基于改进细菌群体趋药性算法的风-蓄-火联合调度的研究

Research on Joint Dispatch of Wind-Storage-Thermal System Based on Improved Bacterial Colony Chemotaxis Algorithm

由于风电功率波动性大,直接接入电网会给电网安全运行带来很大的风险。针对风电出力的随机性,在风电预测的基础上,结合抽水蓄能削峰填谷的特点,提出了风-蓄-火联合系统日前和时前调度策略,日前调度阶段以风—蓄—火联合调度获取最大经济效益为目标函数,采用改进的细菌群体趋药性算法进行优化,得到风、蓄、火的日前出力计划。时前调度阶段对日前阶段的机组出力进行修正,首先在满足抽水蓄能、满足约束条件的情况下,修正抽水蓄能的出力,再修正火电机组的出力,修正目标是以火电机组的运行成本最小。最后,以含风电场的算例对该模型进行了验证,仿真结果表明了所提出的调度策略具有一定的可行性。

Because the wind power has a severe fluctuation, and it can bring great risk to the safety of power grid if it is direct- ly connected to power grid. According to the randomness of wind power, based on the wind power prediction and combined with the characteristics of the pumped storage, a two - stage coordinated joint dispatch strategy for wind farm and pumped - storage power station is proposed, which is consisted of day - ahead dispatch and hour - ahead dispatch. The day - ahead dis- patching model takes the maximum economic benefits of the wind - storage - thermal joint operation as the objective, and it is optimized by the improved bacterial colony chemotaxis algorithm, so the day - ahead output of wind - storage - thermal is known. In hour - ahead dispatch stage, according to the results of short - term wind power prediction the planning power is constantly revised. Firstly, based on the satisfied constraint condition of pumped - storage unit, the output of pumped - stor- age unit is revised. Secondly, the output of thermoelectric generating set is revised. The objective is to make the cost of the operation of thermoelectric generating set minimum. Finally, the model is verified by an example containing wind farms, and the simulation results show that the proposed dispatching strategy is feasible.