEEE 135-node test system. The proposed planning-operation decomposition methodology is tested on a real medium–low voltage distribution system of 230 nodes. To verify the efficiency of the proposed methodology, four cases are compared: (I) without BESS and DGs, (II) with DGs, (III) with BESS, and (IV) with BESS and DGs. The numerical results demonstrate the effectiveness and robustness of the proposed methodology.

64 citations