Impact of Time-of-Use Demand Response Program on Optimal Operation of Afghanistan Real Power System

Mohammad Masih Sediqi, Akito Nakadomari, Alexey Mikhaylov, Narayanan Krishnan, Mohammed Elsayed Lotfy, Atsushi Yona and Tomonobu Senjyu
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Mohammad Masih Sediqi: Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
Akito Nakadomari: Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
Narayanan Krishnan: Department of Electrical and Electronics Engineering, SASTRA Deemed University, Thanjavur 613401, India
Mohammed Elsayed Lotfy: Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
Atsushi Yona: Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan
Tomonobu Senjyu: Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara-cho, Nakagami, Okinawa 903-0213, Japan

Energies, 2022, vol. 15, issue 1, 1-21

Abstract: Like most developing countries, Afghanistan still employs the traditional philosophy of supplying all its load demands whenever they happen. However, to have a reliable and cost-effective system, the new approach proposes to keep the variations of demand at the lowest possible level. The power system infrastructure requires massive capital investment; demand response (DR) is one of the economic options for running the system according to the new scheme. DR has become the intention of many researchers in developed countries. However, very limited works have investigated the employment of appropriate DR programs for developing nations, particularly considering renewable energy sources (RESs). In this paper, as two-stage programming, the effect of the time-of-use demand response (TOU-DR) program on optimal operation of Afghanistan real power system in the presence of RESs and pumped hydropower storage (PHS) system in the day-ahead power market is analyzed. Using the concept of price elasticity, first, an economic model indicating the behaviour of customers involved in TOU-DR program is developed. A genetic algorithm (GA) coded in MATLAB software is used accordingly to schedule energy and reserve so that the total operation cost of the system is minimized. Two simulation cases are considered to verify the effectiveness of the suggested scheme. The first stage programming approach leads case 2 with TOU-DR program to 35 MW (811 MW − 776 MW), $16,235 ($528,825 − $512,590), and 64 MW reductions in the peak load, customer bill and peak to valley distance, respectively compared to case 1 without TOU-DR program. Also, the simulation results for stage 2 show that by employing the TOU-DR program, the system’s total cost can be reduced from $317,880 to $302,750, which indicates a significant reduction in thermal units’ operation cost, import power tariffs and reserve cost.

Keywords: time-of-use demand response; optimal operation; price elasticity; renewable energy sources; genetic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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