Abstract
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.
| Original language | American English |
|---|---|
| Number of pages | 5 |
| DOIs | |
| State | Published - 30 Sep 2015 |
| Event | IEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States Duration: 26 Jul 2015 → 30 Jul 2015 |
Conference
| Conference | IEEE Power and Energy Society General Meeting, PESGM 2015 |
|---|---|
| Country/Territory | United States |
| City | Denver |
| Period | 26/07/15 → 30/07/15 |
Bibliographical note
Publisher Copyright:© 2015 IEEE.
NREL Publication Number
- NREL/CP-5D00-63748
Keywords
- Home energy management system
- mixed integer linear programming
- Monte Carlo simulation
- renewable energy sources
- stochastic optimization
