Power generation expansion planning approach considering carbon emission constraints

Decarbonization of the power sector in China is an essential aspect of the energy transition process to achieve carbon neutrality.The power sector accounts for approximately 40%of China’s total CO_(2) emissions.Accordingly,collaborative optimization in power generation expansion planning(GEP)simultaneously considering economic,environmental,and technological concerns as carbon emissions is necessary.This paper proposes a collaborative mixedinteger linear programming optimization approach for GEP.This minimizes the power system’s operating cost to resolve emission concerns considering energy development strategies,flexible generation,and resource limitations constraints.This research further analyzes the advantages and disadvantages of current GEP techniques.Results show that the main determinants of new investment decisions are carbon emissions,reserve margins,resource availability,fuel consumption,and fuel price.The proposed optimization method is simulated and validated based on China’s power system data.Finally,this study provides policy recommendations on the flexible management of traditional power sources,the market-oriented mechanism of new energy sources,and the integration of new technology to support the attainment of carbon-neutral targets in the current energy transition process.

Medium and long-term thermal coal contract embedded reparations from the perspective of an evolutionary game

Coal-fired electricity enterprises are caught in the dilemma of relative fixed prices and rising costs under the scenario of decarbonization.Meanwhile,soaring market-oriented coal pricing results in coal enterprises’increasing defaults on thermal coal medium-and long-term contracts(MLC).To investigate the implementation of MLC at the micro-level,this study formalized the contractual behaviors of coal and coal-fired electricity enterprises based on the asymmetric evolutionary game.We formalized the evolving behaviors of both parties using replicator dynamics equations and proved that there were two evolutionary stabilization strategies(ESSs):compliance and coal enterprises’unilateral default.A multi-agent-based simulation was applied to verify the evolving process of ESSs and determine the critical values of MLC design by sensitive analysis.From the simulation results,coal-fired electricity enterprises do not stop generation under the current carbon quota allocation mechanism,even if carbon emission trading increases electricity generation costs.Coal enterprises choose to“default”when the market price of coal is higher than the contracted price by 18%.However,if the original reparation is increased by 5%,the compliance rate of the coal enterprises improves.Dynamic reparations embedded in the MLC improved enforcement during the contracting period.Moreover,the proposed policy implications have practical significance for enhancing the coordinated operation of coal-electricity energy supply chains.