A Bi-Level Model for Strategic Bidding of Virtual Power Plant in Day-ahead and Balancing Market

A Bi-Level Model for Strategic Bidding of Virtual Power Plant in Day-ahead and Balancing Market

Today, with the reduced fossil fuel resources and increased environmental concerns, considering the increased use of renewable energy sources in power grids appears to be essential given the great benefits of these resources. The virtual power plant is an extensive energy management system to gather the capacity of interruptible loads, storage devices and distributed products to provide support services for the system and the energy marketing. The main objective of this paper is to provide a method for an optimal virtual power plant bidding strategy considering rivals in a joint day-ahead and balancing market. To this end, a bi-level mathematical optimization model with equilibrium constraints is provided. The first level of this model includes the maximization of the virtual power plant profits, while its second level involves maximizing the level of social welfare. The bi-level model is converted to a Mixed-Integer Linear Programming model using the theory of duality and Karush–Kuhn–Tucker (KKT) optimization conditions. The mentioned model is tested on the Standard IEEE 24-Bus network, which results indicated its effectiveness.

Today, with the reduced fossil fuel resources and increased environmental concerns, considering the increased use of renewable energy sources in power grids appears to be essential given the great benefits of these resources. The virtual power plant is an extensive energy management system to gather the capacity of interruptible loads, storage devices and distributed products to provide support services for the system and the energy marketing. The main objective of this paper is to provide a method for an optimal virtual power plant bidding strategy considering rivals in a joint day-ahead and balancing market. To this end, a bi-level mathematical optimization model with equilibrium constraints is provided. The first level of this model includes the maximization of the virtual power plant profits, while its second level involves maximizing the level of social welfare. The bi-level model is converted to a Mixed-Integer Linear Programming model using the theory of duality and Karush–Kuhn–Tucker (KKT) optimization conditions. The mentioned model is tested on the Standard IEEE 24-Bus network, which results indicated its effectiveness.