RESEARCH ARTICLE

Optimal portfolio design of energy storage devices with financial and physical right market

  • Puzhe LAN 1 ,
  • Dong HAN , 1 ,
  • Ruimin ZHANG 1 ,
  • Xiaoyuan XU 2 ,
  • Zheng YAN 2
Expand
  • 1. Department of Electrical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
  • 2. Department of Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China

Received date: 28 Jan 2021

Accepted date: 15 Jun 2021

Published date: 15 Feb 2022

Copyright

2021 Higher Education Press

Abstract

With the continuous development of the spot market, in the multi-stage power market environment with the day-ahead market and right market, the study associated with the portfolio of energy storage devices requires that attention should be paid to transmission congestion and power congestion. To maximize the profit of energy storage and avoid the imbalance of power supply and consumption and the risk of node price fluctuation caused by transmission congestion, this paper presents a portfolio strategy of energy storage devices with financial/physical contracts. First, the concepts of financial/physical transmission rights and financial/physical storage rights are proposed. Then, the portfolio models of financial contract and physical contract are established with the conditional value-at-risk to measure the risks. Finally, the portfolio models are verified through the test data of the Pennsylvania-New Jersey-Maryland (PJM) electric power spot market, and the comparison between the risk aversion of portfolios based on financial/physical contract with the portfolio of the market without rights. The simulation results show that the portfolio models proposed in this paper can effectively avoid the risk of market price fluctuations.

Cite this article

Puzhe LAN , Dong HAN , Ruimin ZHANG , Xiaoyuan XU , Zheng YAN . Optimal portfolio design of energy storage devices with financial and physical right market[J]. Frontiers in Energy, 2022 , 16(1) : 95 -104 . DOI: 10.1007/s11708-021-0788-2

1
Chinmoy L, Iniyan S, Goic R. Modeling wind power investments, policies and social benefits for deregulated electricity market—a review. Applied Energy, 2019, 242: 364–377

DOI

2
Ghorani R, Fotuhi-Firuzabad M, Moeini-Aghtaie M. Main challenges of implementing penalty mechanisms in transactive electricity markets. IEEE Transactions on Power Systems, 2019, 34(5): 3954–3956

DOI

3
Tudu B, Mandal K K, Chakraborty N. Optimal design and development of PV-wind-battery based nano-grid system: a field-on-laboratory demonstration. Frontiers in Energy, 2019, 13(2): 269–283

DOI

4
Gupta A R, Kumar A. Reactive power deployment and cost benefit analysis in DNO operated distribution electricity markets with D-STATCOM. Frontiers in Energy, 2019, 13(1): 86–98

DOI

5
Li P, Cai G, Zhang Y, . Multi-objective optimal allocation strategy for the energy internet in Huangpu District, Guangzhou, China. Frontiers in Energy, 2020, 14(2): 241–253

DOI

6
Vespermann N, Hamacher T, Kazempour J. Access economy for storage in energy communities. IEEE Transactions on Power Systems, 2021, 36(3): 2234–2250

DOI

7
Tenti P, Caldognetto T. A general approach to select location and ratings of energy storage systems in local area energy networks. IEEE Transactions on Industry Applications, 2019, 55(6): 6203–6210

DOI

8
Aguado J A, Quintana V H, Madrigal M, . Coordinated spot market for congestion management of inter-regional electricity markets. IEEE Transactions on Power Systems, 2004, 19(1): 180–187

DOI

9
Deng L, Li Z, Sun H, . Generalized locational marginal pricing in a heat-and-electricity-integrated market. IEEE Transactions on Smart Grid, 2019, 10(6): 6414–6425

DOI

10
Asrari A, Ansari M, Khazaei J, . A market framework for decentralized congestion management in smart distribution grids considering collaboration among electric vehicle aggregators. IEEE Transactions on Smart Grid, 2020, 11(2): 1147–1158

DOI

11
Huang S, Wu Q, Shahidehpour M, . Dynamic power tariff for congestion management in distribution networks. IEEE Transactions on Smart Grid, 2019, 10(2): 2148–2157

DOI

12
Han D, Zhang C, Ping J, . Smart contract architecture for decentralized energy trading and management based on blockchains. Energy, 2020, 199: 117417

DOI

13
Weibelzahl M. Nodal, zonal, or uniform electricity pricing: how to deal with network congestion. Frontiers in Energy, 2017, 11(2): 210–232

