José A. Aguado

Multi-area coordinated decentralized DC optimal power flow

This paper provides a framework to carry out a multi-area optimal power flow in a coordinated decentralized fashion. A DC nonlinear optimal power flow model is used. Losses are incorporated through additional loads based on cosine approximations. The model makes it possible the independent optimal dispatch of each area while the global economical optimum of the whole electric energy system is achieved. This is possible by means of the Lagrangian relaxation decomposition procedure. Optimal energy pricing rates for the energy traded through the interconnections are derived. The developed algorithm can be run in parallel either to carry out numerical simulations or in an actual multi-area electric energy system.

Cumulant-based probabilistic optimal power flow (P-OPF) with Gaussian and gamma distributions

This paper introduces the cumulant method for the probabilistic optimal power flow (P-OPF) problem. By noting that the inverse of the Hessian used in the logarithmic barrier interior point can be used as a linear mapping, cumulants can be computed for unknown system variables. Results using the proposed cumulant method are compared against results from Monte Carlo simulations (MCSs) based on a small test system. The Numerical Results section is broken into two sections: The first uses Gaussian distributions to model system loading levels, and cumulant method results are compared against four MCSs. Three of the MCSs use 1500 samples, while the fourth uses 20 000 samples. The second section models the loads with a Gamma distribution. Results from the proposed technique are compared against a 1000-point MCS. The cumulant method agrees very closely with the MCS results when the mean value for variables is considered. In addition, the proposed method has significantly reduced computational expense while maintaining accuracy.

Inter-Utilities Power-Exchange Coordination: A Market-Oriented Approach

A decentralized operation of the transmission grid for scheduling inter-utilities power exchanges is proposed. This approach is well suited for market-oriented environments; it achieves a market equilibrium while the operational independence of each interconnected utility is preserved. We employ decomposition-coordination techniques in combination with an interior-pointlcutting-plane method in order to reduce the number of iterations of the decomposition algorithm. The paper includes test results on IEEE-based systems.

Cumulant-based stochastic nonlinear programming for variance constrained voltage stability analysis of power systems

This paper proposes a Cumulant Method-based solution to solve a maximum loading problem incorporating a constraint on the maximum variance of the loading parameter. The proposed method takes advantage of some properties regarding saddle node bifurcations to create a linear mapping relationship between random bus loading variables and all other system variables. The proposed methodology is tested using a sample system based on the IEEE 30-bus system using random active and reactive bus loading. Monte Carlo simulations consisting of 10 000 samples are used as a reference solution for evaluation of the accuracy of the proposed method.

Optimal Sizing of Energy Storage for Regenerative Braking in Electric Railway Systems

The problem of optimally sizing hybrid energy storage systems (HESS) installed in electric railway systems, considering the effect of regenerative braking is studied in this paper. HESSs combine traditional batteries and newly developed ultracapacitors, taking advantage of the high energy capacity of batteries and of the flexibility and ability to capture high power density of ultracapacitors. A novel mixed integer linear programming formulation that includes the counting of battery cycles is presented. Some particularities of battery operation are included in the model, like the dependence of its performance on the number of cycles and the depth of discharge (DOD). Results are reported first for a illustrative case study, allowing us to perform sensitivity studies for several parameters; results are also reported and for a larger case, closely resembling the problem faced by railway energy systems planners and operators.

Coordinated spot market for congestion management of inter-regional electricity markets

The rapid growth of inter-regional trading among electricity markets requires the development of new market-oriented mechanisms for the inter-regional congestion management of such trading. In this paper, we deal with the operation of power systems consisting of several interconnected electricity markets. We propose an alternative approach to inter-regional trade that avoids the flaws of forward markets with explicit auctioning of interconnections capacities. We propose the integration of a forward market with a balancing (spot) market for inter-regional exchanges based on nodal pricing. The interaction of transmission system operators (TSOs) belonging to adjacent markets is efficiently taken into account through a decentralized optimal power flow (OPF), which is solved by interior point methods.

A Stochastic Two Settlement Equilibrium Model for Electricity Markets With Wind Generation

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.

Optimal microgrid operation with electric vehicles

The concern about the complete depletion of fossil fuels along with the negative environmental impact of most of the current energy sources are significant reasons to think of a different way to produce electrical energy and, at the same time, satisfy the necessities for urban mobility. In this context, microgrids (MGs) are power networks which, among other properties, allow more flexible demand consumption, and also help with, the efficient integration of renewable resources and electric vehicles (EVs). However, the effect of the incorporation of EVs has to be taken into consideration with care, since that situation may drive to unfeasible operations in grids which have not been designed to support these particular elements. In this paper, a system composed of different agents is used to develop a market-oriented operation in a MG with several EV charge stations. It is expected that the system takes to an optimal management allowing a technically feasible operation considering the behaviour of every agent involved. The demand shifting and the flexible operation of EVs, spatial and temporal, are features that reduce costs and thus improve the benefit of the participants.

Time-frequency transforms comparison for power quality analysis

Voltage signal contains transient disturbances that are caused for multiple reasons. One way to improve the power quality is to analyze efficiently and to deeply understand these signals. The most typical disturbances in power quality have been generated in order to analyze by time-frequency transforms: wavelet transforms (WT) and S-transform (ST). Thus can be obtained a comparison of results of these time-frequency transforms. The voltage signals with different disturbances are simulated by Matlab code with 128 samples per cycle. The disturbances used in this work are carried out from standards, as voltage sag, voltage swell, short interruptions and harmonic distortion, in addition to other disturbances of transitory order as spikes, notches and oscillatory transients.

Sensitivity analysis of component's tolerance in Inductively Coupled Power Transfer system

ICPT systems help drivers to recharge their electrical vehicles via wireless. The core of the system is a pair of coils and two reactive structures. In order to predict the performance of a practical implementation, it is necessary to study the impact of using real components which suffer from variations in their nominal values. Basing on the performed study, we conclude that the components on the side where the inductance is in series with the capacitance should be carefully selected as variations in their values greatly affect the system performance. A 50 kW system has been evaluated in terms of efficiency and load voltage.