Abstract
In today's grid power system, the emergence of flexibility devices such as energy storage systems (ESS), static synchronous compensators (STATCOM), and demand response programs (DRP) can help power system operators make more effective and cost-effective power system scheduling decisions. This paper proposes security-constrained unit commitment (SCUC) for stochastic scheduling of power systems based on the grid and the coordinated strategy of ESS, STATCOM, and DRP units in the presence of high solar PV power penetration. By addressing the problem constraints, the goal is to reduce operational, ESS cost, load shedding, solar power curtailment, and DRP costs. The AC power flow equations and all the model relations have been given convexities to produce a mixed-integer quadratically constrained programming (MIQCP) model, the solution to which would produce global optimum results. The developed model is used for solving the general algebraic modeling system (GAMS), realistic to the IEEE 24-bus system in several case studies, and the outcomes are carefully examined. The economic benefits shared by ESS and DRP with STATCOM devices were reduced by about 5.6% in scheduling costs as compared to solar PV farms.
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Tarashandeh N, Karimi A (2021) Utilization of energy storage systems in congestion management of transmission networks with incentive-based approach for investors. J Energy Storage 33:102034
Artis R, Shivaie M, Weinsier PD (2023) A flexibility-based multi-objective model for contingency-constrained transmission expansion planning incorporating large-scale hydrogen/compressed-air energy storage systems and wind/solar farms. J Energy Storage 70:108086
Soroudi A (2021) Controllable transmission networks under demand uncertainty with modular FACTS. Int J Electr Power Energy Syst 130:106978
Moradi-Sepahvand M, Amraee T, Aminifar F, Akbari A (2023) Coordinated expansion planning of transmission and distribution systems integrated with smart grid technologies. Int J Electr Power Energy Syst 147:108859
Namilakonda S, Guduri Y (2021) Chaotic Darwinian particle swarm optimization for real-time hierarchical congestion management of power system integrated with renewable energy sources. Int J Electr Power Energy Syst 128:106632
Saboori H, Jadid S (2022) Capturing curtailed renewable energy in electric power distribution networks via mobile battery storage fleet. J Energy Storage 46:103883
Prajapati VK, Mahajan V, Padhy NP (2021) Congestion management of integrated transmission and distribution network with RES and ESS under stressed condition. Int Trans Electr Energy Syst 31(2):e12757
Korab R, Połomski M, Owczarek R (2021) Application of particle swarm optimization for optimal setting of phase shifting transformers to minimize unscheduled active power flows. Appl Soft Comput 105:107243
Ahmad AA, Sirjani R, Daneshvar S (2020) New hybrid probabilistic optimisation algorithm for optimal allocation of energy storage systems considering correlated wind farms. J E Storage 29:101335
Punda L, Capuder T, Pandžić H, Delimar M (2017) Integration of renewable energy sources in southeast Europe: a review of incentive mechanisms and feasibility of investments. Renew Sustain Energy Rev 71:77–88
Zhang X, Shi Di, Wang Z, Zeng Bo, Wang X, Tomsovic K, Jin Y (2018) Optimal allocation of series FACTS devices under high penetration of wind power within a market environment. IEEE Trans Power Syst 33(6):6206–6217
Sang Y, Sahraei-Ardakani M (2017) The interdependence between transmission switching and variable-impedance series FACTS devices. IEEE Trans Power Syst 33(3):2792–2803
Kwon K-B, Kim D (2021) Enhanced method for considering energy storage systems as ancillary service resources in stochastic unit commitment. Energy 213:118675
Gupta P et al (2022) Battery energy storage train routing and security-constrained unit commitment under solar uncertainty. J Energy Storage 55:105811
Attarha A, Amjady N, Dehghan S et al (2018) Adaptive robust self-scheduling for a wind producer with compressed air energy storage. IEEE Trans Sustain Energy 9(4):1659–1671
Jadid Bonab M, Dolatabadi A, Mohammadi Ivatloo B et al (2019) Risk constrained energy management of PV integrated smart energy hub in the presence of demand response program and compressed air energy storage. IET Renew Power Gener 13:998–1008
Ghaljehei M, Ahmadian A, Golkar MA et al (2018) Stochastic SCUC considering compressed air energy storage and wind power generation: a techno-economic approach with static voltage stability analysis. Int J Electr Power Energy Syst 100:489–507
Gupta PP, Jain P, Kalkhambkar V, Sharma KC, Bhakar R (2020) Stochastic security-constrained unit commitment with battery energy storage and wind power integration. Int Trans Electr Energy Syst 30(10):e12556
Kalantari N, Abdolahi A, Mousavi SH et al (2023) Strategic decision making of energy storage owned virtual power plant in day-ahead and intra-day markets. J Energy Storage 73:108839
Gupta PP, Jain P, Sharma K, Bhakar R (2019) Stochastic scheduling of compressed air energy storage in DC SCUC framework for high wind penetration. IET Gener Transm Distrib 13(13):2747–2760
