Customer baseline load models for residential sector in a smart-grid environment

R Sharifi,V Vahidinasab,S.H Fathi

doi:10.1016/j.egyr.2016.04.003

R Sharifi, V Vahidinasab + Show 1 more

Open Access

https://doi.org/10.1016/j.egyr.2016.04.003

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Abstract

Abstract Demand response (DR) can expand the customer participation in the electricity market and lead by changing its pattern from a simple function to an interactive relation. There are various methods to evaluate the successful implementation of DR program, the most important of which is determination of customer baseline load (CBL). In fact, CBL is the expected pattern of customer consumption in the absence of DR programs. Few works have been done in the field of calculation of CBL in residential sector, while most of them have paid little attention to the impact of changes in weather conditions on these calculations. In this paper, a new method is presented for the calculation of CBL for customers in residential sector in the context of a smart grid, considering the impact of weather changes. The results clearly show the high impact of changes in weather conditions on the calculation of CBL, and also show the extent of effect of buildings’ improved insulation on this parameter. It is also indicated that implementing DR programs can increase the willingness of customers in residential sector to improve the insulations of their buildings.

Highlights

Until recent years, the activities of wholesale electricity markets were limited to electricity power generation companies, who were competing to gain a higher share of the market and increase their profits
These loads can be divided into two categories based on their characteristics: Deferrable loads (DL), and Loads based on temperature (BT)
A dynamic method was presented for calculating customer baseline load (CBL) for customers of residential sector by considering the impact of weather conditions on power consumption

Summary

Introduction

The activities of wholesale electricity markets were limited to electricity power generation companies, who were competing to gain a higher share of the market and increase their profits. The demand side had little activity due to lack of adaptability to this new environment. This inactivity in demand side led to the greed of supply side which resulted in an increase in prices. This price increase alerted the demand side and caused it to look for strategies to come out of this passivity, which in turn led to the emergence of a broad discussion in electricity markets called the Demand Side Management (DSM). Demand response is the process of managing consumers’ consumption in response to the supply conditions with the aim of reducing electricity costs and improving system reliability (Yin et al, 2010)

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