Abstract
The ABT system holds power producers accountable for stabilizing the grid, preventing over-drawl and under-drawl of power. Before the introduction of ABT, frequent over-drawl and under-drawl beyond the limits caused grid disturbances. It results in fewer generators getting tripped due to the wide variation range in the grid frequency and leads to power shortages for large-scale consumers. CERC in India introduced DSM to penalize over-drawing and under-drawing in power buying/selling schedules. Staying within limits earns incentives tied to grid frequency also preventing producers from charging higher rates for exploiting the lower frequency range. This paper delves into the seamless integration of ABT with India’s regional and national grids. Furthermore, we meticulously scrutinize the power situation in India by examining the interconnection between MCP, DSM, and frequency. The DSM data were diligently collected from the Indian state of Madhya Pradesh for testing. The result shows that MCP linked with the DSM vector provides information on the deviation limit for DAM, power producers, and consumers. Linking of MCP with DSM and frequency makes power utilities more responsible and accountable for a power system.
Similar content being viewed by others
Availability of data and materials
Not applicable.
Abbreviations
- ABT:
-
Availability-based tariff
- CERC:
-
Central Electricity Regulatory Commission
- DSM:
-
Deviation settlement mechanism
- MP:
-
Madhya Pradesh
- MCP:
-
Market clearing price
- MO:
-
Market operators
- ACP:
-
Area clearing price
- UI:
-
Unscheduled interchange
- DAM:
-
Day-ahead market
- DALRS:
-
Distributed adjustable load resources and settlement
- RES:
-
Renewable energy source
- MCD:
-
Market clearing design
- DA:
-
Day-ahead
- MCV:
-
Market clearing volume
- DLMP:
-
Distribution locational marginal price
- DR:
-
Demand response
- RTM:
-
Real-time market
- NN:
-
Neural network
- DSC:
-
Deviation settlement charge
- AT:
-
Availability tariff
- ACEC:
-
Area control error code
- IEX:
-
Indian Energy Exchange
- WRPC:
-
Western Regional Power Committee
- X:
-
Capacity charges/fixed charges
- Y:
-
Energy charges/variable charges
- Z:
-
Unscheduled interchange energy charges
- P:
-
Daily average area clearing price (Paise/KWH)
References
Koul B, Singh K, Brar YS (2022) Deviation settlement mechanism and its implementation in Indian electricity grid. Lect Notes Electr Eng 768:237–246. https://doi.org/10.1007/978-981-16-2354-7_22
Ahmad F, Alam MS (2019) Assessment of power exchange based electricity market in India. Energy Strateg Rev 23:163–177. https://doi.org/10.1016/j.esr.2018.12.012
Gupta AK, Kiran D, Abhyankar AR (2020) Towards efficient real-time deviation settlement mechanism for the Indian grid. IET Gener Transm Distrib 14(2):308–315. https://doi.org/10.1049/iet-gtd.2018.6789
Cai T, Dong M, Chen K, Gong T (2022) Methods of participating power spot market bidding and settlement for renewable energy systems. Energy Rep 8:7764–7772. https://doi.org/10.1016/j.egyr.2022.05.291
Mishra P, Ghose T (2016) A direct method for assessment of overall voltage condition of power system. Int J Electr Power Energy Syst 81:232–238. https://doi.org/10.1016/j.ijepes.2016.02.031
Mishra P, Ghose T (2014) Impact of frequency-based tariff in power market. Int J Power Energy Convers 5(4):402–416. https://doi.org/10.1504/IJPEC.2014.065495
Savelli I, Cornélusse B, Giannitrapani A, Paoletti S, Vicino A (2018) A new approach to electricity market clearing with uniform purchase price and curtailable block orders. Appl Energy 226(March):618–630. https://doi.org/10.1016/j.apenergy.2018.06.003
Wang B, Guo Q, Yang T, Xu L, Sun H (2021) Data valuation for decision-making with uncertainty in energy transactions: a case of the two-settlement market system. Appl Energy 2881:116643. https://doi.org/10.1016/j.apenergy.2021.116643
