Highly resolved optimal renewable allocation planning in power systems under consideration of dynamic grid topology

• Published in: Computers & operations research Vol. 96; pp. 281 - 293
• Main Authors: Slednev, Viktor, Bertsch, Valentin, Ruppert, Manuel, Fichtner, Wolf
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.08.2018; Pergamon Press Inc
• Subjects: Allocations; Alternative energy; Alternative energy sources; Dynamic grid topology; Electric power systems; Electricity distribution; Large-scale optimisation; Operations research; Optimal renewable allocation planning; Optimization; Photovoltaic cells; Renewable energy sources; Solar cells; Studies; Topology; Ireland; Large-scale optimisation; Optimal renewable allocation planning; Dynamic grid topology
• ISSN: 0305-0548; 1873-765X; 0305-0548
• DOI: 10.1016/j.cor.2017.12.008

•Model developed for renewable allocation planning under changing grid topology.•Consideration of assignment of renewable potentials to grid nodes as variable.•The large-scale optimisation model is generic and includes data for all of Europe.•Demonstration of model for renewable expansion and allocation case study in Ireland.•Wind onshore is dominating technology, diversification leads to cost increase. The system integration of an increasing amount of electricity generation from decentralised renewable energy sources (RES-E) is a major challenge for the transition of the European power system. The feed-in profiles and the potential of RES-E vary along the geographical and temporal dimension and are also subject to technological choices and changes. To support power system planning in the context of RES-E expansion and allocation planning required for meeting RES-E targets, analyses are needed assessing where and which RES-E capacities are likely to be expanded. This requires models that are able to consider the power grid capacity and topology including their changes over time. We therefore developed a model that meets these requirements and considers the assignment of RES-E potentials to grid nodes as variable. This is a major advancement in comparison to existing approaches based on a fixed and pre-defined assignment of RES-E potentials to a node. While our model is generic and includes data for all of Europe, we demonstrate the model in the context of a case study in the Republic of Ireland. We find wind onshore to be the dominating RES-E technology from a cost-efficient perspective. Since spatial wind onshore potentials are highest in the West and North of the country, this leads to a high capacity concentration in these areas. Should policy makers wish to diversify the RES-E portfolio, we find that a diversification mainly based on bioenergy and wind offshore is achievable at a moderate cost increase. Including solar photovoltaics into the portfolio, particularly rooftop installations, however, leads to a significant cost increase but also to a more scattered capacity installation over the country.