F.E. Villaseca

Bio: F.E. Villaseca is an academic researcher from Cleveland State University. The author has contributed to research in topics: Auction theory & Voltage source. The author has an hindex of 2, co-authored 3 publications receiving 14 citations.

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

Abstract: 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 Switching Scheme for Multilevel Converters with Non-Equal DC Sources

Abstract: In this paper, we consider unequal voltage sources of integer multiple magnitudes, in cascaded H-bridge converters. The converter uses (m-1)/2 voltage sources and the proposed switching scheme render an m -level staircase waveform with equal steps. Since the resulting voltage levels are equal, the angles are determined for the complete elimination of (m-1) unwanted harmonics. The implementation of switching scheme, in single and three-phase configurations were simulated with Ansoft -Simplorerreg and the frequency spectrum of the resulting waveform and its THD are shown to verify the results. Source and switch utilization were also evaluated.

Dynamic voltage restorer with active disturbance rejection control

Abstract: Power quality is one of the major concerns among consumers and electric utility companies. Custom power systems (CUPS) devices are used to improve the quality of power and enhance the reliability of the power supply in the distribution networks. The dynamic voltage restorer (DVR) is an important CUPS device used to mitigate voltage sag/swell and imbalances. Various control techniques have been implemented to control a DVR, among which the proportional-integral-derivative (PID) controller is dominant because of its model independent property and its error driven technique. In this paper a new controller based on the active disturbance rejection control (ADRC) concept is developed and its performance is compared to that of the PID controller. The model of the DVR and its ADRC and PID controllers were developed under the MATLAB/Simulink© environment. The simulation results demonstrated the effectiveness of the ADRC over the PID controller.

Optimal Active-Reactive Power Dispatch Under Competition via Bilevel Programming

Abstract: 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.

Strategic Bidding in Secondary Reserve Markets

Abstract: 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.

Real time selective harmonic minimization for multilevel inverters using genetic algorithm and artificial neural network angle generation

Abstract: The work developed here proposes a methodology for calculating switching angles for varying DC sources in a multilevel cascaded H-bridges converter. In this approach the required fundamental is achieved, the lower harmonics are minimized, and the system can be implemented in real time with low memory requirements. Genetic algorithm (GA) is the stochastic search method to find the solution for the set of equations where the input voltages are the known variables and the switching angles are the unknown variables. With the dataset generated by GA, an artificial neural network (ANN) is trained to store the solutions without excessive memory storage requirements. This trained ANN then senses the voltage of each cell and produces the switching angles in order to regulate the fundamental at 120 V and eliminate or minimize the low order harmonics while operating in real time.