Daraeepour A, Patino-Echeverri D, Conejo AJ (2019) Economic and environmental implications of different approaches to hedge against wind production uncertainty in two-settlement electricity markets: a PJM case study. Energy Econ 80:336–354. https://doi.org/10.1016/j.eneco.2019.01.015
Kaneko N, Fujimoto Y, Hayashi Y (2022) Sensitivity analysis of factors relevant to extreme imbalance between procurement plans and actual demand: case study of the Japanese electricity market. Appl Energy 313(1):118616. https://doi.org/10.1016/j.apenergy.2022.118616
Goudarzi H, Rayati M, Sheikhi A, Ranjbar AM (2021) A clearing mechanism for joint energy and ancillary services in non-convex markets considering high penetration of renewable energy sources. Int J Electr Power Energy Syst 129:106817. https://doi.org/10.1016/j.ijepes.2021.106817
Silva-Rodriguez L, Sanjab A, Fumagalli E, Virag A, Gibescu M (2022) A light robust optimization approach for uncertainty-based day-ahead electricity markets. Electr Power Syst Res 212(October):108281. https://doi.org/10.1016/j.epsr.2022.108281
Yan X, Chowdhury NA (2013) Mid-term electricity market clearing price forecasting: A hybrid LSSVM and ARMAX approach. Int J Electr Power Energy Syst 53(1):20–26. https://doi.org/10.1016/j.ijepes.2013.04.006
Osińska M, Kyzym M, Khaustova V, Ilyash O, Salashenko T (2022) Does the Ukrainian electricity market correspond to the european model? Util Policy. https://doi.org/10.1016/j.jup.2022.101436
Yan X, Chowdhury NA (2014) Mid-term electricity market clearing price forecasting: a multiple SVM approach. Int J Electr Power Energy Syst 58:206–214. https://doi.org/10.1016/j.ijepes.2014.01.023
Kim MK, Hur D (2013) An optimal pricing scheme in electricity markets by parallelizing security constrained optimal power flow based market-clearing model. Int J Electr Power Energy Syst 48:161–171. https://doi.org/10.1016/j.ijepes.2012.05.047
He Y, Chen Q, Yang J, Cai Y, Wang X (2021) A multi-block ADMM based approach for distribution market clearing with distribution locational marginal price. Int J Electr Power Energy Syst 128:106635. https://doi.org/10.1016/j.ijepes.2020.106635
Kim MK, Park JK, Nam YW (2011) Market-clearing for pricing system security based on voltage stability criteria. Energy 36(2):1255–1264. https://doi.org/10.1016/j.energy.2010.11.019
Munhoz FC (2021) Two-settlement system for the Brazilian electricity market. Energy Policy 152(March):112234. https://doi.org/10.1016/j.enpol.2021.112234
Wu Z, Zhou M, Zhang T, Li G, Zhang Y, Liu X (2020) Imbalance settlement evaluation for China’s balancing market design via an agent-based model with a multiple criteria decision analysis method. Energy Policy 139(February):111297. https://doi.org/10.1016/j.enpol.2020.111297
Karsaz A, Mashhadi HR, Mirsalehi MM (2010) Market clearing price and load forecasting using cooperative co-evolutionary approach. Int J Electr Power Energy Syst 32(5):408–415. https://doi.org/10.1016/j.ijepes.2009.11.001
Vlachos AG, Biskas PN (2014) Embedding renewable energy pricing policies in day-ahead electricity market clearing. Electr Power Syst Res 116:311–321. https://doi.org/10.1016/j.epsr.2014.06.022
Herrero I, Rodilla P, Batlle C (2015) Electricity market-clearing prices and investment incentives: the role of pricing rules. Energy Econ 47:42–51. https://doi.org/10.1016/j.eneco.2014.10.024
Lu X, Yang Y, Wang P, Fan Y, Yu F, Zafetti N (2021) A new converged Emperor Penguin Optimizer for biding strategy in a day-ahead deregulated market clearing price: a case study in China. Energy 227:120386. https://doi.org/10.1016/j.energy.2021.120386
