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基于深度强化学习的综合能源系统低碳经济调度
Low carbon economic dispatch of integrated energy system based on deep reinforcement learning
综合能源系统能够实现多种能源形式的供应，但同时排放的大量CO2也影响着周边环境。针对综合能源系统的低碳经济调度问题，本文提出一种基于双延迟深度确定性策略梯度算法的优化调度策略。首先，以调度运行成本最小为目标函数，建立考虑碳捕集技术和电转气技术的包含电、热、冷多能互补的综合能源系统模型；其次，引入碳交易机制，提高优化调度策略节能减排的积极性；然后，根据强化学习框架设计优化模型的状态空间、动作空间和奖励函数等，利用TD3算法中的智能体与环境互动，探索策略，学习综合能源系统的运行策略；最后，利用历史数据对TD3算法的智能体进行训练。并对比线性规划和粒子群算法在不同场景下进行算例分析。结果表明，本文所提方法可以减少综合能源系统的运行时的碳排放和运行成本，能够实现综合能源系统的低碳经济调度。
Integrated energy systems enable the supply of multiple forms of energy, but at the same time emit a large amount of carbon dioxide, which also affects the surrounding environment. An optimal scheduling strategy based on double delay depth deterministic strategy gradient algorithm is proposed for low carbon economy scheduling in integrated energy systems. Firstly, taking the minimum operation cost as the objective function, a comprehensive energy system model with multiple complementary energies of electricity, heat and cold is established considering carbon capture technology and power to gas technology. Secondly, introduce a carbon trading mechanism to improve the enthusiasm of energy conservation and emission reduction in optimal scheduling. Then, according to the reinforcement learning framework, the state space, action space and reward function of the optimization model are designed, and the agents in the TD3 algorithm are used to interact with the environment to explore strategies and learn the operation strategy of the integrated energy system. Finally, we use the historical data to train the agent of TD3 algorithm, and compare the linear programming algorithm and particle swarm optimization algorithm in different scenarios. The results show that the proposed method can reduce the carbon emission and operating cost of the integrated energy system, and can realize the low-carbon economic dispatch of the integrated energy system.
碳捕获系统;电转气;深度强化学习;双延迟深度确定性策略梯度;综合能源系统;碳交易机制;
carbon capture system; power to gas; deep reinforcement learning; twin delayed deep deterministic policy gradient; integrated energy system; carbon trading mechanism
崔在兴,应雨龙,李靖超,王新友
cuizaixing,Ying Yulong,Li Jingchao,Wang Xinyou
1.上海电力大学能源与机械工程学院;2.上海电机学院电子信息学院
1.Shanghai University of Electric Power College of Energy and Mechanical Engineering;2.Shanghai Dianji university School of Electronic Information Engineering
njqxxyxb/article/abstract/20230608001