DOI

14
Mahesh A, Sandhu K S. A genetic algorithm based improved optimal sizing strategy for solar-wind-battery hybrid system using energy filter algorithm. Frontiers in Energy, 2020, 14(1): 139–151

DOI

15
Sharma R, Suhag S. Feedback linearization based control for weak grid connected PV system under normal and abnormal conditions. Frontiers in Energy, 2020, 14(2): 400–409

DOI

16
Hartwig K, Kockar I. Impact of strategic behavior and ownership of energy storage on provision of flexibility. IEEE Transactions on Sustainable Energy, 2016, 7(2): 744–754

DOI

17
Paterakis N G, de la Nieta A A S, Bakirtzis A G, . Effect of risk aversion on reserve procurement with flexible demand side resources from the ISO point of view. IEEE Transactions on Sustainable Energy, 2017, 8(3): 1040–1050

DOI

18
Saber H, Heidarabadi H, Moeini-Aghtaie M, . Expansion planning studies of independent-locally operated battery energy storage systems (BESSs): a CVaR-based study. IEEE Transactions on Sustainable Energy, 2020, 11(4): 2109–2118

DOI

19
Liu X, Yan Z, Wu J. Optimal coordinated operation of a multi-energy community considering interactions between energy storage and conversion devices. Applied Energy, 2019, 248: 256–273

DOI

20
Naderi M, Hashemi F, Bekker A, . Modeling right-skewed financial data streams: a likelihood inference based on the generalized Birnbaum-Saunders mixture model. Applied Mathematics and Computation, 2020, 376: 125109

DOI

21
Lo Prete C, Guo N, Shanbhag U V. Virtual bidding and financial transmission rights: an equilibrium model for cross-product manipulation in electricity markets. IEEE Transactions on Power Systems, 2019, 34(2): 953–967

DOI

22
Taylor J A. Financial storage rights. IEEE Transactions on Power Systems, 2015, 30(2): 997–1005

DOI

23
Gribik P R, Shirmohammadi D, Graves J S, . Transmission rights and transmission expansions. IEEE Transactions on Power Systems, 2005, 20(4): 1728–1737

DOI

24
Baldick R. Border flow rights and contracts for differences of differences: models for electric transmission property rights. IEEE Transactions on Power Systems, 2007, 22(4): 1495–1506

DOI

25
Thomas D, Kazempour J, Papakonstantinou A, . A local market mechanism for physical storage rights. IEEE Transactions on Power Systems, 2020, 35(4): 3087–3099

DOI

26
Budworth L, Prestwich A, Sykes-Muskett B, . A feasibility study to assess the individual and combined effects of financial incentives and monetary contingency contracts on physical activity. Psychology of Sport and Exercise, 2019, 44: 42–50

DOI

27
Leshno J D, Pradelski B S R. The importance of memory for price discovery in decentralized markets. Games and Economic Behavior, 2021, 125: 62–78

DOI

28
Madrigal M, Flores M. Integrated software platform to teach different electricity spot market architectures. IEEE Transactions on Power Systems, 2004, 19(1): 88–95

DOI

29
Gui Z, von Thadden E L, Zhao X. Incentive-compatibility, limited liability and costly liquidation in financial contracting. Games and Economic Behavior, 2019, 118: 412–433

DOI

30
Hogan W W. Contract networks for electric power transmission. Journal of Regulatory Economics, 1992, 4(3): 211–242

DOI

31
Muñoz-Álvarez D, Bitar E. Financial storage rights: definition and basic properties. In: 2014 North American Power Symposium (NAPS), Pullman, WA, USA, 2014: 1–6

32
Quintela F R, Redondo R C, Melchor N R, . A general approach to Kirchhoff’s laws. IEEE Transactions on Education, 2009, 52(2): 273–278

DOI

33
Sioshansi R. Using storage-capacity rights to overcome the cost-recovery hurdle for energy storage. IEEE Transactions on Power Systems, 2017, 32(3): 2028–2040

DOI

34
Cui S, Wang Y, Li C, . Prosumer community: a risk aversion energy sharing model. IEEE Transactions on Sustainable Energy, 2020, 11(2): 828–838

DOI

35
Palomba G, Riccetti L. Portfolio frontiers with restrictions to tracking error volatility and value at risk. Journal of Banking & Finance, 2012, 36(9): 2604–2615

DOI

36
Catalao J P S, Pousinho H M I, Mendes V M F. Optimal offering strategies for wind power producers considering uncertainty and risk. IEEE Systems Journal, 2012, 6(2): 270–277

DOI

Outlines

/