Open AccessOptimizing load variations using demand side management in the presence of SPV generation
Author(s) -
Preety Gupta,
Yajvender Pal Verma,
Deepak Kumar
Publication year - 2021
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/1033/1/012071
Subject(s) - deferral , load shifting , demand side , electricity , load profile , battery (electricity) , computer science , energy management , peak demand , load management , variance (accounting) , photovoltaic system , energy storage , distributed generation , power (physics) , automotive engineering , reliability engineering , environmental economics , energy (signal processing) , renewable energy , engineering , business , electrical engineering , economics , statistics , physics , mathematics , accounting , quantum mechanics
Demand Side Management (DSM) is a new concept that provides a viable and more efficient option to alter the net electricity consumption pattern without bringing much discomfort to the consumers. With the development of control and information technology, residential community provides a new potential demand side management entity to the distribution utilities to optimize their load profile. In this paper, the opportunities associated with Solar Photo Voltaic (SPV) integrated distribution utilities residential consumer DSM to minimize the gap between the targeted and actual load profile are investigated. A load deferral DSM model to shift the operation of not so critical residential appliances along with the optimal energy dispatch model from the residential consumer side battery energy storage (BES) is presented. A centrally controlled DSM strategy to optimize the operating time of deferrable devices and BES bidirectional power flow has been proposed. The DSM results considering different scenarios with and without BES and load deferral are compared with the original case of without DSM. It has been observed that the DSM strategy in the presence of SPVs and battery storage can substantially reduce the overall variance of the actual load curve from the predicted load curve.