Smart energy‐consumption management system considering consumers' spending goals (SEMS‐CCSG). (11th December 2015)

• Record Type: Journal Article
• Authors: Yaqub, Raziq; Ahmad, Sadiq; Ahmad, Ayaz; Amin, Muhammad
• Is Part Of: International transactions on electrical energy systems. Volume 26:Number 7(2016:Oct.)
• Page Start: 1570
• Page End: 1584
• Publication Date: 2015-12-11
• Subjects: smart grid -- demand side management -- energy consumption controller and scheduler (ECS) -- remote applications servers (RAS) -- local applications servers (LAS) -- relays panel; Electric power -- Periodicals; Electric power systems -- Periodicals; Electrical engineering -- Periodicals; 621.3
• DOI: 10.1002/etep.2167
• Languages: English
• ISSNs: 2050-7038

Abstract

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.