This paper proposes an enhanced optimization formulation to help determine the type of power generation mix that can meet a given carbon emission target at the minimum cost. Compared to the previous studies, the model proposed in this paper takes account of the emission cost at operational level and explores its impacts on the long-term emission target oriented generation planning innovatively. Meanwhile, the model is able to take account of the integer variables and nonlinearity of the operational cost together with network constraints and renewable generation expansion in one long-term generation planning model. The problem is solved by an innovative discrete gradient search method, and a new concept, Emission Reduction Cost (ERC) is developed, which helps determine which generation technology is the most cost efficient in emission reduction during different stages of generation expansion. A case study on a modified IEEE 30 bus system is presented to demonstrate the application of this model and the value of considering short-term emission costs and the network constraints on the long-term generation expansion. The results and sensitivity analysis are provided to show that a higher short-term financial pressure can help realize the emission target at a lower total cost (investment and operational costs). Optimization without considering it may overestimate the total cost required for the generation mix restructuring. Additionally, a comparative study shows that optimization without considering network constraints may underestimate the total cost required for realizing the specified emission reduction target.

This paper presents a new emission constrained power generation expansion model to investigate what kind of generation mix is necessary and economical in order to meet a specific emission target. The proposed model can help governments make decisions for generation expansion to meet their emission reduction targets by employing a cost efficient planning methodology. Renewable source generation is considered in this research. The year-round generation and emission cost is evaluated by a dynamic programming based unit commitment. A case study on an IEEE 30 bus system is provided to verify the effectiveness of this model, showing how the new scheme can help the generation system move towards a low carbon electricity supply future. Optimized generation mix results are provided to investigate the generation cost (including investment) varies with different emission prices.

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