Power system simulation

About: Power system simulation is a research topic. Over the lifetime, 6447 publications have been published within this topic receiving 154516 citations.

Impacts of Wind Power on Thermal Generation Unit Commitment and Dispatch

Abstract: This paper proposes a new simulation method that can fully assess the impacts of large-scale wind power on system operations from cost, reliability, and environmental perspectives. The method uses a time series of observed and predicted 15-min average wind speeds at foreseen onshore- and offshore-wind farm locations. A Unit Commitment and Economic Dispatch (UC-ED) tool is adapted to allow for frequent revisions of conventional generation unit schedules, using information on current wind energy output and forecasts for the next 36 h. This is deemed the most faithful way of simulating actual operations and short-term planning activities for a system with large wind power penetration. The problem formulation includes ramp-rate constraints for generation schedules and for reserve activation, and minimum up-time and down-time of conventional units. Results are shown for a realistic future scenario of the Dutch power system. It is shown that problems such as insufficient regulating and reserve power-which are typically associated with the variability and limited predictability of wind power-can only be assessed in conjunction with the specifics of the conventional generation system that wind power is integrated into. For the thermal system with a large share of combined heat and power (CHP) investigated here, wind power forecasting does not provide significant benefits for optimal unit commitment and dispatch. Minimum load problems do occur, which result in wasted wind in amounts increasing with the wind power installed

Point Estimate Schemes to Solve the Probabilistic Power Flow

Abstract: This paper analyzes the behavior of Hong's point estimate methods to account for uncertainties on the probabilistic power flow problem. This uncertainty may arise from different sources as load demand or generation unit outages. Point estimate methods constitute a remarkable tool to handle stochastic power system problems because good results can be achieved by using the same routines as those corresponding to deterministic problems, while keeping low the computational burden. In previous works related to power systems, only the two-point estimate method has been considered. In this paper, four different Hong's point estimate schemes are presented and tested on the probabilistic power flow problem. Binomial and normal distributions are used to model input random variables. Results for two different case studies, based on the IEEE 14-bus and IEEE 118-bus test systems, respectively, are presented and compared against those obtained from the Monte Carlo simulation. Particularly, this paper shows that the use of the scheme provides the best performance when a high number of random variables, both continuous and discrete, are considered.