Luburić Z, Pandžić H (2019) FACTS devices and energy storage in unit commitment. Int J Electr Power Energy Syst 104:311–325
Yang Z, Shen C, Zhang L, Crow ML, Atcitty S (2001) Integration of a STATCOM and battery energy storage. IEEE Trans Power Syst 16(2):254–260
Sreejith S, Simon SP, Selvan MP (2015) Analysis of FACTS devices on security constrained unit commitment problem. Int J Electr Power Energy Syst 66:280–293
Dawn S, Tiwari PK (2016) Improvement of economic profit by optimal allocation of TSCS & UPFC with wind power generators in double auction competitive power market. Int J Electr Power Energy Syst 80:190–201
Sahraei-Ardakani M, Hedman KW (2016) Day-ahead corrective adjustment of FACTS reactance: a linear programming approach. IEEE Trans Power Syst 31(4):2867–2875
Zarate-Minano R, Conejo A, Milano F (2008) OPF-based security redispatching including FACTS devices. IET Gener Transm Distrib 2(6):821–833
Norouzi MR, Ahmadi A, Nezhad AE, Ghaedi A (2014) Mixed integer programming of multi-objective security constrained hydro/thermal unit commitment. Renew Sustain Energy Rev 29:911–923
Lorca A, Sun XA (2017) Multi-stage robust unit commitment with dynamic uncertainty sets and energy storage. IEEE Trans Power Syst 32(3):1678–1688
Nikoobakht A, Mardaneh M, Aghaei J et al (2017) Flexible power system operation accommodating uncertain wind power generation using transmission topology control: an improved linearised AC SCUC model. IET Gener Transm Distrib 11(1):142–153
Park H, Jin YG, Park JK (2018) Stochastic security-constrained unit commitment with wind power generation based on dynamic line rating. Int J Electr Power Energy Syst 102:211–222
Henrion R, Romisch W (2022) Problem-based optimal scenario generation and reduction in stochastic programming. Math Program 191(1):183–205
Ahmad AA, Sirjani R, Daneshvar S (2020) New hybrid probabilistic optimization algorithm for optimal allocation of energy storage systems considering correlated wind farms. J Energy Storage 29:101335
Numan M, Feng D, Abbas F, Habib S, Hao Su (2021) Coordinated operation of reconfigurable networks with dynamic line rating for optimal utilization of renewable generation. Int J Electr Power Energy Syst 125:106473
Lai CM, Jiashen T (2022) Network topology optimisation based on dynamic thermal rating and battery storage systems for improved wind penetration and reliability. Appl Energy 305:117837
Jadidbonab M et al (2019) Risk-constrained energy management of PV integrated smart energy hub in the presence of demand response program and compressed air energy storage. IET Renew Power Gener 13(6):998–1008
Pathiravasam C, Venayagamoorthy GK (2022) Distributed demand response management for a virtually connected community with solar power. IEEE Access 10:8350–8362
Rehman AU et al (2021) An efficient energy management in smart grid considering demand response program and renewable energy sources. IEEE Access 9:148821–148844
Mohseni S, Brent AC, Kelly S, Browne WN (2022) Demand response-integrated investment and operational planning of renewable, and sustainable energy systems considering forecast uncertainties: a systematic review. Renew Sustain Energy Rev 158:112095
Yang J, Wiedmann T, Luo F, Yan G, Wen F, Broadbent GH (2022) A fully decentralized hierarchical transactive energy framework for charging EVs with local DERs in power distribution systems. IEEE Trans Transport Electrif 8:1–1
AL Ahmad A, Sirjani R (2021) Optimal planning and operational strategy of energy storage systems in power transmission networks: an analysis of wind farms. Int J Energy Res 45(7):11258–11283
Soroudi A (2017) Power system optimization modeling in GAMS, vol 78. Springer, Switzerland
Rosenthal A, Richard E (2004) GAMS—a user's guide
Gupta PP, Jain P, Sharma CK, Bhakar R (2019) Optimal scheduling of electric vehicles in stochastic AC SCUC problem for large-scale wind power penetration. Intern Trans Electr Energy Syst 30:e2596
Acknowledgements
The authors would like to express their sincere gratitude to the Department of Technology, Shivaji University, Kolhapur, for their support and resources throughout this research endeavor. Special thanks are extended to Prof. H. T. Jadhav for his invaluable guidance and mentorship. Nileshkumar, working as a PhD research scholar, acknowledges the support and encouragement received from all those involved in this study. Their contributions have been instrumental in the successful completion of this research.
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Nileshkumar J. Kumbhar contributed to conceptualization, writing—original draft, visualization, methodology, software, investigation, formal analysis, and writing—review and editing. H.T. Jadhav contributed to investigation, methodology, visualization, writing—review and editing, and supervision.
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Kumbhar, N.J., Jadhav, H.T. Techno-economic analysis of energy storage integration combined with SCUC and STATCOM to improve power system stability. Electr Eng (2024). https://doi.org/10.1007/s00202-024-02410-y
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DOI: https://doi.org/10.1007/s00202-024-02410-y