计及P2P能源交易的综合能源系统优化调度与经济运行

由于可再生能源出力具有随机性、波动性等特征，目前可再生能源消纳问题也愈加明显，如何处理电力无法长时间存储的问题是解决上述问题的关键所在。综合能源系统可以通过内部各个单元的协同运行，有效实现电-氢-热等多种能源的互补，降低弃风、弃光率。随着综合能源系统的迅猛发展，将多个地理位置接近的综合能源系统互相连接并以集群的形式运行是必然的发展趋势，这种端对端的能源交易有利于提高各综合能源系统运行的安全性与可靠性，并实现可再生能源的就地消纳与高效利用。

综合能源系统群中的各系统间存在能量交互，如电能交易和热能交易。综合能源系统群的优化调度策略的目标是实现综合能源系统群整体最优运行，需要同时考虑各系统自身的经济运行问题，以及综合能源系统之间功率交互问题。

对于解决可再生能源电源出力的随机性给综合能源系统群的优化调度带来的问题，本文构建了基于柔性加权管模型预测控制方法的三阶段能量管理策略，其中包括日前的鲁棒能量管理，日内和实时在线滚动时域能量管理。为了可靠地保障各用户的隐私，以子综合能源系统间的交互功率为优化问题的耦合变量，将传统的集中式优化解耦为各子综合能源系统的子优化问题，采用交替方向乘子法对问题进行求解，并结合求解结果对惩罚因子进行更新。通过算例仿真验证了柔性加权管模型预测控制方法在不确定性信息下的经济性，以及改进交替方向乘子法的有效性和收敛性。

Due to the randomness and volatility of renewable energy output, the consumption problem of renewable energy is becoming more obvious. How to deal with the problem that electricity cannot be stored for a long time is the key to solving the above problem. The integrated energy system can effectively realize the complementing of electricity, hydrogen, heat, and other energy through the collaborative operation of each internal unit and reduce the abandonment rate of wind and solar power. With the rapid development of integrated energy systems, it is an inevitable development trend to connect multiple integrated energy systems with close geographical locations and run them in the form of clusters. The peer-to-peer (P2P) energy trading is conducive to improving the security and reliability of the operation of the integrated energy system and realizing the local consumption and efficient utilization of renewable energy.

There is energy trading among the systems in the integrated energy system cluster, such as power trading and heat energy trading. The objective of the optimal energy scheduling strategy of an integrated energy system cluster is to achieve the overall optimal operation of an integrated energy system cluster, and the economic operation of each system and the power interaction between integrated energy systems should be considered at the same time.

To solve the problem of optimal energy scheduling of integrated energy system clusters caused by the randomness of renewable energy output, this paper constructed a multi-stage energy management strategy based on the flexible weighted tube model predictive control (MPC) method, including day-ahead, intra-day, and real-time stage. To reliably ensure the privacy for each integrated energy system, in the interaction between integrated energy system power for the optimization problem of coupled variables, the traditional centralized optimal decoupling for each integrated energy system of sub-optimization problems, using alternating direction multiplier method with varying penalty factors to solve the problem. The economy of the flexible weighted tube MPC method under uncertain information and the effectiveness and convergence of the improved alternating direction multiplier method is verified by numerical simulation.

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