Distributionally Robust Distributed Generation Expansion Planning in a Market Environment
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Date
2019Type
- Conference Paper
Abstract
A generation expansion planning strategy to derive the optimal mix of distributed generations in a market environment is proposed. The considered system includes candidate decentralized storage units, variable generation units, dispatchable generation units and demand response. Distributionally robust optimization is applied to characterize the uncertainties in wind and PV generation forecasts by describing a family of possible uncertainty distributions with an ambiguity set. Finally, a multistage stochastic programming model is formulated to minimize the worst-case expectation of the sum of long-term investment costs and short-term operational costs. A case study based on Belgian electricity system data demonstrates the effectiveness of the proposed model and the importance of considering markets when optimizing the mix of distributed generation. The impacts of different products in reserve markets are analyzed and the outcomes from distributionally robust optimization, robust optimization and stochastic optimization are compared. Show more
Publication status
publishedExternal links
Book title
2019 16th International Conference on the European Energy Market (EEM)Pages / Article No.
Publisher
IEEEEvent
Subject
Decentralized energy resources; Distributionally robust optimization; Electricity markets; Generation expansion planning; Linear decision ruleOrganisational unit
09481 - Hug, Gabriela / Hug, Gabriela
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