Vijayalakshmi Anbazhagan
Department of Electrical Engineering, IIT-M, Chennai-600036
K. Shanti Swarup
Department of Electrical Engineering, IIT-M, Chennai-600036
Haile- Selassie Rajamani
Engineering and Informatics, University of Bradford, BD7 1DP
Prashant Pillai
Engineering and Informatics, University of Bradford, BD7 1DP
Abstract
Virtual Power Plant (VPP) is an important desired new comer to the electricity market. The objective of VPP is to supply green energy by integrating Renewable Energy Sources (RES) like wind and solar, etc., optimize the grid stability, enable customers to participate flexibly in the market operation and maximize the VPP profit. A VPP may consist of number of customers. Handling them as an individual is a difficult task to VPP operator, hence, electricity customer segmentation based on their demand becomes crucial. Nowadays, customers are becoming producers (called as prosumers), VPP helps to plan power transaction from prosumers and/or grid to reduce the loss and congestion, etc. In this paper, a new method has been proposed for electricity customer segmentation and the results are compared with K-means clustering method as well. Electricity customer segmentation plays a vital role in dispatching scheduled power, prioritize the customers in an emerging situation, tariff design, demand response, voltage regulation and planning power transaction from prosumer and/or generation, etc. Here, the segmentation has been used for tariff design.