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

Puzhe LAN , Dong HAN , Ruimin ZHANG , Xiaoyuan XU , Zheng YAN

Front. Energy ›› 2022, Vol. 16 ›› Issue (1) : 95 -104.

PDF (884KB)
Front. Energy ›› 2022, Vol. 16 ›› Issue (1) : 95 -104. DOI: 10.1007/s11708-021-0788-2
RESEARCH ARTICLE
RESEARCH ARTICLE

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

Author information +
History +
PDF (884KB)

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.

Graphical abstract

Keywords

portfolio / node price fluctuation / transmission right / energy storage right / risk aversion

Cite this article

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

登录浏览全文

4963

注册一个新账户 忘记密码

References

[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

[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

[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

[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

[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

[6]

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

[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

[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

[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

[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

[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

[12]

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

[13]

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

[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

[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

[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

[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

[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

[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

[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

[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

[22]

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

[23]

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

[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

[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

[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

[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

[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

[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

[30]

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

[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

[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

[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

[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

[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

RIGHTS & PERMISSIONS

Higher Education Press

AI Summary AI Mindmap
PDF (884KB)

3815

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/