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Coordinated optimal dispatch for active distribution network under multi-time scales

机译:多时间尺度下主动配电网的协调最优调度

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Recently, large-scale renewable energy sources access to power system has brought a great challenge on the energy management and stability operation of active distribution network. To a two stage multi-source coordinated optimized dispatching model under multi-time scales is established, based on the load forecasts and intermittent energy output forecasts, to fully consume large amounts of renewable energy sources (RES), which consists of day-ahead dispatch model and real-time dispatch model. The optimization objective of the optimal dispatch model is to minimize the operation costs of active distribution network by controlling the energy storage and controllable distributed generation, such as the diesel engine and micro turbine (MT). Based on the optimal dispatch results in the day-ahead dispatch, the real-time dispatch deals with the forecast error of renewable energy and loads, considering the costs of adjusting the ESS and diesel engine plan based on the realized scenarios. An improved particle swarm optimization (PSO) algorithm is adopted to solve the models. Finally, the feasibility and effectiveness of the proposed strategy is verified through the simulation examples.
机译:近年来,大规模可再生能源接入电力系统对有源配电网的能源管理和稳定运行提出了巨大的挑战。基于负荷预测和间歇性能源输出预测,建立了多时间尺度下的两阶段多源协调优化调度模型,以充分消耗大量的可再生能源,包括日间调度模型和实时调度模型。最优调度模型的优化目标是通过控制能量存储和可控的分布式发电(例如柴油机和微型涡轮机)来最小化主动配电网的运营成本。基于提前调度中的最佳调度结果,实时调度处理可再生能源和负荷的预测误差,并考虑根据实现的方案调整ESS和柴油发动机计划的成本。采用改进的粒子群算法(PSO)对模型进行求解。最后,通过仿真实例验证了所提策略的可行性和有效性。

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