Representing cross-border trade of electricity in long-term energy-system optimization models with a limited geographical scope. (1st March 2020)

• Record Type: Journal Article
• Authors: Mertens, Tim; Poncelet, Kris; Duerinck, Jan; Delarue, Erik
• Is Part Of: Applied energy. Volume 261(2020)
• Publication Date: 2020-03-01
• Subjects: Long-term power system planning -- Energy-system optimization models -- Cross-border trade -- Transmission networks -- Geographical scope; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2019.114376
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: Ignoring trade potentials affect technology choices and domestic welfare. Congestion rents constitute an important welfare component in planning exercises. Including foreign dispatch decisions is the recommended modeling approach. Approaches based on annual average trade potentials are not recommended. Abstract: Long-term energy system optimization models can be designed to model systems with a broad geographical scope that comprises multiple countries. However, due to computational limitations, often the geographical scope is restricted to a single country. This raises the problem of correctly accounting for cross-border trade of electricity in models with a limited geographical scope. Therefore, this paper assesses the impact of not correctly representing cross-border trade flows in geographically restricted long-term planning models. To this end, we use a planning model for the interconnected Central-Western European power system to compare technology choices and welfare estimates for Belgium when (i) cross-border trade of electricity is ignored and (ii) cross-border trade flows are an endogenous part of the planning model. Furthermore, this paper presents two sets of methodologies to account for transmission flows in planning models. A first methodology is to extend the model's geographical scope and fix the capacity variables in the neighboring countries in line with pre-designed scenarios for those countries. A second methodology further reduces the computational cost by using specially tailored import and export curves to represent each country's trade opportunities. The results indicate that for highly interconnected systems, neglecting cross-border trade or having a highly stylized representation of cross-border flows can lead to inaccurate welfare estimates and technology biases. In addition, a key insight presented in this paper is that congestion rents can constitute a major share of the welfare gains attained by trading electricity. Finally, endogenizing the dispatch decisions in neighboring countries is the most accurate method to deal with cross-border trade, while by correctly designing cross-border trade curves computational time can be reduced, but planning model outcomes become less accurate.