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Title: Stochastic Optimal Scheduling of Residential Appliances with Renewable Energy Sources

This paper proposes a stochastic, multi-objective optimization model within a Model Predictive Control (MPC) framework, to determine the optimal operational schedules of residential appliances operating in the presence of renewable energy source (RES). The objective function minimizes the weighted sum of discomfort, energy cost, total and peak electricity consumption, and carbon footprint. A heuristic method is developed for combining different objective components. The proposed stochastic model utilizes Monte Carlo simulation (MCS) for representing uncertainties in electricity price, outdoor temperature, RES generation, water usage, and non-controllable loads. The proposed model is solved using a mixed integer linear programming (MILP) solver and numerical results show the validity of the model. Case studies show the benefit of using the proposed optimization model.
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Resource Relation:
Conference: Presented at the 2015 IEEE Power and Energy Society General Meeting, 26-30 July 2015, Denver, Colorado
Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE)
Research Org:
NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States))
Sponsoring Org:
NREL Laboratory Directed Research and Development (LDRD)
Country of Publication:
United States
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION home energy management system; mixed integer linear programming; stochastic optimization; Monte Carlo simulation; renewable energy sources