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An economic risk based optimal bidding strategy for various market players considering optimal wind placements in day-ahead and real-time competitive power market

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  • Rajesh Panda

    (Presidency University)

  • Prashant Kumar Tiwari

    (MNNIT Allahabad)

Abstract

This paper proposes a novel optimal bidding strategy of various market players for day-ahead and real-time competitive power markets considering optimal wind placements. The proposed problem formulation consists of three-stage stochastic mixed integer linear problem in which the expected profit of market participants such as Generation Companies (GenCos) and Distribution Companies (DisCos) are determined and compared with and without presence of wind generators (WG). In the first stage, the market clearing mechanism is established in which the GenCos and DisCos bid according to the mean–variance approach, and profit of market participants is determined considering the regulation market and imbalance cost (IC) without WG. WG are located optimally in the system by accessing Conditional Value-at-Risk (CVaR) as risk assessment tool. In the second stage, risk cost is minimized considering the profit distribution as per the probability distribution curve. A trade-off is made between expected profit and risk cost by variation in the weight parameter. In the third stage, the expected system profit is determined considering the regulating price and IC for all scenarios with the presence of WG. The proposed approach is applied to a modified IEEE 30 bus system to show the effectiveness of the proposed model.

Suggested Citation

  • Rajesh Panda & Prashant Kumar Tiwari, 2022. "An economic risk based optimal bidding strategy for various market players considering optimal wind placements in day-ahead and real-time competitive power market," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(1), pages 347-362, February.
    • Handle: RePEc:spr:ijsaem:v:13:y:2022:i:1:d:10.1007_s13198-021-01251-3
    DOI: 10.1007/s13198-021-01251-3
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    References listed on IDEAS

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    1. Sánchez de la Nieta, Agustín A. & Paterakis, Nikolaos G. & Gibescu, Madeleine, 2020. "Participation of photovoltaic power producers in short-term electricity markets based on rescheduling and risk-hedging mapping," Applied Energy, Elsevier, vol. 266(C).
    2. Esmaeili Aliabadi, Danial & Kaya, Murat & Sahin, Guvenc, 2017. "Competition, risk and learning in electricity markets: An agent-based simulation study," Applied Energy, Elsevier, vol. 195(C), pages 1000-1011.
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    Cited by:

    1. Germán Herrera Vidal & Camilo Molina Guerrero, 2024. "Deterministic ınventory models with non-perishable product: a comparative study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2500-2517, June.

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