
Smart energy‐consumption management system considering consumers' spending goals (SEMS‐CCSG)
Author(s) -
Yaqub Raziq,
Ahmad Sadiq,
Ahmad Ayaz,
Amin Muhammad
Publication year - 2016
Publication title -
international transactions on electrical energy systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.428
H-Index - 42
ISSN - 2050-7038
DOI - 10.1002/etep.2167
Subject(s) - smart grid , incentive , electricity , environmental economics , consumption (sociology) , energy management , energy consumption , energy management system , demand response , computer science , stability (learning theory) , grid , operations research , energy (signal processing) , economics , engineering , microeconomics , social science , statistics , geometry , mathematics , machine learning , sociology , electrical engineering
Summary The goal of this paper is to optimize energy consumption, with minimum consumer interaction, and least impact on his/her life style, comfort and convenience. In the literature different demand side management (DSM) schemes are employed for consumer demand management. Till now, to the best of our knowledge none of researchers considered the consumers preferences, priorities, ease of use, grid stability, deviation minimization, demand curve flattening and implantation cost, collectively in a single management scheme. In this paper we proposed an innovative, cost‐effective solution, to overcome most of the shortcomings of the previous solutions. In addition, it would also provide consumers' privacy as it would mask the energy usage pattern that combines psychological incentives in addition to economic benefits. The proposed Smart Energy‐consumption Management System Considering Consumers' Spending Goal (SEMS‐CCGS) can be used for optimized electricity consumption at any premises (residential, enterprise, commercial, etc.). The preliminary simulations showed 25.6% of electricity cost saving using SEMS‐CCGS. The proposed system is appraised valuable by the utility companies whose focus is to shave peak loads. It also plays an important role in grid stability by improving the diversity factor and deviation of consumers load profile from available load curve. The simulation shows that deviation is minimized up to 45%. Copyright © 2015 John Wiley & Sons, Ltd.