Fuzzy optimisation model of an incremental capacity auction formulation with greenhouse gas consideration

Abstract

An incremental capacity auction (ICA) is a mechanism to procure future generation capacity in a power system. Greenhouse gas (GHG) emissions from generators negatively affect our climate and there is a real need to reduce them. Thus, it is critically important for ICA models to procure future generation capacity that reduces GHG emissions. In this paper, we propose two ICA models incorporating energy‐limited generation (renewables and storage) and a GHG emission constraint. All offers are converted into unforced capacity, negating any effect of energy limitations of generation offers. The first ICA model uses classical optimisation and considers GHG emission limits and maximises social welfare (SW). The second ICA model uses a fuzzy optimisation technique to simultaneously optimise the objectives of SW maximisation and GHG emission minimisation. Both ICA models are tested on two datasets with 10 and 338 capacity supply offers constructed using Ontario data. While both models control GHG emissions as desired, the ICA model with fuzzy optimisation is shown to find a better balance between maximising net SW and minimising GHG emissions, with superior reductions in GHG for minor decreases in SW. Results demonstrate how GHG emission reduction results in increased selection of low carbon generation.

Fuzzy logic in the decision-making tasks of connecting renewable energy sources into the electricity supply system

“…In turn, Baqui [12] formulated an automated decision-making model for the allocation of power grid resources using fuzzy logic algorithms. The rule base was created on the knowledge of the subject area and analysis of the operator's decision-making activities.…”

Bayesian-Nash equilibria for fuzzy value auctions

“…(1) Plum (1992) proved for 2 N  that a similar theorem is valid for the auctions where a winner has to pay a combination of the two highest bids. Some works have dealt with the application of the fuzzy theory to auctions (see, e.g., Fang et al (2004), Ignatius et al (2010), Kaur et al (2017), Zhou et al (2021), Bhachu et al (2023)); these works do not study Bayesian-Nash equilibria. However, Bayesian-Nash equilibria for fuzzy value auctions are of considerable interest.…”