CAJ | 학술논문

以上海某园区微网为例，提出一种包含分布式能源、储能、可平移负荷3类电力资源的能源管理优化方法。该方法首先将可再生能源进行完全消纳，然后运用可控分布式能源、储能和可平移负荷对削减后的微网负荷进行第二轮优化。考虑到优化问题存在大量的非线性规划，提出分解迭代算法，将“源-荷-储”3类可控资源利用粒子群算法进行独立求解，并通过迭代使得整体解逼近全局最优解。同时，本系统针对微网预测困难，提出滚动优化方法，提高整体优化的准确性和实时性。算例结果验证了该方法的有效性。
이상해모완구미망위례，제출일충포함분포식능원、저능、가평이부하3류전력자원적능원관리우화방법。해방법수선장가재생능원진행완전소납，연후운용가공분포식능원、저능화가평이부하대삭감후적미망부하진행제이륜우화。고필도우화문제존재대량적비선성규화，제출분해질대산법，장“원-하-저”3류가공자원이용입자군산법진행독립구해，병통과질대사득정체해핍근전국최우해。동시，본계통침대미망예측곤난，제출곤동우화방법，제고정체우화적준학성화실시성。산례결과험증료해방법적유효성。
Taking a certain Sci-tech Park's microgrid in Shanghai as example, an energy source management optimization method, in which three electric power resources such as distributed generation, energy storage system and shiftable load are included, is proposed. In the proposed method firstly the output of renewable energy sources are fully consumed by the load in the park; then the controllable DGs, energy storage system and shiftable load are utilized to perform the second round optimization for the load that has been reduced. Considering the fact that there are a lot of non-linear programmings in the optimization problem, a decomposition iteration algorithm, which independently solves three kinds of controllable resources such as DG, load and energy storage by particle swarm optimization (PSO) to make the solutions of the three kinds of controllable resources closed to globally optimal solution through iterations, is put forward. Besides, in allusion to the difficulty in load prediction due to the randomness of the load in microgrid, a receding horizon optimization method is given to improve the accuracy and real-time of global optimization. The effectiveness of the given method is validated by the results of case calculation.