William D. Rosehart

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.

Multiobjective optimal power flows to evaluate voltage security costs in power networks

In this paper, new optimal power flow (OPF) techniques are proposed based on multiobjective methodologies to optimize active and reactive power dispatch while maximizing voltage security in power systems. The use of interior point methods together with goal programming and linearly combined objective functions as the basic optimization techniques are explained in detail. The effects of minimizing operating costs, minimizing reactive power generation, and/or maximizing loading margins are then compared in both a 57-bus system and a 118-bus system, which are based on IEEE test systems and modeled using standard power flow models. The results obtained using the proposed mixed OPFs are compared and analyzed to suggest possible ways of costing voltage security in power systems.

Comprehensive control strategy for a variable speed cage machine wind generation unit

A comprehensive control strategy, that addresses all three control objectives in a wind generation system, i.e. control of the local bus voltage to avoid voltage rise, capture of the maximum power in the wind and minimization of the power loss in the induction generator is proposed. The control signals are the desired current wave shapes (instantaneous three-phase currents) of the rectifier and the inverter in a double-sided PWM converter system connected between the wind generating unit and the grid. Studies performed on a complete model for a variable speed cage machine wind generation unit, including wind profile, wind turbine, induction generator, PWM converter, local load and transmission line, show that even as the wind speed changes randomly, the proposed control strategy leads the system to the optimum operating conditions.

A survey of load control programs for price and system stability

Load control and demand side load management programs have been implemented in a large number of competitive power markets. These programs can provide enhanced system security and many benefits to participants. This paper reviews and compares existing economically driven programs.

Optimal power flow with complementarity constraints

This paper proposes a mathematical program with complementarity constraints to better model the relationship between the base, or current, operating point and the maximum loading point in a power system when solving maximum loading problems.

Bifurcation analysis of various power system models

This paper presents the bifurcation analysis of a detailed power system model composed of an aggregated induction motor and impedance load supplied by an under-load tap-changer transformer and an equivalent generator and transmission system. Different modeling levels with their respective differential-algebraic equations are studied, to determine the minimum dynamic model of the system that captures the most relevant features needed for bifurcation studies of power systems. An aggregated model of a realistic load is used to illustrate the ideas presented throughout the paper.

Effect of detailed power system models in traditional and voltage-stability-constrained optimal power-flow problems

Detailed generator, exponential load, and static var compensator models are incorporated into both traditional and voltage stability constrained optimal power flow problems to study the effect that the different models have on costs and system loadability. The proposed models are compared to typical models by means of a detailed analysis of the results obtained for two IEEE test systems; interior point methods are used to obtain numerical solutions of the associated optimization problems.

Probabilistic Power Flow by Monte Carlo Simulation With Latin Supercube Sampling

In this paper, a Latin supercube sampling (LSS) combined with Monte Carlo simulation is presented to efficiently sample random variables in the probabilistic power flow (PPF) problem. The results of the LSS method are compared with other techniques, namely Latin hypercube sampling (LHS) and simple random sampling (SRS), using bin-by-bin histogram comparison. The simulation results are presented for the case of IEEE 118-bus test system.

An Optimal Power Flow Algorithm to Achieve Robust Operation Considering Load and Renewable Generation Uncertainties

Consideration of uncertain injections in optimal power flow (OPF) calculation is increasingly important because more renewable generators, whose outputs are variable and intermittent, are connected into modern power systems. Since it is often difficult to predict the variations of both load and renewable generator output accurately, this paper proposes an OPF algorithm to make optimized results not only have a high probability to achieve minimized generation cost, but also robust to the uncertain operating states. In this paper, the objective of the OPF is to minimize the generation cost of the scenario which has the largest probability to appear in the future. In order to make the OPF result be able to accommodate other possible scenarios, the OPF constraints are modified. Considering the probabilistic distributions of both load and renewable energy output, the modified constraints are derived from Taguchis orthogonal array testing and probabilistic power flow calculation. The effectiveness of the proposed OPF method is demonstrated by the cases up to the system with 2736 buses.

Evenly distributed pareto points in multi-objective optimal power flow

This letter presents a normal boundary intersection method to form the Pareto surface for power system multi-objective optimization problems.