Joint energy and reserve markets: current implementations and modeling trends

Bidding strategy for battery storage systems in the secondary control reserve market

This paper proposes an active-reactive power dispatch procedure that is expressed via a bilevel optimization problem whose upper and lower level criteria are, respectively, the minimum opportunity cost and minimum offered price of active power. It analyzes the impact of minimizing such criteria on system operation, and it investigates the behavior of marginal prices and opportunity costs and their use in mechanisms to compensate generators for power provision. The bilevel problem is solved using a version of interior point methods derived for mathematical programs with complementarity constraints. Results obtained with three test systems are analyzed.

Optimal Active-Reactive Power Dispatch Under Competition via Bilevel Programming

Electricity markets are based on several sequential energy and reserve trading mechanisms to constantly maintain the balance between generation and demand. During the last years, reserve markets are getting much importance all around the world with the increasing social awareness of the renewable energy benefits. Additional reserve quantities and larger remunerations are being implemented by the regulators since this renewable energy is highly dependent on weather conditions uncertainties. Utilities are therefore demanding more and more powerful models to better optimize their reserve bidding curves to be sent to the system operators. This paper describes a new methodology to obtain an optimized real bidding curve for the secondary (spinning) reserve market. The approach is based on the maximization of a company profit, assuming a set of residual demand curves scenarios for its competitors' representation, and considering the day-ahead market opportunity cost to build the reserve cost curve. The case study validates the main features of the proposed methodology by its application to the Spanish secondary reserve market. This methodology is being daily used by one of the most important electricity companies in Spain.

Strategic Bidding in Secondary Reserve Markets

This paper presents an agent-based simulator for examination of a secondary control market dominated by hydro power producer as decision support for one of the market participants. Proposed is a Q-learning algorithm for determining possible strategic behavior. Adaptive learning is made possible by application of certain characteristics to agents quantity-price pairs bids. Considered are for each agent its portfolio of different hydro power plants with their water values estimated by a stochastic dynamic programming scheme. The simulator is applied to the Swiss system where strategic behavior will be shown. Additionally it is analyzed how single agents could make use of strategic behavior in case of special occurrences in the market.

Strategic bidding of ancillary services for a hydro power producer

This paper describes a simple method to derive strategic equilibrium solutions for a single Generating Company (GENCO) bidding in electricity markets. This method computes the product mix of real power and the ancillary services of reactive power and spinning reserve supplied by GENCO. Generator capability curves are incorporated into a two-player competitive market model to simulate market auctions for real power and ancillary services. Player 1 is defined as the GENCO entering the auction and Player 2 is the equivalent representation of all other GENCOs competing in the auction. Game theory techniques are utilized to identify optimal Nash Equilibrium solutions for the power market auctions, which are optimal bidding strategies for the competing players. Software was developed to automatically simulate the market auction and identify equilibrium solutions from a defined combination of bidding strategies. Simulations demonstrate that the computed equilibrium solution optimizes the GENCO's payoff.

A.G. Morinec

Papers

Optimal generator bidding strategies for power and ancillary services using game theory