Optimal Home Energy Demand Management Based Multi-Criteria Decision Making Methods

Dhiaa Halboot Muhsen,Haider Tarish Haider,Yaarob Al-Nidawi,Tamer Khatib

doi:10.3390/electronics8050524

Dhiaa Halboot Muhsen, Haider Tarish Haider + Show 2 more

Open Access

https://doi.org/10.3390/electronics8050524

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Abstract

From the growth of residential energy demands has emerged new approaches for load scheduling to realize better energy consumption by shifting the required demand in response to cost changes or incentive offers. In this paper, a hybrid method is proposed to optimize the load scheduling problem for cost and energy saving. The method comprises a multi-objective optimization differential evolution (MODE) algorithm to obtain a set of optimal solutions by minimizing the cost and peak of a load simultaneously, as a multi-objective function. Next, an integration of the analytic hierarchy process (AHP) and a technique for order preferences by similarity to ideal solution (TOPSIS) methods are used as multi-criteria decision making (MCDM) methods for sorting the optimal solutions’ set from the best to the worst, to enable the customer to choose the appropriate schedule time. The solutions are sorted based on the load peak and energy cost as multi-criteria. Data are for ten appliances of a household used for 24 h with a one-minute time slot. The results of the proposed method demonstrate both energy and cost savings of around 47% and 46%, respectively. Furthermore, the results are compared with other recent methods in the literature to show the superiority of the proposed method.

Highlights

The demand for energy consumption is rapidly growing due to an increase in the world wide population, urbanization, climate changes and technological developments [1]
A new load scheduling approach is proposed based on the hybridization of a multi-objective optimization algorithm and integrated multi-criteria decision making (MCDM) methods to obtain the optimal load scheduling for various appliances
A multi-objective optimization differential evolution (MODE) algorithm is presented to minimize the cost and peak of load simultaneously based on optimality of the Pareto front

Summary

Introduction

The demand for energy consumption is rapidly growing due to an increase in the world wide population, urbanization, climate changes and technological developments [1]. More devices have been added to the traditional customers’ devices list that place a high demand on the available generation capacity, such as electric vehicles [2,3]. The traditional solution for meeting the required energy demand is building new generation capacities [4,5]. Increasing the generation capacity faces many problems such as the depletion of fossil fuel, air pollution and climate change [6]. The new renewable energy resources such as photovoltaic (PV) and wind turbine have some barriers such as the intermittent problem and high initial cost [7,8]. The available varied pricing tariffs leads to the provision of flexible

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Results

Conclusion