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Optimal bidding strategy of a gas-fired power plant in interdependent low-carbon electricity and natural gas markets

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  • Dimitriadis, Christos N.
  • Tsimopoulos, Evangelos G.
  • Georgiadis, Michael C.

Abstract

This work presents a bi-level optimization framework to determine the optimal bidding strategies for a strategic gas-fired power plant, exerting market power in interdependent pool-based electricity and natural gas markets, under a carbon emission trading scheme (CETS). The upper-level problem aims at maximizing the profits of the strategic player, while at the lower-level problem, the day-ahead electricity and natural gas markets are cleared sequentially, considering the provision of carbon emission allowances for conventional power producers and high penetration of wind power generation. The bi-level formulation is initially recast into a mathematical program with equilibrium constraints (MPEC), using the Karush-Kuhn-Tucker optimality conditions and duality theory, and is further reformulated into a mixed integer linear program. The proposed algorithm is applied to a Pennsylvania-New Jersey-Maryland (PJM) 5-bus power grid, incurred by transmission constraints and a single node natural gas network. Numerical simulations provide CETS-embedded electricity clearing prices and optimal bidding decisions for the strategic gas-fired power plant, under plausible power transmission congestions and natural gas prices increment scenarios.

Suggested Citation

  • Dimitriadis, Christos N. & Tsimopoulos, Evangelos G. & Georgiadis, Michael C., 2023. "Optimal bidding strategy of a gas-fired power plant in interdependent low-carbon electricity and natural gas markets," Energy, Elsevier, vol. 277(C).
    • Handle: RePEc:eee:energy:v:277:y:2023:i:c:s0360544223011040
    DOI: 10.1016/j.energy.2023.127710
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    References listed on IDEAS

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    1. Dimitriadis, Christos N. & Tsimopoulos, Evangelos G. & Georgiadis, Michael C., 2022. "Strategic bidding of an energy storage agent in a joint energy and reserve market under stochastic generation," Energy, Elsevier, vol. 242(C).
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