首页|期刊导航|电力建设|考虑频率-惯量协同约束的沙戈荒地区光热-光伏联合电站智能调度

考虑频率-惯量协同约束的沙戈荒地区光热-光伏联合电站智能调度OA

Optimized Dispatch for CSP-PV Hybrid Plants in Sandy-Gobi-Desert Regions Considering Frequency-Inertia Coordinated Constraints

中文摘要英文摘要

[目的]针对我国"沙戈荒"大型新能源基地并网面临的高渗透率与低惯量特征,以及传统调度方法主要围绕稳态功率平衡和经济运行,对频率安全隐患关注不足的局限,本文提出一种计及广义惯量与频率变化率硬约束的光热-光伏联合电站优化调度方法.[方法]首先,构建包含光热同步机物理特性的频率安全边界模型,将优化调度建模为马尔可夫决策过程.其次,针对传统双延迟深度确定性策略梯度算法(twin delayed deep deterministic policy gradient,TD3)在长周期储热状态感知及稀疏频率越限样本学习上的不足,提出一种融合长短期记忆网络(long short-term memory,LSTM)与优先经验回放(prioritized experience replay,PER)的改进TD3(LSTM-PER-TD3)算法.[结果]基于改进IEEE-30及IEEE-57节点系统的多场景仿真表明:所提LSTM-PER-TD3算法在完整频率-惯量约束场景下实现了频率越限与备用短缺双零,且总运行成本与混合整数线性规划(mixed integer linear programming,MILP)方法得到的理论最优解仅相差2.94%.[结论]光热电站同时具备储热时移调节能力与同步机组物理惯量支撑双重优势,能够为高比例新能源基地筑牢频率安全保障;所构建的LSTM-PER-TD3优化算法,在兼顾运行安全性与经济性的前提下实现了机组高效调度,可为高比例新能源电力系统并网运行下的主动频率支撑与智能化经济调度提供理论依据与技术支撑.

[Objective]To address the high penetration and low-inertia characteristics arising from the grid integration of large-scale renewable energy bases in"sandy-gobi-desert"regions,as well as the limitations of traditional dispatch methods that primarily focus on steady-state power balance and economic operation with insufficient attention to frequency security risks,this paper proposes an optimal dispatch method for concentrated solar power-photovoltaic hybrid power plants considering generalized inertia and rate of change of frequency hard constraints.[Methods]First,the optimal dispatch of concentrated solar power-photovoltaic hybrid power plants is modeled as a markov decision process.This model incorporates dynamic security constraints,such as the rate of change of frequency and generalized inertia,to achieve strict control over grid frequency security boundaries.Second,to efficiently solve this highly nonlinear scheduling model and overcome the limitations of the conventional twin delayed deep deterministic policy gradient(TD3)algorithm—specifically addressing the low utilization efficiency of historical information and the insufficient learning of critical disturbance samples—an improved TD3 algorithm integrating long short-term memory(LSTM)networks and a prioritized experience replay(PER)mechanism is proposed.[Results]Multi-scenario simulation results based on modified IEEE-30 and IEEE-57 bus systems demonstrate that,under the complete frequency-inertia constrained scenario,the proposed LSTM-PER-TD3 algorithm achieves zero frequency-limit violations and zero reserve shortage,with a total operating cost only 2.94%above the mixed integer linear programming(MILP)theoretical optimum.[Conclusions]Concentrating solar power plants possess dual advantages of thermal energy storage for time-shifting regulation and physical inertia support from synchronous units,which can firmly guarantee frequency security for high-penetration new energy bases.The developed LSTM-PER-TD3 optimization algorithm realizes efficient unit scheduling while balancing operational safety and economy.It provides theoretical foundations and technical support for active frequency support and intelligent economic scheduling of power systems with high-penetration new energy integration.

陈实;晏红平;臧天磊;刘艺洪;陈江平;王舒灏;李华强

四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065四川大学电气工程学院,成都市 610065

信息技术与安全科学

沙戈荒地区光热-光伏联合电站频率稳定频率-惯量约束深度强化学习

sandy-gobi-desert regionsconcentrated solar power-photovoltaic hybrid power plantfrequency stabilityfrequency-inertia constraintsdeep reinforcement learning

《电力建设》 2026 (8)

101-118,18

国家自然科学基金项目(52577129,52377115)国家重点研发计划资助项目(2025ZD0807300) This work is supported by National Natural Science Foundation of China(No.52577129,No.52377115)and National Key R&D Program of China(No.2025ZD0807300).

10.12204/j.issn.1000-7229.2026.08.008

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