Abstract
When energy meets information, smart grid, also known as the Internet of energy, has been widely considered to be the informationization of the electric power system. As an essential characteristic of smart grid, demand side management can reschedule the users’ energy consumption to reduce the operating expense from expensive generators and further to defer the capacity addition in the long run. Considering the electricity price as an essential incentive to coordinate the real-time interaction among the power provider and consumers, in this chapter, we propose an optimal real-time pricing strategy for demand side management in smart grid. Firstly, we analytically model the power provider and consumers’ behaviors in form of cost and utility functions. Secondly, we propose distributed algorithms and show that real-time pricing can align individual optimality with systematic optimality. Finally, we also take account of the interaction among power consumers and formulate demand side management in smart grid as an interaction game with Nash equilibrium achievable via best response. Simulation results demonstrate that the proposed distributed algorithms can potentially benefit both the power provider and consumers. The optimal real-time pricing strategy can be utilized to address demand side management in smart grid towards the benefit of the overall system.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
L.T. Berger, K. Iniewski, Smart Grid Applications, Communications, and Security (Wiley, Hoboken, 2012)
S. Boyd, L. Vandenberghe, Convex Optimization (Cambridge University Press, Cambridge, 2004)
R. Deng, H. Liang, Whether to charge an electric vehicle or not? A near-optimal online approach, in Proceedings of IEEE power and energy society general meeting (PES-GM), 2016, pp. 1–5
R. Deng, H. Liang, Whether to charge or discharge an electric vehicle? An optimal approach in polynomial time, in Proceedings of IEEE Vehicular Technology Conference (VTC-fall), 2017, pp. 1–5
R. Deng, Z. Yang, Cooperative transmission game for smart grid communication, in Proceedings of IEEE International Conference on Control & Automation (ICCA), 2014, pp. 314–319
R Deng, S Maharjan, X Cao, J Chen, Y Zhang, S Gjessing, Sensing-delay tradeoff for communication in cognitive radio enabled smart grid, in Proceedings of IEEE International Conference on Smart Grid Communications (SmartGridComm), 2011, pp. 155–160
R. Deng, J. Chen, X. Cao, Y. Zhang, S. Maharjan, S. Gjessing, Sensing-performance tradeoff in cognitive radio enabled smart grid. IEEE Trans. Smart Grid 4(1), 302–310 (2013a)
R Deng, Z Yang, J Chen, Load scheduling with price uncertainty and coupling constraints, in Proceedings of IEEE Power & Energy Society General Meeting (PES-GM), 2013b, pp. 1–5
R. Deng, Z. Yang, J. Chen, N.R. Asr, M.Y. Chow, Residential energy consumption scheduling: A coupled-constraint game approach. IEEE Trans. Smart Grid 5(3), 1340–1350 (2014a)
R. Deng, Z. Yang, J. Chen, M.Y. Chow, Load scheduling with price uncertainty and temporally-coupled constraints in smart grids. IEEE Trans. Power Syst. 29(6), 2823–2834 (2014b)
R. Deng, G. Xiao, R. Lu, J. Chen, Fast distributed demand response with spatially and temporally coupled constraints in smart grid. IEEE Trans. Ind. Inf. 11(6), 1597–1606 (2015a)
R. Deng, Z. Yang, M.Y. Chow, J. Chen, A survey on demand response in smart grids: Mathematical models and approaches. IEEE Trans. Ind. Inf. 11(3), 570–582 (2015b)
R. Deng, Z. Yang, F. Hou, M.Y. Chow, J. Chen, Distributed real-time demand response in multiseller–multibuyer smart distribution grid. IEEE Trans. Power Syst. 30(5), 2364–2374 (2015c)
R Deng, Z Zhang, J Ren, H Liang, Indoor temperature control of cost-effective smart buildings via real-time smart grid communications, in Proceedings of IEEE Global Communications Conference (GLOBECOM), 2016, pp. 1–6
