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Open AccessArticle

A Cluster-Based Baseline Load Calculation Approach for Individual Industrial and Commercial Customer

1
School of Electrical Engineering, Southeast University, Nanjing 210096, China
2
Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham B15 2TT, UK
3
Guangzhou Power Supply Bureau Limited Company, Guangzhou 510620, China
*
Author to whom correspondence should be addressed.
Energies 2019, 12(1), 64; https://doi.org/10.3390/en12010064
Received: 29 October 2018 / Revised: 15 December 2018 / Accepted: 21 December 2018 / Published: 26 December 2018
(This article belongs to the Special Issue Demand Response in Electricity Markets)
Demand response (DR) in the wholesale electricity market provides an economical and efficient way for customers to participate in the trade during the DR event period. There are various methods to measure the performance of a DR program, among which customer baseline load (CBL) is the most important method in this regard. It provides a prediction of counterfactual consumption levels that customer load would have been without a DR program. Actually, it is an expected load profile. Since the calculation of CBL should be fair and simple, the typical methods that are based on the average model and regression model are the two widely used methods. In this paper, a cluster-based approach is proposed considering the multiple power usage patterns of an individual customer throughout the year. It divides loads of a customer into different types of power usage patterns and it implicitly incorporates the impact of weather and holiday into the CBL calculation. As a result, different baseline calculation approaches could be applied to each customer according to the type of his power usage patterns. Finally, several case studies are conducted on the actual utility meter data, through which the effectiveness of the proposed CBL calculation approach is verified. View Full-Text
Keywords: customer baseline load; individual customer; power usage patterns; demand response customer baseline load; individual customer; power usage patterns; demand response
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MDPI and ACS Style

Song, T.; Li, Y.; Zhang, X.-P.; Li, J.; Wu, C.; Wu, Q.; Wang, B. A Cluster-Based Baseline Load Calculation Approach for Individual Industrial and Commercial Customer. Energies 2019, 12, 64.

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