Cuckoo Search Optimization Technique for Multi-objective Home Energy Management

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 612)


Increasing demand of power and emergence of smart grid has gain maximum attention of researchers which has further opened new opportunities for Home Energy Management System (HEMS). HEMS under Demand Response (DR) helps to reduce the On-peak hour load by shifting the load toward the Off-peak hours. This load shifting strategy effects the user comfort, however in return DR gives them incentives in term of electricity bill reduction. Consumer electricity cost and peak load have a tradeoff, to sort out this situation an efficient system is required. In this paper, we present a multi-objective HEMS to schedule home appliances using Cuckoo Search Algorithm (CSA) while considering the objective load fitness criteria. This proposed load fitness criteria effectively reduces the cost and peak load. Simulations are performed to verify the generic behavior i.e., system performance on any price tariffs. For this purpose, results are validated for three price signals: day-ahead Real Time Peak Price (RTP), Time of Use (TOU) and Critical Peak Price (CPP).


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  1. 1.COMSATS Institute of Information TechnologyIslamabadPakistan
  2. 2.Computer Information Science, Higher Colleges of TechnologyFujairahUnited Arab Emirates
  3. 3.Cameron Library, University of AlbertaEdmontonCanada

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