Comprehensive Framework for Distribution Network Multi-Investment Expansion Planning: Emissions, Uncertainty, and Resource Remuneration Integration

Abstract

Changes are currently unfolding within electric distribution networks as renewable energy integration grows. This paper introduces a novel stochastic approach for expansion planning in distribution networks with high renewable energy penetration. The model addresses uncertainties, daily and seasonal impacts, distributed generation remuneration, carbon emissions, and optimal energy storage deployment. Risk aversion techniques such as value-at-risk and conditional value-at-risk are employed to prepare networks for impactful events. Emphasizing multi-period investment over single-period, the analysis considers confidence levels and risk aversion’s effects on reliability indexes, energy storage placement, generation patterns, network topology, and costs. Using a realistic 180-bus distribution network in Portugal spanning 30 years, the method’s applicability and robustness are demonstrated. Results illustrate the benefits of multi-period investment, with cost increases of 6.09 % and 2.97 % for single- and multi-period investments at a 90 % confidence level, respectively, when both are compared to a situation with no risk aversion. Higher confidence levels amplify the trade-off between extreme scenario cost reduction and total cost increase, with a 99 % confidence level reducing scenario costs by 19.01 % while increasing total costs by 5.64 %.