Abstract
Reasonable configuration of equipment capacity can effectively improve the economics of wind-photovoltaic-battery hybrid generation system (WPB-HGS). Based on the current needs of investors to pay more attention to the economic benefits of WPB-HGS, this paper proposes a capacity configuration method for WPB-HGS considering return on investment (ROI). A bi-level planning model for integrated planning and operation of WPB-HGS was established. The lower-level model optimizes the system’s operating status with the goal of maximizing the daily power sales of the system. The upper-level model plans the equipment capacity of the WPB-HGS with the goal of maximizing the annual net income and return on investment. The model is solved using adaptive weighted particle swarm optimization. According to actual engineering examples, the specific equipment capacity is configured, and the configuration results are analyzed to verify the effectiveness of the method.
Highlights
With the overexploitation of fossil energy such as oil and coal, the problem of energy exhaustion is becoming more and more serious [1]
Based on the bi-level planning model established in this paper, the typical data of scenery in Figures 4 and 5, the basic parameters of each equipment in Tables 1 and 2, and the electricity sales strategy in Tables 4 and 5, AW-particle swarm optimization (PSO) was used to solve the model
Table shows the maximum power difference in high, filling. This is because the investment cost and replacement cost of energy storage batteries are system beforestorage and after unit time.for peak output and valley filling in system output is not and the useoutput of energy batteries
Summary
With the overexploitation of fossil energy such as oil and coal, the problem of energy exhaustion is becoming more and more serious [1]. Reference [20] presents a methodology for the joint capacity optimization of renewable energy (RE)sources, i.e., wind and solar, and the state-of-the-art hybrid energy storage system (HESS) composed of battery energy storage (BES) and supercapacitor (SC) storage technology, employed in a grid-connected microgrid (MG). In Reference [21], two constraint-based iterative search algorithms are proposed for optimal sizing of the wind turbine (WT), solar photovoltaic (PV), and the battery energy storage system (BESS) in the grid-connected configuration of a microgrid. In Reference [23], a bi-level model is proposed to optimize the allocation of photovoltaic (PV), wind turbine (WT), and energy storage system (ESS) in distribution networks. Established a bi-level model of planning operation integration of the WPB-HGS This bi-level planning model can optimize the capacity and operation state of the system equipment to improve the economy of planning results.
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