考虑地源热泵和需求响应的变电站综合能源系统多时间尺度优化调度研究

Research on multi-time scale optimal scheduling of integrated energy system in substation considering ground source heat pump and demand response

中文关键词: 变电站综合能源  模型预测控制  多时间尺度  优化调度

英文关键词: substation comprehensive energy  model predictive control  multiple time scales  optimal scheduling

中文摘要:

      针对变电站综合能源系统的经济稳定运行问题,提出了一种基于模型预测控制（model predictive control,MPC）的多时间尺度优化调度策略,结合地源热泵与需求响应。首先构建了系统架构,并阐述了MPC算法流程。在日前调度中,通过考虑分时电价与新能源的随机性,建立了以最小化运行成本为目标的优化模型,确定了机组最优出力与储能计划。日内调度则利用MPC算法对日前计划进行实时校正,以降低不确定性对电网的影响,提升经济性。通过算例分析,比较了不同方案,探讨了需求响应特性与地源热泵能效水平。结果表明,所提模型在需求响应环境下实现了系统优化运行,提高了设备利用率,降低了运行成本,并促进了可再生能源消纳。

英文摘要:

      Aiming at the economic stability of substation integrated energy system, a multi-time scale optimization scheduling strategy based on model predictive control（MPC）is proposed, which combines ground source heat pump and demand response. Firstly, the system architecture is constructed and the MPC algorithm flow is described. In day-ahead scheduling, by considering the randomness of TOU and new energy, an optimization model aiming at minimizing operation cost is established, and the optimal output and energy storage plan of the unit are determined. Intra-day scheduling uses MPC algorithm to correct the day-ahead schedule in real time to reduce the impact of uncertainty on the power grid and improve the economy. The demand response characteristics and energy efficiency level of ground source heat pump are discussed by comparing different schemes through example analysis. The results show that the proposed model can optimize the system operation under the demand response environment, improve the equipment utilization rate, reduce the operating cost, and promote the consumption of renewable energy.