Optimization of Power System Operation

Abstract: Preface. 1 Introduction. 1.1 Conventional Methods. 1.2 Intelligent Search Methods. 1.3 Application of Fuzzy Set Theory. 2 Power Flow Analysis. 2.1 Mathematical Model of Power Flow. 2.2 Newton-Raphson Method. 2.3 Gauss-Seidel Method. 2.4 P-Q decoupling Method. 2.5 DC Power Flow. 3 Sensitivity Calculation. 3.1 Introduction. 3.2 Loss Sensitivity Calculation. 3.3 Calculation of Constrained Shift Sensitivity Factors. 3.4 Perturbation Method for Sensitivity Analysis. 3.5 Voltage Sensitivity Analysis. 3.6 Real-Time Application of Sensitivity Factors. 3.7 Simulation Results. 3.8 Conclusion. 4 Classic Economic Dispatch. 4.1 Introduction. 4.2 Input-Output Characteristic of Generator Units. 4.3 Thermal System Economic Dispatch Neglecting Network Losses. 4.4 Calculation of Incremental Power Losses. 4.5 Thermal System Economic Dispatch with Network Losses. 4.6 Hydrothermal System Economic Dispatch. 4.7 Economic Dispatch by Gradient Method. 4.8 Classic Economic Dispatch by Genetic Algorithm. 4.9 Classic Economic Dispatch by Hopfi eld Neural Network. 5 Security-Constrained Economic Dispatch. 5.1 Introduction. 5.2 Linear Programming Method. 5.3 Quadratic Programming Method. 5.4 Network Flow Programming Method. 5.5 Nonlinear Convex Network Flow Programming Method. 5.6 Two-Stage Economic Dispatch Approach. 5.7 Security-Constrained ED by Genetic Algorithms. 6 Multiarea System Economic Dispatch. 6.1 Introduction. 6.2 Economy of Multiarea Interconnection. 6.3 Wheeling. 6.4 Multiarea Wheeling. 6.5 MAED Solved by Nonlinear Convex Network Flow Programming. 6.6 Nonlinear Optimization Neural Network Approach. 6.7 Total Transfer Capability Computation in Multiareas. 7 Unit Commitment. 7.1 Introduction. 7.2 Priority Method. 7.3 Dynamic Programming Method. 7.4 Lagrange Relaxation Method. 7.5 Evolutionary Programming-Based Tabu Search Method. 7.6 Particle Swarm Optimization for Unit Commitment. 7.7 Analytic Hierarchy Process. 8 Optimal Power Flow. 8.1 Introduction. 8.2 Newton Method. 8.3 Gradient Method. 8.4 Linear Programming OPF. 8.5 Modifi ed Interior Point OPF. 8.6 OPF with Phase Shifter. 8.7 Multiple-Objectives OPF. 8.8 Particle Swarm Optimization for OPF. 9 Steady-State Security Regions. 9.1 Introduction. 9.2 Security Corridors. 9.3 Traditional Expansion Method. 9.4 Enhanced Expansion Method. 9.5 Fuzzy Set and Linear Programming. 10 Reactive Power Optimization. 10.1 Introduction. 10.2 Classic Method for Reactive Power Dispatch. 10.3 Linear Programming Method of VAR Optimization. 10.4 Interior Point Method for VAR Optimization Problem. 10.5 NLONN Approach. 10.6 VAR Optimization by Evolutionary Algorithm. 10.7 VAR Optimization by Particle Swarm Optimization Algorithm. 10.8 Reactive Power Pricing Calculation. 11 Optimal Load Shedding. 11.1 Introduction. 11.2 Conventional Load Shedding. 11.3 Intelligent Load Shedding. 11.4 Formulation of Optimal Load Shedding. 11.5 Optimal Load Shedding with Network Constraints. 11.6 Optimal Load Shedding without Network Constraints. 11.7 Distributed Interruptible Load Shedding. 11.8 Undervoltage Load Shedding. 11.9 Congestion Management. 12 Optimal Reconfi guration of Electrical Distribution Network. 12.1 Introduction. 12.2 Mathematical Model of DNRC. 12.3 Heuristic Methods. 12.4 Rule-Based Comprehensive Approach. 12.5 Mixed-Integer Linear Programming Approach. 12.6 Application of GA to DNRC. 12.7 Multiobjective Evolution Programming to DNRC. 12.8 Genetic Algorithm Based on Matroid Theory. 13 Uncertainty Analysis in Power Systems. 13.1 Introduction. 13.2 Defi nition of Uncertainty. 13.3 Uncertainty Load Analysis. 13.4 Uncertainty Power Flow Analysis. 13.5 Economic Dispatch with Uncertainties. 13.6 Hydrothermal System Operation with Uncertainty. 13.7 Unit Commitment with Uncertainties. 13.8 VAR Optimization with Uncertain Reactive Load. 13.9 Probabilistic Optimal Power Flow. 13.10 Comparison of Deterministic and Probabilistic Methods. Author Biography. Index.

Wide-area measurement based stabilizing control of large power systems-a decentralized/hierarchical approach

Abstract: The aim of this paper is to assess the capability of the emerging synchronized phasor measurement technology in improving the overall stability of the Hydro-Quebec transmission system through supplementary modulation of voltage regulators. Following a thorough singular value and eigenvalue analysis of the system dynamic interactions, five control sites consisting of four generators and one synchronous condenser are chosen to implement new power system stabilizers with a supplementary input from remote phasor measuring units, geographically spread over nine electrically coherent areas. Since the remote feedback loops are built on top of an existing decentralized control system, this design approach results in a decentralized/hierarchical control architecture with significant advantages in terms of reliability and operational flexibility. A systematic control and measurement pairing yielded four dominant natural loops, each associated with a significant open-loop inter-area oscillatory mode at 0.06, 0.4, 0.7 and 0.95 Hz respectively. These PSSs have a speed sensitive local loop operating in the usual way, and a wide-area measurement based global loop which involves a single differential frequency signal between two suitably selected areas. The tuning and coordination technique for these advanced multiple input signals PSSs is described. Their impacts on the system is assessed using both small-signal analysis and nonlinear simulations in a transient stability program. Wide-area stabilizing controllers have a significant potential in improving the dynamic performance of the Hydro-Quebec's existing power system.

Stability Simulation Of Wind Turbine Systems

Abstract: A simulation and digital computer modeling effort is described in which a wind turbine- generator system is adapted for stability evaluation using a large scale transient stability computer program. Component models of the MOD-2 wind generator system are described and their digital model equations are provided. A versatile wind velocity model is described, which provides the capability of simulating a wide variety of wind variations, in addition to the usual network disturbances. Computed results obtained from runs of the enhanced stability program are provided that illustrate the wind turbine-generator system dynamic performance for changes in wind velocity.