Strategic models for producers and consumers in electricity markets

• Ano de defesa: 2025
• Autor(a) principal: Lêdo, João Augusto Silva [UNESP]
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Problemas matemáticos com restrições de equilíbrio– MPEC; Problemas de complementaridade; Ofertas estratégicas e lances estratégicos; Mercados de eletricidade do dia seguinte; Sistemas hidrotérmicos; Bilevel optimization; Mathematical problem with equilibrium constraints > MPEC; Equilibrium problem with equilibrium constraints > EPEC; Complementary problems; Strategic offering and strategic bidding; Day-ahead electricity markets; Hydrothermal systems
• Link de acesso: https://hdl.handle.net/11449/310827

This work presents a comprehensive approach to modeling and solving strategic behavior in hydro-dominated day-ahead electricity markets. First, a bilevel strategic offering (SO) model is proposed for a strategic company (SC) that operates in such a market. The upper-level model maximizes the SC's profits, while the lower-level model represents a hydrothermal market clearing (MC) that accounts for detailed hydro, thermal, and network constraints for both the SC and non-strategic companies (NSCs). To solve this problem, the lower-level model is replaced by its primal and dual constraints along with a strong duality equality, resulting in a non-convex mathematical programming with equilibrium constraints (MPEC) formulation. This MPEC is then reformulated to include only a single bilinear term, which is iteratively convexified and solved until convergence is achieved. Extending this research, the work also addresses the challenge of finding Nash equilibria in a wholesale electricity market with strategic producers and strategic consumers. This problem is formulated as an Equilibrium Problem with Equilibrium Constraints (EPEC), where each participant's decision-making is modeled as an MPEC. Unlike previous approaches, which rely on Karush-Kuhn-Tucker (KKT) conditions and face numerical instability due to complementarity constraints, this work employs Primal-Dual Optimality Conditions (PDOCs) to reformulate MPECs in a convex manner. The proposed method transforms MPECs into convex rotated quadratic conic problems, enabling the derivation of their exact dual counterparts and ensuring a stable solution process. The methodology is validated using a realistic case study, comparing scenarios where producers and consumers exert market power against those where perfect competition is assumed. The results demonstrate the effectiveness of the proposed approach in capturing strategic interactions and improving market modeling accuracy.