Modified IEEE 30-bus Test System Research Articles

Fuzzy-based voltage/reactive power scheduling for voltage security improvement and loss reduction

This paper presents a new approach using fuzzy set theory for voltage and reactive power control of power systems. The purpose is to find a solution which takes both voltage security enhancement and loss reduction into account for an electric power system. The approach translates violation level of buses voltage and controlling ability of controlling devices into fuzzy set notations using a linearized model. A feasible solution set which achieves voltage improvement is first attained using the max-min operation of fuzzy sets, the final solution which takes power loss reduction into account is then determined employing the min-operation on the feasible solution set previously obtained. A modified IEEE 30-bus test system is used to demonstrate the application of the proposed approach. Simulation results show that the approach is efficient, simple, and straightforward.

Fuzzy-Based Voltage/Reactive Power Scheduling for Voltage Security Improvement and Loss Reduction

This paper presents a new approach using fuzzy set theory for voltage and reactive power control of power systems. The purpose is to find a solution that takes both voltage security enhancement and loss reduction into account for an electric power system. The approach translates violation levels of buses voltage and controlling ability of controlling devices into fuzzy set notations using a linearized model. A feasible solution set that achieves voltage improvement is first attained using the max-min operation of fuzzy sets. The final solution, which takes power loss reduction into account, is then determined employing the min-operation on the feasible solution set previously obtained. A modified IEEE 30-bus test system is used to demonstrate the application of the proposed approach. Simulation results show that the approach is efficient, simple, and straightforward.

VOLTAGE/REACTIVE POWER CONTROL VIA FUZZY LINEAR PROGRAMMING APPROACH

This research presents a fuzzy linear programming method, which employs various membership functions pertaining to constraints and cost functions of system models for voltage reactive power control. Though the problem can be solved by the conventional linear programming approach, the solution from this approach lies on the boundary of the feasible region; hence only a small disturbance is enough to cause the solution to fall outside the constraints. In this research, we develop a fuzzy linear programming model which uses fuzzy set technique to help reach a solution. Because of employment of fuzzy technique, constraints of the system model can be treated lightly such that the presented method is able to consider both cost and security combined. Accordingly, its solution is relatively better compared to that of satisfying hard constraints. A modified IEEE 14-bus test system is used to demonstrate the application of the proposed approach. Computational results show that the proposed method is fairly effective and has the advantage of flexibility.

A new approach to evaluate generation capacity bids

Decision making on capacity addition has become highly complex as the power industry worldwide is undergoing regulatory changes. This paper argues the use of mathematical models to aid the decision makers to select generation capacity bids. A three-stage optimization scheme is developed to accurately estimate the benefits from a specific project. A multiobjective framework to capture both quantitative as well as qualitative information (through expert judgement) has been employed. The model can be used to estimate the marginal benefit from a project and calculate a composite index to rank them in order of their desirability. A case study for modified IEEE 30-bus test system illustrates the methodological issues.

96/01613 Application of Hopt bifurcation theory for determining critical value of generator contol or load parameter

This paper presents a new approach based on a neural network and heuristic model for voltage-reactive power control. The idea is to combine the learning and parallel-processing characteristics of a neural network as well as the fuzzy reasoning of a heuristic model to simplify the problem and improve the efficiency of calculation. The control variables are determined using a neural network type knowledge base and the quantities of the control actions are calculated with the heuristic model. The modified IEEE 30-bus test system is used to demonstrate the application of the proposed approach.

A new fuzzy control approach to voltage profile enhancement for power systems

This paper presents a new approach using fuzzy set theory for voltage and reactive power control of power systems. The purpose is to enhance voltage security of an electric power system. The violation bus voltage and the controlling variables are translated into fuzzy set notations to formulate the relation between voltage violation level and controlling ability of controlling devices. A feasible solution set is first attained using the minimum operation of fuzzy sets, then the optimal solution is quickly determined employing the maximum operation. A modified IEEE 30-bus test system is used to demonstrate the application of the proposed approach. Simulation results show that the approach is efficient and has good flexibility and adaptability for voltage-reactive power control.

Application of a neural network and heuristic model for voltage-reactive power control

This paper presents a new approach based on a neural network and heuristic model for voltage-reactive power control. The idea is to combine the learning and parallel-processing characteristics of a neural network as well as the fuzzy reasoning of a heuristic model to simplify the problem and improve the efficiency of calculation. The control variables are determined using a neural network type knowledge base and the quantities of the control actions are calculated with the heuristic model. The modified IEEE 30-bus test system is used to demonstrate the application of the proposed approach.