Georgilakis PS (2006) Market clearing price forecasting in deregulated electricity markets using adaptively trained neural networks. In: Lect. Notes Comput. Sci. (including Subser. Lect. Notes Artif. Intell. Lect. Notes Bioinformatics). 3955 LNAI:56–66. https://doi.org/10.1007/11752912_8
Gupta M, Gupta S, Thakur T (2019) Implementation of new electricity regulatory norms for deviation settlement mechanism: a case study of India. Cogent Eng 6(1):1–24. https://doi.org/10.1080/23311916.2019.1623152
Kalyanasundaram V, Vijayakumar K, Vishnuram P, Kanakaraj P (2016) Market clearing price calculation for a deregulated power market. Indian J Sci Technol 9:42. https://doi.org/10.17485/ijst/2016/v9i42/101850
Shariat Torbaghan S et al (2021) Designing day-ahead multi-carrier markets for flexibility: models and clearing algorithms. Appl Energy 285(January):116390. https://doi.org/10.1016/j.apenergy.2020.116390
Gupta P, Verma YP (2019) Optimisation of deviation settlement charges using residential demand response under frequency-linked pricing environment. IET Gener Transm Distrib 13(12):2362–2371. https://doi.org/10.1049/iet-gtd.2018.7116
On AP, Tariff A (2005) ABC of ABT A PRIMER ON
I. Central Electricity Regulatory Commission (CERC) (2017) Review of the principles of deviation settlement mechanism (DSM), including linkage with frequency, in light of emerging markets. p. 175. http://www.cercind.gov.in/2018/Reports/ASB.pdf
Central Electricity Regulatory Commission (2018) Deviation settlement mechanism and related matters (fourth amendment) regulations. In: Cent. Electr. Regul. Comm., no. L, pp. 1–12. http://www.cercind.gov.in/2018/regulation/dsm_fourth_amendment11-22-2018.pdf
Deshmukh SR, Doke DJ, Nerkar YP (2008) Optimal generation scheduling under ABT using forecasted load and frequency. In: 2008 Jt. Int. Conf. Power Syst. Technol. POWERCON IEEE Power India Conf. POWERCON 2008. https://doi.org/10.1109/ICPST.2008.4745200
IEX. Power markets and exchange operations
Soonee S, Narasimhan S, Pandey V (2006) Significance of unscheduled interchange mechanism in the Indian electricity supply industry. In: Proc. 12th …, no. January, 2006, [Online]. Available: http://www.srldc.in/Downloads/Significance_of_UI.pdf
Mishra P, Ghose T (2012) Exploring profit earning strategies used by DISCOMs under frequency linked tariff followed in India. In: 2012 IEEE 5th Power India Conf. PICONF 2012. https://doi.org/10.1109/PowerI.2012.6479490
Gupta AK, Balasubramanian R, Vaitheeswaran N (2008) ANN-based block frequency prediction in ABT regime and optimal availability declaration. In: IEEE Power Energy Soc. 2008 Gen. Meet. Convers. Deliv. Electr. Energy 21st Century, PES, pp. 1–8. https://doi.org/10.1109/PES.2008.4596778.
Acknowledgements
The authors thank the Madhya Pradesh Power Management Company Limited, Jabalpur, for providing us the data for study purposes.
Funding
Not applicable.
Author information
Authors and Affiliations
Contributions
RKC proposed the research topic, designed the proposed system, performed the simulations, computed and analyzed the results, and prepared the paper. SKM, NK, and DSC identified the issues related to the problem statement, discussed, analyzed, and verified the results obtained, and revised the manuscript. All the authors contributed to the writing of the manuscript and have read and approved the final manuscript.
Corresponding author
Ethics declarations
Ethics approval and consent to participate
Not applicable.
Competing interests
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Chauhan, R.K., Maurya, S.K., Kumar, N. et al. Effect of linking of deviation settlement mechanism for over-drawl and under-drawl of power with market clearing price. Electr Eng 106, 1907–1923 (2024). https://doi.org/10.1007/s00202-023-02031-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00202-023-02031-x