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.
- Research Organization:
- NREL (National Renewable Energy Laboratory (NREL), Golden, CO (United States))
- Sponsoring Organization:
- NREL Laboratory Directed Research and Development (LDRD)
- DOE Contract Number:
- AC36-08GO28308
- OSTI ID:
- 1313618
- Report Number(s):
- NREL/CP-5D00-63748
- Country of Publication:
- United States
- Language:
- English
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