A Robust Optimization Approach for Demand Side Scheduling Considering Uncertainty of Manually Operated Appliances
A Robust Optimization Approach for Demand Side Scheduling Considering Uncertainty of Manually Operated Appliances
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DOI：
10.1109/tsg.2016.2564159
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发表时间：
2018-03
影响因子：
9.6
通讯作者：
Yuefang Du;Lin Jiang;Yuanzheng Li;Qinghua Wu
中科院分区：
文献类型：
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作者：
Yuefang Du;Lin Jiang;Yuanzheng Li;Qinghua Wu
手动操作设备（MOA）是基于用户的实时需求手动操作的，并且其能量消耗对于其他可替换设备（SA）是不确定的。由于MOA的不确定性分布通常是未知的，且不易估计，本文将MOA不确定性下的家电能耗调度问题描述为鲁棒优化问题。在MOA所有可能的能源消耗情况下，鲁棒方法考虑了最坏的情况下，以减少所有家用电器的电费，基于实时电价方案结合倾斜的块率。采用代间投影进化算法求解鲁棒优化问题，该算法是一种内部遗传算法和外部粒子群优化算法相结合的嵌套启发式算法。案例研究是基于一天的情况下，一个月的情况下，各种组合的SA和MOA。仿真结果表明，与不考虑MOA不确定性的方法和考虑固定模式MOA的方法相比，该方法在降低电费方面是有效的。
Manually operated appliances (MOAs) are manually operated based on users’ real-time demands and their energy consumption is uncertain to other schedulable appliances (SAs). This paper represents energy consumption scheduling of home appliances under the uncertainty of the MOAs as a robust optimization problem, as uncertainty distribution of MOAs is usually unknown and not easily estimated. Among all possible energy consumption cases of the MOAs, the robust approach takes into account the worst case to reduce electricity payment of all home appliances, based on the real-time electricity pricing scheme combined with inclining block rate. Intergeneration projection evolutionary algorithm, which is a nested heuristic algorithm with inner genetic algorithm and outer particle swarm optimization algorithm, is adopted to solve the robust optimization problem. Case studies are based on one day case, and one month case with various combinations of SAs and MOAs. Simulation results illustrate the effectiveness of the proposed approach in reduction of electricity payment compared with the approach without considering the uncertainty of MOAs, and the approach considering MOAs with fixed pattern.