电力建设2026，Vol.47Issue(8)：101-118,18.DOI:10.12204/j.issn.1000-7229.2026.08.008
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
Optimized Dispatch for CSP-PV Hybrid Plants in Sandy-Gobi-Desert Regions Considering Frequency-Inertia Coordinated Constraints
摘要
Abstract
[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.关键词
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Key words
sandy-gobi-desert regions/concentrated solar power-photovoltaic hybrid power plant/frequency stability/frequency-inertia constraints/deep reinforcement learning分类
信息技术与安全科学引用本文复制引用
陈实,晏红平,臧天磊,刘艺洪,陈江平,王舒灏,李华强..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[J].电力建设,2026,47(8):101-118,18.基金项目
国家自然科学基金项目(52577129,52377115) （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). （2025ZD0807300）
