A Multiple-objective Neurodynamic Optimization to Electric Load Management Under Demand-Response Program

In a power system, a price-based demand-response program offers end electricity users time-varying prices, incentivizing them to shift demand from high-price hours to low-price hours during a day. Heating/cooling (H/C) loads are typical flexible loads to be shifted. Specifically, end users optimize the hourly H/C load to balance electricity costs and comfort. In this paper, a two-time-scale neurodynamic optimization approach is applied for this multi-objective optimization problem. As a result, optimal use of H/C loads is derived that yields significant savings and acceptable comfort. A case study of the Houston City is presented to show the effectiveness of the proposed neurodynamic approach.

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