An enhanced Benders decomposition algorithm for two-stage stochastic LPs is presented and applied to a largescale dynamic generation and transmission expansion planning model for the European power system. The improved algorithm is a variation of the traditional multi-cut Benders decomposition algorithm where the scenario aggregation used for the optimality cuts is reduced at a given error threshold. Experimental results show that this technique improves convergence and reduces computation time. An analysis using the planning model to compute an optimal development of the European power sector under a global climate policy is also discussed.Index Terms-Benders decomposition, investments under uncertainty, large-scale power system planning
Ambitious emission reduction targets are challenging the status quo on designing effective strategies for electricity generation portfolios. In this chapter, we consider the role of low-carbon technologies and determine the cost-benefits of policy strategies to mitigate greenhouse gas emissions in the EU. In particular, we look into how long-term scenarios for transmission expansion and decarbonisation policies influence the evolution of the EU power system infrastructure. We use an EU electricity investment model to determine the optimal portfolio of electricity generation technologies and compute their respective costs and emissions achieved towards 2050. Based on the investment model's results (strategies and suggested portfolios), we investigate how these portfolios perform under divergent policy or geopolitical developments. For this purpose, we apply a robust optimisation tool based on the min-max and the min-max regret criteria, which selects ideal portfolios by stress testing a particular scenario or policy choice under uncertainty of input parameters. Results show that pursuing a strong transmission expansion strategy under the EU PRIMES reference case leads to the maximum regret, while relying on EU scenarios with strong prospects for decarbonisation, either with possibilities or with limitation on transmission expansion, leads to portfolios that exhibit the least variance. However, applying regret analysis on investment costs and total emissions indicates a limited transmission investment case as the more robust one, also noting that a high carbon price will accelerate the energy transition.
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