Heuristic optimization for an aggregator-based resource allocation in the smart grid
Heuristic optimization for an aggregator-based resource allocation in the smart grid
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DOI：
10.1109/pesgm.2016.7741095
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发表时间：
2016-07
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通讯作者：
T. Hansen;Robin Roche;Siddharth Suryanarayanan;A. A. Maciejewski-A.;H. Siegel
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作者：
T. Hansen;Robin Roche;Siddharth Suryanarayanan;A. A. Maciejewski-A.;H. Siegel
我们利用基于营利性聚合器的住宅需求响应 (DR) 方法来解决智能电网资源分配问题。使用一组给定的可调度住宅客户资产（例如智能电器）的聚合实体必须设置一个时间表来优化给定的目标。在这里，我们考虑针对聚合商的利润进行优化。为了鼓励客户参与住宅灾难恢复计划，提出了一种名为客户激励定价（CIP）的新定价结构。聚合器利润使用建议的启发式框架进行优化，该框架以遗传算法的形式实现，必须确定客户资产和 CIP 的时间表。为了验证我们的启发式框架，我们使用 24 小时内的真实定价数据来模拟由 5555 个住宅客户家庭和 56 642 个可调度资产组成的大型系统的优化。我们表明，通过纯粹出于经济原因进行优化，聚合器可以对整个电力系统的负载状况做出有益的改变。
We utilize a for-profit aggregator-based residential demand response (DR) approach to the smart grid resource allocation problem. The aggregator entity, using a given set of schedulable residential customer assets (e.g., smart appliances), must set a schedule to optimize for a given objective. Here, we consider optimizing for the profit of the aggregator. To encourage customer participation in the residential DR program, a new pricing structure named customer incentive pricing (CIP) is proposed. The aggregator profit is optimized using a proposed heuristic framework, implemented in the form of a genetic algorithm, that must determine a schedule of customer assets and the CIP. To validate our heuristic framework, we simulate the optimization of a large-scale system consisting of 5555 residential customer households and 56 642 schedulable assets using real pricing data over a period of 24-h. We show that by optimizing purely for economic reasons, the aggregator can enact a beneficial change on the load profile of the overall power system.