Scenario Analysis of Demand Response Using Artificial Electric Power Market Simulations

Masanori HIRANO; Ryo WAKASUI; Kiyoshi IZUMI

doi:10.52731/ijskm.v7.i2.770

Masanori HIRANO The University of Tokyo https://orcid.org/0000-0001-5883-8250
Ryo WAKASUI The University of Tokyo
Kiyoshi IZUMI The University of Tokyo

DOI: https://doi.org/10.52731/ijskm.v7.i2.770

Keywords: decarbonization, demand response, electric power market, multi-agent simulation

Abstract

We created and analyzed various Demand Response (DR) scenarios in the electric power market using multi-agent simulation. We first built a multi-agent simulation for the electric power market using actual data, including prices from the Japanese Electric Power Exchange (JEPX) market, electricity consumption in Japan, and an actual factory. Using this multi-agent simulation, we tested several possible DR scenarios for the factory. We then compared these scenarios using two newly defined indices for assessing the reduction efficiency of cost and CO2 emissions. The results showed that a work time shift in the summer and peak shift in factory demand in the winter were the best in terms of cost and CO2 emission reduction efficiencies. Thus, we demonstrated the usefulness of our multi-agent simulation for examining the effectiveness of DR scenarios by simulating complex interactions that consider the seasonal and time-of-day characteristics of power prices.

References

P. L. Joskow, “Introduction to electricity sector liberalization: lessons learned from cross-country studies,” Electricity market reform: an international perspective, vol. 1, pp. 1–32, 2006.

K. Hohki, “Outline of Japan Electric Power Exchange (JEPX),” IEEJ Transactions on Power and Energy, vol. 125, no. 10, pp. 922–925, 2005.

V. Masson-Delmotte, P. Zhai, H.-O. P ̈ortner, D. Roberts, J. Skea, P. R. Shukla, A. Pirani, W. Moufouma-Okia, C. P ́ean, R. Pidcock et al., “An IPCC Special Report on the impacts of global warming of Global warming of 1.5 °C,” 2018.

M. H. Albadi and E. F. El-Saadany, “A summary of demand response in electricity markets,” Electric Power Systems Research, vol. 78, no. 11, pp. 1989–1996, 2008.

A. Helleboogh, G. Vizzari, A. Uhrmacher, and F. Michel, “Modeling dynamic environments in multi-agent simulation,” Autonomous Agents and Multi-Agent Systems, vol. 14, no. 1, pp. 87–116, 2007.

H. Kitano and S. Tadokoro, “RoboCup Rescue: A Grand Challenge for Multiagent and Intelligent Systems,” AI Magazine, vol. 22, no. 1, pp. 39–39, 2001.

P. Trigo and P. Marques, “The electricity market as a multi-agent system,” in Proceedings of the 5th International Conference on the European Electricity Market. IEEE, 2008, pp. 1–6.

F. Sensfuß, “Assessment of the impact of renewable electricity generation on the German electricity sector: An agent-based simulation approach,” 2007, https://doi.org/10.5445/IR/100000777.

F. Sensfuß, M. Ragwitz, and M. Genoese, “The merit-order effect: A detailed analysis of the price effect of renewable electricity generation on spot market prices in Germany,” Energy Policy, vol. 36, no. 8, pp. 3086–3094, 2008.

O. Weiss, D. Bogdanov, K. Salovaara, and S. Honkapuro, “Market designs for a 100% renewable energy system: Case isolated power system of Israel,” Energy, vol. 119, pp.266–277, 2017.

S. Kan and Y. Shibata, “Study on FIP Policy Design by Using Multi-agent Based Electric Power Market Simulation Model,” 2020, https://eneken.ieej.or.jp/en/reportdetail.php?article info id=8918.

A. S. Chuang, F. Wu, and P. Varaiya, “A game-theoretic model for generation expansion planning: Problem formulation and numerical comparisons,” IEEE Transactions on Power Systems, vol. 16, no. 4, pp. 885–891, 2001.

C. J. Day and D. W. Bunn, “Divestiture of Generation Assets in the Electricity Pool of England and Wales: A Computational Approach to Analyzing Market Power,” Journal of Regulatory Economics, vol. 19, no. 2, pp. 123–141, 2001.

Y. Jiang, K. Zhou, X. Lu, and S. Yang, “Electricity trading pricing among prosumers with game theory-based model in energy blockchain environment,” Applied Energy, vol. 271, p. 115239, 2020.

M. Ghaffari, A. Hafezalkotob, and A. Makui, “Analysis of implementation of Tradable Green Certificates system in a competitive electricity market: A game theory approach,” Journal of Industrial Engineering International, vol. 12, no. 2, pp. 185–197, 2016.

J. K. Kok, C. J. Warmer, and I. G. Kamphuis, “PowerMatcher: multiagent control in the electricity infrastructure,” in Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, 2005, pp. 75–86.

H. S. Oh and R. J. Thomas, “Demand-side bidding agents: Modeling and simulation,”IEEE Transactions on Power Systems, vol. 23, no. 3, pp. 1050–1056, 2008.

Z. Zhou, F. Zhao, and J. Wang, “Agent-based electricity market simulation with demand response from commercial buildings,” IEEE Transactions on Smart Grid, vol. 2, no. 4, pp. 580–588, 2011.

T. Torii, K. Izumi, and K. Yamada, “Shock transfer by arbitrage trading: analysis using multi-asset artificial market,” Evolutionary and Institutional Economics Review, vol. 12, no. 2, pp. 395–412, 2015.