Resumen:
This paper presents a conjectured-price-response equilibrium approach for modeling both centralized generation (CG) and behind-the-meter distributed generation (BMDG). A Nash game is set up with two constraints linking the CG and BMDG decisions to satisfy both the electricity demand in an energy market and the firm capacity in a capacity market. CG agents maximize their market profits while BMDG customers minimize their net supply costs, making decisions on their annual capacity investments and hourly productions decisions. Customers’ costs account for 1) the energy bought from the grid minus the BMDG energy surpluses sold; 2) the payment of the grid access tariff (power and energy-based terms) and 3) the BMDG capacity investments’ costs. The equilibrium conditions enable to represent different degrees of oligopoly using conjectural variations in both the energy and capacity markets. This work proves that such an equilibrium problem can be solved through an equivalent, yet simpler-to-solve, quadratic minimization problem. Some case examples compare the results of the proposed joint energy and capacity equilibrium with those from an energy-only equilibrium. Among other conclusions, these cases show that the proposed equilibrium sends adequate economic signals to the consumers to taper off the total system peak demand, whenever the weight of the power-based term of the access tariff is not extremely high.
Palabras Clave: Generation expansion; Distributed generation; Energy and capacity markets; Capacity payments; Nash equilibrium
Índice de impacto JCR y cuartil WoS: 5,659 - Q1 (2021); 5,200 - Q1 (2022)
Referencia DOI:
https://doi.org/10.1016/j.ijepes.2021.107055
Publicado en papel: Octubre 2021.
Publicado on-line: Abril 2021.
Cita:
S. Doménech, F.A. Campos, J. Villar, M. Rivier, Joint energy and capacity equilibrium model for centralized and behind-the-meter distributed generation. International Journal of Electrical Power & Energy Systems. Vol. 131, pp. 107055-1 - 107055-13, Octubre 2021. [Online: Abril 2021]
