Optimal Planning of Residential Microgrids Based on Multiple Demand Response Programs Using ABC Algorithm

Habib Ur Rahman Habib, Asad Waqar, Abdul Khalique Junejo, Moustafa Magdi Ismail, Monir Hossen, Mehdi Jahangiri, Asif Kabir, Sheheryar Khan, Yun Su Kim

Research output: Contribution to journalArticlepeer-review


The smart grid has revolutionized the conventional electricity grid with the proposition of demand-side management (DSM). A DSM program enables the user to schedule its energy consumption in compliance with any pricing signal. This scheduling helps the grid operator to reduce the peak load demand and jointly benefits the user to reduce its electricity costs. Despite that, while doing so, it jeopardizes the user's comfort. In the present paper, the authors have investigated the impact of communal DSM programs on the consumption patterns of users, including single as well as multiple households. The objective is to simultaneously minimize the electricity costs and user discomfort to make a win-win situation for both the grid operator and the user. Therefore, a multi-objective optimization problem (MOOP) has been formed to simultaneously minimize the daily electricity cost, peak to average ratio (PAR) of load demand, user discomfort, environmental emission, and total net present cost (TNPC). In order to evaluate the best scheduling method, sizing scenarios for a residential microgrid in a Southern Pakistani metropolis surrounded by rural areas are presented in this paper. The originality of this article comes from a comparison of the techno-economic and environmental performance of several sizing options for a residential load powered by renewable energy. The artificial bee colony (ABC) algorithm has been selected to solve the MOOP. The DSM programs are based upon different pricing signals, including real-time electricity pricing (RTEP), critical peak pricing (CPP), time of use (TOU), and day-ahead pricing (DAP) pricing. The results of the proposed ABC algorithm are compared with GA and standard algorithms, and they reveal the effectiveness of the proposed method. When demand response is used, the suggested optimization technique shows that the SH spring with PV/WG/grid-connected microgrid is the most investable-reliable sizing option with a minimal TNPC of 1405.18 for DAP tariff with SH spring. Additionally, with a reduction in emissions of 6699 kg/yr, DAP tariff with SH spring shows that PV/WG/DG/grid-connected system has the greatest impact on the environment. For DAP tariff with SH spring, optimal sizes of PV, WG and converter are 26.7 kW, 30 kW and 6.67 kW, respectively.

Original languageEnglish
Pages (from-to)116564-116626
Number of pages63
JournalIEEE Access
Publication statusPublished - 2022


  • ABC algorithm
  • CPP
  • DAP
  • Demand side management
  • RTEP
  • TOU
  • electricity cost
  • environmental emission
  • genetic algorithm
  • load shifting
  • multi-objective optimization
  • optimal operation
  • peak to average ratio
  • residential microgrid
  • user comfort


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