스마트 그리드에 있어서 저장 장치를 고려한 최적 에너지 소비 스케줄링 = 게임 이론적 접근

다국어 초록 (Multilingual Abstract)

In this research, we consider a smart grid network of electricity with multiple consumers connected to a monopolistic provider. Each consumer can be informed the real time price changes through the smart meter and updates his consumption schedule to minimize the energy consumption expenditures by which the required power demand should be satisfied under the given real time pricing scheme. This real-time decision making problem has been recently studied through game-theoretic approach. The present paper contributes to the existing literature by incorporating storage appliance into the set of available household appliances which has somewhat distinctive functions compared to other types of appliances and would be regarded to play a significant role in energy consumption scheduling for the future smart grid. We propose a game-theoretic algorithm which could draw the optimal energy consumption scheduling for each household appliances including storage. Results on simulation data showed that the storage contributed to increase the efficiency of energy consumption pattern in the viewpoint of not only individual consumer but also whole system.

참고문헌 (Reference)

1 김태완, "수요 반응에서 가정용 전력기계의 최적화된 스케쥴링 기법" 한국통신학회 35 (35): 1407-1415, 2010

2 문용마, "소비자 행동과 가격탄성을 고려한 스마트 그리드 수요반응 실시간 가격 결정 모델" 한국경영과학회 39 (39): 49-67, 2014

3 Centolella, P., "The integration of price responsive demand into regional transmission organization (RTO) wholesale power markets and system operations" 35 (35): 1568-1574, 2010

4 Lee, M., "The current state and the prospect of smart grid market" The Export-Import Bank of Korea 2012

5 Park, K., "Scheduling problem for energy efficiency optimization in smart grid" 1187-1206, 2012

6 Conejo, A. J., "Real-time demand response model" 1 (1): 236-242, 2010

7 Samadi, P., "Optimal real-time pricing algorithm based on utility maximization for smart grid" 415-420, 2010

8 Saad, W., "Game-Theoretic Methods for the Smart Grid : An Overview of Microgrid Systems, Demand-Side Management, and Smart Grid Communications" 29 (29): 86-105, 2012

9 Fudenberg, D, "Game Theory" MIT Press 1991

10 Rosen, J. B., "Existence and uniqueness of equilibrium points for concave n-person games" 33 : 347-351, 1965

11 Wade, N. S., "Evaluating the benefits of an electrical energy storage system in a future smart grid" 38 : 7180-7188, 2010

12 Triki, C, "Dynamic pricing of electricity in retail markets" 7 (7): 21-S36, 2009

13 Boyd, S., "Convex Optimization" Cambridge University Press 2004

14 Mohsenian-Rad, A. H., "Autonomous Demand-Side Management Based on Game-Theoretic Energy Consumption Scheduling for the Future Smart Grid" 1 (1): 320-331, 2010

15 Vytelingum, P., "Agent-based Micro-Storage Management for the Smart Grid" 39-46, 2010

16 Gomes, A., "A multiple objective approach to direct load control using an interactive evolutionary algorithm" 22 (22): 1004-1011, 2007

17 Bu, S., "A game-theoretical decision-making scheme for electricity retailers in the smart grid with demand-side management" 387-391, 2011

18 Ruiz, N., "A direct load control model for virtual power plant management, IEEE Trans" 24 (24): 959-966, 2009

19 Choi, T., "A Study on Energy Cost Saving Strategy in the Smart Grid Environment" 517-518, 2010