Intensive quadratic programming approach for home energy management systems with power utility requirements

This paper proposes a model of a home energy management system (HEMS) to meet utility requirements while maximizing home profit. It contributes to intensify the flattening effects on the exchanging power pattern with a constraint of a fair profit reduction among households. The proposed method first uses a normal mixed-integer linear programming approach to find out the highest profit a household can get under a condition of a generous power limitation. It is highly possible that the resulted power aggregated from numerous homes may negatively affect power system operation such as violating voltage limits and overloading transformers. Based on that highest profit, the utility proposes the same percentage number of profit reduction for all households. Then, each HEMS performs an intensive mixed-integer quadratic programming optimization to flatten the selling and buying profiles whilst constraining the home profit reduction to the percentage set by the utility. A simulation shows that the peak power demand at the substation transformer would reduce about 44% if each household suffered a reduction of just 10% of the highest possible home profit. Since the flattening effects are improved if increasing the home profit reduction, our method is a basis for the utility to determine a compensation or alternative incentives to shave the peak-load and flatten the demand curve.