Incentives to encourage the uptake of renewable energy generation have fostered wind energy in many power systems. These incentives usually take the form of market instruments (e.g., feed-in tariff or premium) that are not directly amenable to optimization representations of the market. In this paper, we propose an equilibrium model of the short-term market to address the impact of wind operation under different structural assumptions. The model is formulated for several price taking, risk averse firms in competition. It accounts for wind generation uncertainty and embeds a representation of the day ahead and balancing mechanisms. The consumer is modeled by a linear inverse demand function. We focus on feed-in premium as the incentive to wind as this is the instrument most favored today in European discussions. The model is formulated as a stochastic equilibrium problem where the Karush-Kuhn-Tucker (KKT) conditions from the optimization problem of each firm are simultaneously solved together with market clearing conditions on energy, capacity for reserve and energy for reserve. The problem for each firm consists of a two-stage stochastic optimization problem with a recourse function based on the conditional value at risk ( CVaRθ) as a risk measure. Due to price taking assumptions the model is a single stage complementarity problem; it is implemented and solved using the software GAMS. An example based on a stylized simplification of the Spanish power market and motivated by the impact of wind penetration on the revenue of conventional plants is used to illustrate the proposed approach.

Wind and Solar photovoltaic power plants outputs are usually highly variable due to gusts of wind and sharp sun irradiance level variations caused by cloud shading effects. These effects negatively impact system security, especially in weak power networks. On the other hand, due to the recent technological progress and cost reductions, electrical energy storage systems are an attractive alternative that can be easily integrated into non‐despatchable power plants to compensate for those power output fluctuations. This study proposes a methodology for optimal sizing of a hybrid (lithium‐ion battery and ultracapacitor) energy storage system for renewable energy network integration. Special attention is paid to the battery cycling degradation process. It is shown that battery aging due to cycling is a major driver for optimal sizing. The resulting sizing problem is posed as a non‐linear programming problem. Finally, real and illustrative case studies are presented for both, wind and photovoltaic power plants integrating a hybrid energy storage system. Results are reported by comparing different energy storage system configurations.

Transitioning from fossil fuel dominated power systems to high penetrations of intermittent renewable generation is affecting classical electricity market designs. Here, a method is proposed to model and assess the absence of co-optimization of energy and reserve that prevails in the European system. Co-optimization is formulated through an optimization problem (COM), and its absence as an equilibrium problem (EQM) built on Karush-Kuhn-Tucker conditions of agents’ optimization and market clearing equations. EQM cannot be reformulated as a single optimization problem. Market distortions are identified by comparing the complementarity conditions of both models. These are then discussed on system with Feed in Premium to wind generation. Parameters in the models allow to represent different market configurations regarding: available wind generation, Feed in Premium to wind, generators’ risk aversion, and required reserve from wind generation.