(1990). ENERGY FUNCTION ANALYSIS FOR POWER SYSTEM STABILITY. Electric Machines & Power Systems: Vol. 18, No. 2, pp. 209-210.

Energy function analysis for power system stability

Consideration of transient stability constraints in optimal power flow (OPF) problems is increasingly important because modern power systems tend to operate closer to stability boundaries due to the rapid increase of electricity demand and the deregulation of electricity markets. Transient stability constrained OPF (TSCOPF) is however a nonlinear optimization problem with both algebraic and differential equations, which is difficult to be solved even for small power systems. This paper develops a robust and efficient method for solving TSCOPF problems based on differential evolution (DE), which is a new branch of evolutionary algorithms with strong ability in searching global optimal solutions of highly nonlinear and nonconvex problems. Due to the flexible properties of DE mechanism, the hybrid method for transient stability assessment, which combines time-domain simulation and transient energy function method, can be employed in DE so that the detailed dynamic models of the system can be incorporated. To reduce the computational burden, several strategies are proposed for the initialization, assessment and selection of solution individuals in evolution process of DE. Numerical tests on the WSCC three-generator, nine-bus system and New England ten-generator, 39-bus system have demonstrated the robustness and effectiveness of the proposed approach. Finally, in order to deal with the large-scale system and speed up the computation, DE is parallelized and implemented on a Beowulf PC-cluster. The effectiveness of the parallel DE approach is demonstrated by simulations on the 17-generator, 162-bus system.

Application of Differential Evolution Algorithm for Transient Stability Constrained Optimal Power Flow

In this paper, a new hybrid intelligent system is proposed for transient stability prediction. This intelligent system is composed of a preprocessor, an array of neural networks (NN) and an interpreter. The preprocessor partitions the whole set of synchronous machines into subsets, each one including only two generators. Each subset is assigned to one NN, which extracts the input/ output mapping function of that subset. Then, the interpreter combines the responses of the NNs in a voting procedure to determine the transient stability status of the power system. This mechanism can cover the probable errors of the NNs, increasing the accuracy of the final response of the hybrid intelligent system. In addition to the transient stability status, this intelligent system can determine tripped generators and islanded parts of the power system for unstable cases. The proposed method has been examined on the PSB4 and New England test systems. The obtained results indicate the efficiency of the hybrid intelligent system for transient stability prediction.

Transient Stability Prediction by a Hybrid Intelligent System

This paper presents a comprehensive survey on application of various conventional, optimization and artificial intelligence (AI) based computational techniques for impact assessment of optimally placed and coordinated control of distributed generations (DGs) and flexible AC transmission systems (FACTS) controllers in power systems (PSs). This review work is presented from the viewpoint of different performance criterion enhancement of PSs such as minimization of active and reactive power losses and reduction of cost of system, more flexible operation and control, increase overall system energy efficiency, increase reliability of system, relieved transmission and distribution congestion, enhance power quality (PQ) of system, improve the voltage profile (VP), increase the loadability of systems, increase available power transfer capacity (APTC) of system, enhance PS stability, reduce PS oscillations, improve environmental GHG conditions and provide the reactive power support in emergency case such as under fault, sudden change in field excitation of alternators or load increase in PSs. This paper also presents the current status of the various conventional, optimization, and AI computational techniques for optimally placed and coordinated control of DG and FACTS controllers in PSs for enhancement of PSs performance parameters. Authors strongly believe that this survey will be very much useful to the researchers, scientific engineers, industrial persons working in this area to find out the relevant references and current state of the art.

A survey on impact assessment of DG and FACTS controllers in power systems

Multi-objective congestion management by modified augmented ε-constraint method

This paper presents a new approach for determining the effectiveness of preventive generation rescheduling and shunt/series compensation in improving transient stability using trajectory sensitivity (TS) method. It is shown that the effectiveness of changes in parameter values can be judged by evaluating the TS of certain variables with respect to clearing time. Therefore, the need to evaluate a host of sensitivities with respect to many parameters is obviated. This heuristic is motivated by the fact that for simple models and small changes, controllability of trajectories using certain parameters can be inferred from observability in certain output signals. An example of such a parameter and signal pair is shunt susceptance at a bus and the square of voltage at that bus, respectively. Case studies are carried out on a 10-machine 39-bus system with detailed models and 17-machine system to validate this method.

Determination of effectiveness of transient stability controls using reduced number of trajectory sensitivity computations

In this paper, a structure preserving energy margin (EM) sensitivity-based analysis is presented to determine the amount of preventive generation rescheduling to stabilize a transiently unstable power system. An expression using a simplified model is derived to relate the change in the EM to change in generation. Utilising this expression, two approaches for generation rescheduling are developed which are applicable to detailed model of power systems. The proposed methods are applied to the 10-machine New England power system and 16-machine power system with detailed power system models.

Stability-constrained generation rescheduling using energy margin sensitivities

This paper presents a structure preserving energy margin sensitivity based analysis to determine the effectiveness of FACTS devices to improve transient stability of a power system. A structure preserving energy model, which retains the topology of the network is used to derive simple analytical expressions for improvement in energy margin due to series or shunt compensation. The expressions are in terms of current magnitude through a line for series compensation and voltage magnitude at a bus for shunt compensation. Therefore, these expressions are easy to interpret in the context of applying compensation at strategic locations. The proposed method is applied to a four-machine, ten-bus system and a ten-machine, 39-bus New England system, and its validity is demonstrated through time domain simulations both for a classical and detailed model with AVR for generators.

Application of Structure Preserving Energy Margin Sensitivity to Determime the Effectiveness of Shunt and Serles FACTS Devices

In this paper, a Power Flow (PF) algorithm for a Power Distribution System (DS) derived from the conventional backward-forward sweep method is simulated with the integration of Solar Photovoltaic (SPV) based distributed generation. This integration algorithm is based on the load current injection, where the SPV generation is modeled as a negative load injection at one of the nodes of the DS. In this method, the PF solution is obtained by executing both the sweeps in a single step through a Load Current to Bus Voltage (LCBV) matrix. The SPV system is integrated considering an additional inverter node connected to one of the nodes of DS through the SPV interfacing elements. Based on the control specification at the inverter node, it may operate either in PV or PQ mode. The SPV inverter node voltage is computed using an alternate-iterative method in a separate algorithm. The effectiveness of the modified PF algorithm is verified on the balanced DS, considering diverse test systems (IEEE-33 node, IEEE-69 node DS). The qualitative aspects of the algorithm are analyzed and compared with the existing conventional technique.

K.N. Shubhanga

Papers

Determination of effectiveness of transient stability controls using reduced number of trajectory sensitivity computations

Stability-constrained generation rescheduling using energy margin sensitivities

Application of Structure Preserving Energy Margin Sensitivity to Determime the Effectiveness of Shunt and Serles FACTS Devices

Power Flow Analysis of Power Distribution System Integrated with Solar Photovoltaic Based Distributed Generation

Power system event detection and localization—A new approach