Energy Flexibility Management Based on Predictive Dispatch Model of Domestic Energy Management System

Amin Shokri Gazafroudi, Francisco Prieto-Castrillo, Tiago Pinto, Javier Prieto, Juan Manuel Corchado and Javier Bajo
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Amin Shokri Gazafroudi: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
Francisco Prieto-Castrillo: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
Tiago Pinto: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
Javier Prieto: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
Juan Manuel Corchado: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain
Javier Bajo: BISITE Research Group, University of Salamanca, Edificio I+D+i, 37008 Salamanca, Spain

Energies, 2017, vol. 10, issue 9, 1-16

Abstract: This paper proposes a predictive dispatch model to manage energy flexibility in the domestic energy system. Electric Vehicles (EV), batteries and shiftable loads are devices that provide energy flexibility in the proposed system. The proposed energy management problem consists of two stages: day-ahead and real time. A hybrid method is defined for the first time in this paper to model the uncertainty of the PV power generation based on its power prediction. In the day-ahead stage, the uncertainty is modeled by interval bands. On the other hand, the uncertainty of PV power generation is modeled through a stochastic scenario-based method in the real-time stage. The performance of the proposed hybrid Interval-Stochastic (InterStoch) method is compared with the Modified Stochastic Predicted Band (MSPB) method. Moreover, the impacts of energy flexibility and the demand response program on the expected profit and transacted electrical energy of the system are assessed in the case study presented in this paper.

Keywords: decision-making under uncertainty; domestic energy management system; energy flexibility; interval optimization; stochastic programming (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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