X. Fang, S. Misra, G. Xue, D. Yang, Smart grid — The new and improved power grid: A survey. IEEE Commun. Surv. Tutorials 14(4), 944–980 (2012)
D. Fudenberg, J. Tirole, Game Theory (MIT Press, Cambridge, 1991)
V.C. Gungor, D. Sahin, T. Kocak, S. Ergut, C. Buccella, C. Cecati, G.P. Hancke, Smart grid technologies: Communication technologies and standards. IEEE Trans. Ind. Inf. 7(4), 529–539 (2011)
V.C. Gungor, D. Sahin, T. Kocak, S. Ergut, C. Buccella, C. Cecati, G.P. Hancke, A survey on smart grid potential applications and communication requirements. IEEE Trans. Ind. Inf. 9(1), 28–42 (2013)
Y. Liu, R. Deng, H. Liang, Game-theoretic control of PHEV charging with power flow analysis. AIMS Energy 4(2), 379–396 (2016)
Y. Liu, R. Deng, H. Liang, A stochastic game approach for PEV charging station operation in smart grid. IEEE Trans. Ind. Inf. 14(3), 969–979 (2018)
J.A. Momoh, Smart Grid: Fundamentals of Design and Analysis (Wiley, Hoboken, 2012)
J.O. Neel, J.H. Reed, R.P. Gilles, Convergence of cognitive radio networks, in, Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), 2004, pp. 2250–2255
P. Palensky, D. Dietrich, Demand side management: Demand response, intelligent energy systems, and smart loads. IEEE Trans. Ind. Inf. 7(3), 381–388 (2011)
N. Rahbari-Asr, M.Y. Chow, J. Chen, R. Deng, Distributed real-time pricing control for large-scale unidirectional V2G with multiple energy suppliers. IEEE Trans. Ind. Inf. 12(5), 1953–1962 (2016)
J. Ren, J. Hu, R. Deng, D. Zhang, Y. Zhang, X.S. Shen, Joint load scheduling and voltage regulation in the distribution system with renewable generators. IEEE Trans. Ind. Inf. 14(4), 1564–1574 (2018)
A.I. Sabbah, A. El-Mougy, M. Ibnkahla, A survey of networking challenges and routing protocols in smart grids. IEEE Trans. Ind. Inf. 10(1), 210–221 (2014)
P. Samadi, A.H. Mohsenian-Rad, R. Schober, V.W. Wong, J. Jatskevich, Optimal real-time pricing algorithm based on utility maximization for smart grid, in Proceedings of IEEE International Conference on Smart Grid Communications (SmartGridComm), 2010, pp. 415–420
P. Siano, Demand response and smart grids-a survey. Renew. Sust. Energ. Rev. 30, 461–478 (2014)
M. Wang, H. Liang, R. Deng, R. Zhang, X.S. Shen, VANET based online charging strategy for electric vehicles. In: Proceedings of IEEE Global Communications Conference (GLOBECOM), 2013, pp 4804–4809
M. Wang, H. Liang, R. Zhang, R. Deng, X. Shen, Mobility-aware coordinated charging for electric vehicles in VANET-enhanced smart grid. IEEE J. Sel. Areas Commun. 32(7), 1344–1360 (2014)
P. You, S.H. Low, L. Zhang, R. Deng, G.B. Giannakis, Y. Sun, Z. Yang, Scheduling of EV battery swapping–part ii: Distributed solutions. IEEE Trans. Control Netw. Syst. 5(4), 1920–1930 (2018)
Z. Zhang, R. Deng, T. Yuan, S.J. Qin, Bi-level demand response game with information sharing among consumers. IFAC-PapersOnLine 49(7), 663–668 (2016)
Z. Zhang, R. Deng, T. Yuan, S.J. Qin, Distributed optimization of multi-building energy systems with spatially and temporally coupled constraints, in Proceedings of IEEE American Control Conference (ACC), 2017a, pp. 2913–2918
Z. Zhang, R. Deng, T. Yuan, S.J. Qin, Sliding window games for cooperative building temperature control using a distributed learning method. Front Eng. Manage. 4(3), 304–314 (2017b)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2022 Springer Nature Singapore Pte Ltd
About this entry
Cite this entry
Deng, R. (2022). Smart Grid and Demand Side Management. In: Tian, YC., Levy, D.C. (eds) Handbook of Real-Time Computing. Springer, Singapore. https://doi.org/10.1007/978-981-287-251-7_43
Download citation
DOI: https://doi.org/10.1007/978-981-287-251-7_43
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-287-250-0
Online ISBN: 978-981-287-251-7
eBook Packages: EngineeringReference Module Computer Science and Engineering