Research on multi-objective capacity optimization of PV-CSP hybrid system

ZHANG Bozhi; LU Yan; TAN Chen; ZHOU Lixia; DING Zeyu; HOU Hongjuan

doi:10.19666/j.rlfd.202109177

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Research on multi-objective capacity optimization of PV-CSP hybrid system

更新时间：2025-09-28

- Research on multi-objective capacity optimization of PV-CSP hybrid system
- Thermal Power Generation Vol. 51, Issue 5, Pages: 9-17(2022)
- 作者机构：
  
  1. 国网冀北电力有限公司计量中心
  2. 国网冀北电力有限公司秦皇岛供电公司
  3. 国网冀北电力有限公司
  4. 华北电力大学能源动力与机械工程学院
  5. 华北电力大学新能源电力系统国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.19666/j.rlfd.202109177
  CLC： TM615
- Published：2022
- 稿件说明：
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ZHANG Bozhi, LU Yan, TAN Chen, et al. Research on multi-objective capacity optimization of PV-CSP hybrid system[J]. Thermal power generation, 2022, 51(5): 9-17.
DOI：

ZHANG Bozhi, LU Yan, TAN Chen, et al. Research on multi-objective capacity optimization of PV-CSP hybrid system[J]. Thermal power generation, 2022, 51(5): 9-17. DOI： 10.19666/j.rlfd.202109177.

摘要

将光伏发电和光热发电相结合，可以改善单独光伏发电可靠性低和单独光热发电成本高的缺陷。故提出一种针对光伏光热互补发电系统的多目标容量优化方法，旨在寻找平衡互补系统经济性和供电可靠性的最优折衷解。以张北地区的光伏光热互补发电系统为例，对其进行了容量优化，获得了帕累托最优解集，进而通过理想点法获得了最优折衷解，并通过敏感性分析研究了电负荷及容量参数变化对系统容量优化结果及性能的影响。结果表明，当太阳能倍数2.5、电加热器额定功率为74 MW、储热时长20 h、光伏装机容量82 MW和蓄电池容量为0时，互补系统有最优折衷解，相应的平准化度电成本和负载缺电率分别为1.06元/(kW·h)和5.57%。

Abstract

Combining photovoltaic(PV) with concentrated solar power(CSP) can improve the shortcomings of low PV reliability and high CSP cost. A multi-objective capacity optimization method for PV-CSP hybrid system is proposed to search for the optimal compromise solution between economy and power supply reliability. The main components capacities of a PV-CSP hybrid system located in Zhangbei are optimized and the Pareto optimal schemes are obtained. Then

the optimal compromise solution is obtained by the ideal point method. Moreover

the influence of the change of electric load and capacity parameters on the system capacity optimization results and performance is studied through sensitivity analysis. The results show that

when the solar multiple

electric heater rated power

thermal energy storage capacity

PV installed capacity and battery capacity are 2.5

74 MW

20 h

82 MW and 0

the hybrid system has an optimal compromise solution

and the corresponding levelized cost of energy(LCOE) and loss of power supply probability(LPSP) are 1.06 yuan/(kW·h) and 5.57%

respectively. In addition

sensitivity analysis is conducted to study the impact changes in electrical load and capacity parameters on the capacity optimization results and performance of the hybrid system.

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