Coordinated scheduling of energy storage systems as a fast reserve provider

Abstract The need for the operational reserve is growing due to the increase of variability and intermittency in both generation and demand sides. Hence, energy storage systems (ESSs) are considered as an alternative source of the reserve, while conventional generators are not efficient based on economic and environmental perspectives. This paper studies an enhanced model for ESSs’ participation as a fast reserve provider. The day-ahead scheduling of ESSs within scenarios disturbs their stored energy in the sequence of hours. This issue can dramatically increase or decrease the stored energy of ESSs and threatens the safety of operational planning. The proposed model of this paper introduces coordination strategies for the deployment of fast reserves of ESSs. The stochastic model of this paper considers the fluctuations of wind speed and also the load forecasting errors as the source of uncertainties. A decomposition-based method is employed to reduce the complexity of the model dealing with a large number of variables. A modified version of the IEEE RTS-24 test system is used to evaluate different strategies for managing of ESSs' reservoir. The result shows that large deviations of the reservoir can make the operation of ESSs infeasible in uncoordinated strategies. Also, two proposed strategies for performance under normal and conservative criteria provide choices for system operators based on the desired level of security. Besides, the deployment of fast reserves of ESSs improves operation quality by the money-saving and increasing the quality of power delivery.

[1]  Vahid Vahidinasab,et al.  Two-stage hybrid stochastic/robust optimal coordination of distributed battery storage planning and flexible energy management in smart distribution network , 2019 .

[2]  Yinghua Han,et al.  Robust and opportunistic scheduling of district integrated natural gas and power system with high wind power penetration considering demand flexibility and compressed air energy storage , 2020 .

[3]  Markus Mueller,et al.  A Numerical and Graphical Review of Energy Storage Technologies , 2014 .

[4]  Robert J. Thomas,et al.  Secure Planning and Operations of Systems With Stochastic Sources, Energy Storage, and Active Demand , 2013, IEEE Transactions on Smart Grid.

[5]  S. Fathi,et al.  A bi-level model for strategic bidding of a price-maker retailer with flexible demands in day-ahead electricity market , 2020, International Journal of Electrical Power & Energy Systems.

[6]  Yaowang Li,et al.  Combined Heat and Power dispatch considering Advanced Adiabatic Compressed Air Energy Storage for wind power accommodation , 2019, Energy Conversion and Management.

[7]  Joao P. S. Catalao,et al.  Robust scheduling of variable wind generation by coordination of bulk energy storages and demand response , 2015 .

[8]  Vahid Vahidinasab,et al.  Multiobjective generation and transmission expansion planning of renewable dominated power systems using stochastic normalized normal constraint , 2020 .

[9]  Vahid Vahidinasab,et al.  Multiobjective ray optimization algorithm as a solution strategy for solving non-convex problems: A power generation scheduling case study , 2020 .

[10]  Jianhui Wang,et al.  Robust Energy and Reserve Scheduling Considering Bulk Energy Storage Units and Wind Uncertainty , 2018, IEEE Transactions on Power Systems.

[11]  Mousa Marzband,et al.  Stochastic network-constrained co-optimization of energy and reserve products in renewable energy integrated power and gas networks with energy storage system , 2019, Journal of Cleaner Production.

[12]  Vahid Vahidinasab,et al.  Robust optimization framework for dynamic distributed energy resources planning in distribution networks , 2019, International Journal of Electrical Power & Energy Systems.

[13]  Vahid Vahidinasab,et al.  Market bidding strategy of the microgrids considering demand response and energy storage potential flexibilities , 2019, IET Generation, Transmission & Distribution.

[14]  Wei Tian,et al.  Stochastic Scheduling of Battery-Based Energy Storage Transportation System With the Penetration of Wind Power , 2017, IEEE Transactions on Sustainable Energy.

[15]  Vahid Vahidinasab,et al.  Two alternative robust optimization models for flexible power management of electric vehicles in distribution networks , 2017 .

[16]  Quanyuan Jiang,et al.  Wavelet-Based Capacity Configuration and Coordinated Control of Hybrid Energy Storage System for Smoothing Out Wind Power Fluctuations , 2013, IEEE Transactions on Power Systems.

[17]  Igor Kuzle,et al.  Robust unit commitment with large-scale battery storage , 2017, 2017 IEEE Power & Energy Society General Meeting.

[18]  Emil M. Constantinescu,et al.  Flexible Operation of Batteries in Power System Scheduling With Renewable Energy , 2016, IEEE Transactions on Sustainable Energy.

[19]  Wei Wang,et al.  Cooperative Planning of Active Distribution System With Renewable Energy Sources and Energy Storage Systems , 2018, IEEE Access.

[20]  Ali Elkamel,et al.  Stochastic SCUC considering compressed air energy storage and wind power generation: A techno-economic approach with static voltage stability analysis , 2018 .

[21]  Zuyi Li,et al.  Comparison of Scenario-Based and Interval Optimization Approaches to Stochastic SCUC , 2012, IEEE Transactions on Power Systems.

[22]  Vahid Vahidinasab,et al.  Emergency Services of Energy Storage Systems for Wind Ramp Events , 2019, 2019 Smart Grid Conference (SGC).

[23]  Mohammad Shahidehpour,et al.  Battery-Based Energy Storage Transportation for Enhancing Power System Economics and Security , 2015, IEEE Transactions on Smart Grid.

[24]  Farhad Samadi Gazijahani,et al.  Chance-constrained CAES and DRP scheduling to maximize wind power harvesting in congested transmission systems considering operational flexibility , 2019, Sustainable Cities and Society.

[25]  Brayima Dakyo,et al.  Energy Management in the Decentralized Generation Systems Based on Renewable Energy—Ultracapacitors and Battery to Compensate the Wind/Load Power Fluctuations , 2015, IEEE Transactions on Industry Applications.

[26]  Mohammad Shahidehpour,et al.  Hourly Coordination of Electric Vehicle Operation and Volatile Wind Power Generation in SCUC , 2012, IEEE Transactions on Smart Grid.

[27]  Jihong Wang,et al.  A reserve capacity model of AA-CAES for power system optimal joint energy and reserve scheduling , 2019, International Journal of Electrical Power & Energy Systems.

[28]  Joao P. S. Catalao,et al.  Transmission switching, demand response and energy storage systems in an innovative integrated scheme for managing the uncertainty of wind power generation , 2018 .

[29]  Antonio J. Conejo,et al.  The role of energy storage in mitigating ramping inefficiencies caused by variable renewable generation , 2018 .

[30]  Xu Andy Sun,et al.  Multistage Robust Unit Commitment With Dynamic Uncertainty Sets and Energy Storage , 2016, IEEE Transactions on Power Systems.

[31]  Sumsun Naher,et al.  A review of mechanical energy storage systems combined with wind and solar applications , 2020 .

[32]  Vahid Vahidinasab,et al.  Coordinated Storage and Flexible Loads as a Network Service Provider: a Resilience-Oriented Paradigm , 2019, 2019 IEEE 28th International Symposium on Industrial Electronics (ISIE).