电力系统风险规避投资模型及分布式求解策略

田坤鹏, 韩建振, 臧义, 王均

太阳能学报 ›› 2024, Vol. 45 ›› Issue (11) : 34-39.

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (11) : 34-39. DOI: 10.19912/j.0254-0096.tynxb.2023-1048

电力系统风险规避投资模型及分布式求解策略

  • 田坤鹏1, 韩建振2, 臧义1, 王均1
作者信息 +

RISK-AVERSE INVESTMENT MODELS AND DISTRIBUTED SOLUTION STRATEGIES FOR POWER SYSTEMS

  • Tian Kunpeng1, Han Jianzhen2, Zang Yi1, Wang Jun1
Author information +
文章历史 +

摘要

建立电源、电网、柔性负荷和储能的数学模型,引入条件风险价值度量可再生能源不确定性风险,建立互联电力系统“源-网-荷-储”协调规划模型。考虑各区域电力系统信息安全性和隐私性提出分布式求解策略,以区域间联络线为耦合变量将集中式优化模型解耦为分布式优化模型。将动态惩罚参数和预测校正策略整合到交替方向乘子算法提高收敛速度,通过算例仿真验证基于分布式优化的风险规避投资模型的有效性。

Abstract

A mathematical model is established for generation, transmission, controllable load, and energy storage. The conditional value-at-risk is used to measure renewable energy uncertainty. A coordinated framework of “source-grid-load-storage” is proposed for the interconnected power system. A solution method is proposed to consider the information security and privacy of each regional power system. The centralized optimization model is decoupled into a distributed optimization model using inter-regional contact lines as coupling variables. The dynamic penalty parameters and prediction correction strategy are integrated into the alternating direction multiplier algorithm to improve the convergence speed. The numerical results verify the effectiveness of the risk-averse investment model based on distributed optimization.

关键词

数学模型 / 区域规划 / 可再生能源 / 储能 / 风险分析 / 电力系统仿真 / 分布式优化

Key words

mathematical models / regional planning / renewable energy / energy storage / risk analysis / power system simulation / distributed optimization

引用本文

导出引用
田坤鹏, 韩建振, 臧义, 王均. 电力系统风险规避投资模型及分布式求解策略[J]. 太阳能学报. 2024, 45(11): 34-39 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1048
Tian Kunpeng, Han Jianzhen, Zang Yi, Wang Jun. RISK-AVERSE INVESTMENT MODELS AND DISTRIBUTED SOLUTION STRATEGIES FOR POWER SYSTEMS[J]. Acta Energiae Solaris Sinica. 2024, 45(11): 34-39 https://doi.org/10.19912/j.0254-0096.tynxb.2023-1048
中图分类号: TM715   

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基金

河南工业大学博士基金(2022BS049);河南省科技攻关资助项目(222102240061)

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