Multi-objective optimization of household appliance scheduling problem considering consumer preference and peak load reduction

Abstract This paper addresses the load scheduling problem in residential sector while considering preferences of consumers and reduction of peak load. This study proposes an optimization model using multi-objective mixed integer linear programming considering a time-of-use (ToU) electricity tariff. Furthermore, this study considers the coordinated peak load reduction in a multiple-household environment. The proposed model aims to minimize three objectives: the electricity cost, the scheduling inconvenience and the peak load. Considering three objectives could enable consumers and utility companies to control their priority in minimizing one over the others. Three multi-objective optimization approaches are applied to solve the proposed model: normalized weighted-sum approach, preemptive optimization and compromise optimization. Numerical experiments show that the proposed solutions lead to significant savings in electricity costs, eliminate consumer inconvenience, while reducing the system peak loading. Furthermore, the results show outstanding performance when compared against three schedules from the literature and the consumer’s preferred schedule. Moreover, the coordinated schedules for the multiple-household problem lead to a significant reduction and levelling of the aggregated peak load.

[1]  Marco L. Della Vedova,et al.  Electric load management approaches for peak load reduction: A systematic literature review and state of the art , 2016 .

[2]  Kelum A. A. Gamage,et al.  Demand side management in smart grid: A review and proposals for future direction , 2014 .

[3]  Abdellatif Miraoui,et al.  Electric energy management in residential areas through coordination of multiple smart homes , 2017 .

[4]  Thillainathan Logenthiran,et al.  Demand Side Management in Smart Grid Using Heuristic Optimization , 2012, IEEE Transactions on Smart Grid.

[5]  Tamer Khatib,et al.  Domestic load management based on integration of MODE and AHP-TOPSIS decision making methods , 2019, Sustainable Cities and Society.

[6]  Ahmad Faruqui,et al.  Toward a New Paradigm for Valuing Demand Response , 2006 .

[7]  Milan Zelany,et al.  A concept of compromise solutions and the method of the displaced ideal , 1974, Comput. Oper. Res..

[8]  Jared L. Cohon,et al.  Multiobjective programming and planning , 2004 .

[9]  P. Yu Multiple-Criteria Decision Making: "Concepts, Techniques, And Extensions" , 2012 .

[10]  P. Yu A Class of Solutions for Group Decision Problems , 1973 .

[11]  P. Warren A review of demand-side management policy in the UK , 2014 .

[12]  Chongqing Kang,et al.  Review and prospect of integrated demand response in the multi-energy system , 2017 .

[13]  Leehter Yao,et al.  Real-Time Energy Management Optimization for Smart Household , 2016, 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[14]  Oleksandr Romanko,et al.  Normalization and Other Topics in Multi­Objective Optimization , 2006 .

[15]  Marco L. Della Vedova,et al.  Applying limited-preemptive scheduling to peak load reduction in smart buildings , 2015, 2015 IEEE 20th Conference on Emerging Technologies & Factory Automation (ETFA).

[16]  Akos Baldauf A smart home demand-side management system considering solar photovoltaic generation , 2015, 2015 5th International Youth Conference on Energy (IYCE).

[17]  Pierluigi Siano,et al.  Demand response and smart grids—A survey , 2014 .

[18]  Marco L. Della Vedova,et al.  Peak shaving through real-time scheduling of household appliances , 2014 .

[19]  J. Torriti A review of time use models of residential electricity demand , 2014 .

[20]  Ong Hang See,et al.  A review of residential demand response of smart grid , 2016 .

[21]  Nadeem Javaid,et al.  An Energy Efficient Residential Load Management System for Multi-class Appliances in Smart Homes , 2015, 2015 18th International Conference on Network-Based Information Systems.

[22]  Haider Tarish Haider,et al.  Optimal residential load scheduling based on time varying pricing scheme , 2015, 2015 IEEE Student Conference on Research and Development (SCOReD).

[23]  Hanife Apaydin Özkan,et al.  A home power management system using mixed integer linear programming for scheduling appliances and power resources , 2016, 2016 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe).

[24]  Xiao-Ping Zhang,et al.  Real-Time Scheduling of Residential Appliances via Conditional Risk-at-Value , 2014, IEEE Transactions on Smart Grid.

[25]  Yan Shi,et al.  Multiobjective optimization technique for demand side management with load balancing approach in smart grid , 2016, Neurocomputing.

[26]  H. Vincent Poor,et al.  Prioritizing Consumers in Smart Grid: A Game Theoretic Approach , 2013, IEEE Transactions on Smart Grid.

[27]  G Hamed Shakouri,et al.  Multi-objective cost-load optimization for demand side management of a residential area in smart grids , 2017 .

[28]  Shuai Lu,et al.  Robust scheduling of smart appliances with uncertain electricity prices in a heterogeneous population , 2014 .

[29]  Karl Henrik Johansson,et al.  Scheduling smart home appliances using mixed integer linear programming , 2011, IEEE Conference on Decision and Control and European Control Conference.

[30]  Gengyin Li,et al.  Optimal residential community demand response scheduling in smart grid , 2018 .

[31]  Anup Pradhan,et al.  Optimal load scheduling of household appliances considering consumer preferences: An experimental analysis , 2018, Energy.

[32]  Álvaro Gomes,et al.  A multi-objective genetic approach to domestic load scheduling in an energy management system , 2014 .

[33]  Jiangfeng Zhang,et al.  Optimal scheduling of household appliances for demand response , 2014 .

[34]  Anna Alberini,et al.  Response of residential electricity demand to price: The effect of measurement error , 2011 .

[35]  Xiaohua Xia,et al.  Corrigendum to “Optimal scheduling of household appliances for demand response” [Electr. Power Syst. Res. 116 (November) (2014) 24–28] , 2016 .

[36]  X. Xia,et al.  Combined residential demand side management strategies with coordination and economic analysis , 2016 .

[37]  Jianzhong Wu,et al.  Robust-Index Method for Household Load Scheduling Considering Uncertainties of Customer Behavior , 2015, IEEE Transactions on Smart Grid.

[38]  Xiaohua Xia,et al.  Optimal scheduling of household appliances with a battery storage system and coordination , 2015 .

[39]  Xiaohua Xia,et al.  Optimal Scheduling of Household Appliances Incorporating Appliance Coordination , 2014 .