Stochastic Optimal Scheduling of Residential Appliances with Renewable Energy Sources

Hongyu Wu, Annabelle Pratt, Sudipta Chakraborty

Research output: Contribution to conferencePaperpeer-review

35 Scopus Citations

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 languageAmerican English
Number of pages5
DOIs
StatePublished - 30 Sep 2015
EventIEEE Power and Energy Society General Meeting, PESGM 2015 - Denver, United States
Duration: 26 Jul 201530 Jul 2015

Conference

ConferenceIEEE Power and Energy Society General Meeting, PESGM 2015
Country/TerritoryUnited States
CityDenver
Period26/07/1530/07/15

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

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