Andrés Delgadillo

Analysis of Electric Grid Interdiction With Line Switching

This paper addresses the vulnerability analysis of the electric grid under terrorist threat. This problem is formulated as a mixed-integer nonlinear bilevel program. In the upper-level optimization, the terrorist agent maximizes the damage caused in the power system, which is measured in terms of the level of system load shed. On the other hand, in the lower-level optimization, the system operator minimizes the damage by means of an optimal operation of the power system. The distinctive modeling feature introduced in this paper is that, among the different corrective actions available, the system operator has the capability to modify the network topology. Due to its nonconvexity and nonlinearity, the resulting bilevel programming problem cannot be equivalently transformed into a standard one-level optimization problem. Therefore, this paper proposes a new approach based on Benders decomposition within a restart framework. Some numerical results obtained by the proposed algorithm are provided and compared with those published, based on the IEEE Reliability Test System.

A trilevel programming approach for electric grid defense planning

This paper addresses the allocation of defensive or hardening resources in an electric power grid to mitigate the vulnerability against multiple contingencies. This planning problem is characterized by a defender-attacker-defender model which is formulated as a trilevel programming problem. In the upper level, the system planner identifies the components to be defended or hardened in order to reduce the damage associated with plausible outages. In the middle level, the disruptive agent determines the set of out-of-service components so that the damage in the system is maximized. Finally, in the lower level, the system operator minimizes the damage caused by the outages selected by the disruptive agent by means of an optimal operation of the power system. We propose a novel two-stage solution approach that attains optimality with moderate computational effort. The original trilevel program is first transformed into an equivalent bilevel program, which is subsequently solved by an efficient implicit enumeration algorithm. Numerical results show the effectiveness of the proposed methodology.

A new approach to model load levels in electric power systems with high renewable penetration

In medium- and long-term power system models, it is a common approach to approximate the demand curve by load levels in order to make the models computationally tractable. However, in such an approach, the chronological information between individual hours is lost. In this paper, we propose a novel approach to power system models which constitutes an alternative to the traditional load levels. In particular, we introduce the concept of system states as opposed to load levels, which allows us to better incorporate chronological information in power system models, thereby resulting in a more accurate representation of system outcomes such as electricity prices and total cost. Moreover, the system states can be defined taking into account various important system features at once, as opposed to load levels which are defined using just one specific feature, i.e., demand or net demand. Therefore the system states approach better captures other results such as reserve prices, which are not driven by the usual feature used to define load levels. In a case study, we compare the newly proposed methodology to a standard load level approach, which validates that the system states approach better captures power system outcomes.

Optimizing the Surge Arresters Location for Improving Lightning Induced Voltage Performance of Distribution Network

This paper will deal with improvement of lightning induced voltage performance of distribution network by optimizing the surge arrester location on the distribution network. The optimization of the location is made by using a novel formulation based on genetic algorithms. Here is described the implementation of this methodology by using sophisticate software which has been used for lightning induced voltage analysis. It is also described the capabilities and the limitations of this novel formulation. The performance of the network is evaluated by means of a probability distribution curve obtained from a statistical evaluation of the lightning induced voltages on the distribution line.

Strategic bidding in Colombian electricity market using a multi-agent learning approach

In this paper, a multi-agent model of an electricity market is proposed using the agent-based computational economics (ACE) methodology. The proposed methodology for modeling the bidding price behavior of Generation Companies (GENCOs) is based on a reinforcement learning algorithm (Q-learning) that uses some soft computing techniques to face the discovery of a complex function among bidding prices, states and profits. The proposed model also comprise the power system operation of a large-scale system by simulating optimal DC power flows (DCOPF) in order to obtain real dispatches of agents and a mapping from action space (bidding strategies) to quantities dispatched. In this model, agents are provided with learning capabilities so that they learn to bid depending on market prices and their risk perception so that profits are maximized. The proposed methodology is applied on colombian power market and some results about bidding strategies dynamics are shown. In addition, a new index defined as rate of market exploitation is introduced in order to characterize the agents bidding behavior.

Impact Assessment of Power Quality Limits in Colombia: a Regulatory Approach

In order to improve present regulations about power quality (PQ) in Colombia, an impact assessment of PQ limits among utility companies and customers is presented in this paper. This evaluation takes into account results obtained from a previous project of PQ measurements in Bogota-Colombia (PQB) over a representative sample of end users. This paper evaluates the percentage of users that would be surpassing some proposed limits for PQ disturbances such as: THD, TDD, individual harmonics, unbalance voltage, flicker and unbalance current. This analysis was carried out for industrial and commercial facilities taking into account that these users require higher levels of power quality and therefore may inquire in bigger costs in case of poor power quality conditions compared to other type of users such as residential customers. The results achieved in this work show that for some disturbances is possible to apply a regulation based on international standards as IEC and IEEE but in other parameters their application could become very expensive for utilities and end users

Agent learning methodology for generators in an electricity market

In this paper, a model of the Colombian electricity market is implemented using the agent-based computational economics (ACE) methodology. The paper propose a methodology to model the offer price behavior of generation companies upon the actual colombian market structure and the effects in market prices and agentspsila profits. This model is based on a learning algorithm that uses some soft computing techniques to face the discovery of a complex function among offer prices, power system variables and profits. In addition, this methodology allows the agents to improve their offer strategies by maximizing their own profits. Finally, the paper presents some results obtained from the model about the behavior of spot prices and agents profits.

Implementation of Genetic Algorithms in ATP for Optimal Allocation and Sizing of Active Power Line Conditioners

In last years optimal allocation of active power line conditioner (APLC) at industrial facilities has become an important research subject. In this work the genetic algorithms (GA) are used to determine the allocation and sizing of APLCs. This methodology is implemented in ATP (alternative transients program), and particularly with its components called ATP models routines. The main topic of the paper is to illustrate the process used to achieve the implementation of GA with these components using ATP foreign functions. The structure of chromosome, the genetic operators and a novel concept of ATP models networks are described. The approach proposed is applied on an 11 bus test system, illustrating the minimization of voltage distortion at PCC (point coupling common) and the current harmonic injection of APLCs

A novel approach for the simulation of power quality stationary disturbances in electric power systems

This paper presents a method for calculation of stationary Power Quality Disturbances-PQD based on measurements, distribution system modeling and Monte Carlo techniques. A method to simulate PQD with specific random behavior based on Perfect Sampling is proposed. Three non-sinusoidal conditions power quantities are employed to illustrate the proposed methodology, and a proposal for statistical interpretation of simulated results is presented as well.

Influence of grounding system modeling on Transient analysis of transmission lines due to direct lightning strike

The aim of this paper is to implement different grounding system (GS) models in order to compare its influence on the calculation of overvoltages in transmission lines, produced by direct lightning strikes. The models studied were a lumped DC resistance, a non linear resistance, and a synthesized circuit based on the frequency response of the GS. The latest model is proposed by the authors and takes into account the frequency dependent transient behavior of the GS.