M. Abdullah Khan

Optimal short-term hydrothermal scheduling using decomposition approach and linear programming method

Abstract The operational planning problem of hydrothermal scheduling for the next days demand in a power system is concerned with the determination of generation schedules for hydro and thermal plants to meet the daily system demand so that the total fuel cost of the thermal plants over the day is minimized subject to the operating constraints associated with the thermal and hydro plants as well as the network security constraints. This paper presents an effective algorithm which decomposes the problem into hydro and thermal subproblems and solves them alternatively. While the hydro subproblem is solved using a search procedure, the local variation method, the thermal subproblem is solved using the participation factors/Linear Programming method. The algorithm is very effective in enforcing security constraints and gives an optimal generation schedule which can be readily implemented for the next day. Results obtained from a 9-bus system and a 66-bus utility system demonstrate the effectiveness of the proposed algorithm.

Stability enhancement of a multimachine power system using fuzzy logic based power system stabilizer tuned through genetic algorithm

The paper presents a procedure for application of Fuzzy logic Power System Stabilizer (FPSS) for stability enhancement of a multimachine power system. The location of Power System Stabilizer (PSS) is determined using critical modes and participation factors for different operating conditions. A simple configuration is chosen for FPSS with a speed deviation of synchronous generator and its derivative as input signals. The parameters of the stabilizers are tuned through simulation of non-linear model of power system under chosen disturbance using Crowding Genetic Algorithm (CGA) to minimize a Root Mean Square Deviation (RMSD) index of the concerned state variable which maximizes the damping of the critical mode. Results obtained from a two area, five generator power system indicate the improved performance of FPSS over conventional PSS.

An efficient multi-objective fuzzy logic based successive LP method for optimal reactive power planning

Abstract This paper presents a new and efficient method to solve the Optimal Reactive Power Planning (ORPP) problem, simultaneously minimising transmission losses and improving voltage profile using Multi-objective Fuzzy logic based LP (MFLP) model in Successive Linear Programming (SLP) framework. The ORPP problem is concerned with optimally siting and sizing new capacitors at prospective sites in a planned grid with projected load demands such that, minimum number and quantum of new capacitors are allocated, the transmission losses are minimised and a satisfactory voltage profile is obtained. In this paper, all the prospective capacitor locations are ranked using Voltage Performance Index (VPI) based on sensitivity factors. From the top of the ranked list, a minimum number of locations are chosen for siting new capacitors. Reactive powers at these selected capacitor sites along with generator voltage magnitudes, reactive powers of existing switchable VAR sources and on-load tap changer (OLTC) settings of transformers are used as control variables in this method. In the MFLP framework, each of the objectives and each of the constraints are assigned a satisfaction parameter. The satisfaction parameter corresponding to any objective quantifies the degree of closeness of the current state of the objective to the optimum. The satisfaction parameter corresponding to a constraint describes the degree of enforcement of that constraint. By maximising the minimum of these satisfaction parameters, the objectives are optimised and the constraint enforcements are maximised. The MFLP based SLP method is found to be very effective while planning for systems which have severe under-voltage violations due to insufficient reactive powers, as the method is capable of selectively relaxing certain load voltage constraints, while simultaneously enforcing all other constraints strictly. The MFLP technique optimises all the objectives, i.e. minimises number and quantum of new capacitors, minimises transmission losses and maximises constraint enforcement of all violated constraints, while simultaneously imposing all other problem constraints strictly. This method uses compactly stored, factorised constant matrices in all MFLP steps, both for construction of the MFLP model as well as for the power flow solution. The method was tested on IEEE test systems and on a practical 191 bus electric utility system. The merits of the method, compared with SLP method using non-fuzzy approach, are brought out.

Design of a robust power system stabilizer using fuzzy logic for a multi-machine power system

This paper presents a design procedure for a fuzzy logic based power system stabilizer (FPSS) and investigates the robustness of the FPSS for a multi-machine power system. Speed deviation of synchronous generator and its derivative are chosen as the input signals to the FPSS. A two area, five generator power system is used to illustrate the robustness of the FPSS. A normalized sum-squared deviation (NSSD) index is used for designing the FPSS and demonstrating its robustness. Nonlinear simulation tests for different disturbances and their results are discussed.

Fuzzy Logic Based Successive LP Method for Reactive Power Optimization

This paper presents a new Successive Fuzzy Linear Programming (SFLP) method for Reactive Power Optimization (RPO) to minimize the transmission loss and improve the voltage profile. The SFLP method uses Fuzzy LP (FLP) model in the Successive Linear Programming (SLP) framework to solve the RPO problem. In the FLP model, the objective and each of the constraints are assigned a satisfaction parameter. The satisfaction parameter corresponding to the objective quantifies the degree of closeness of the objective in the current state to the optimum. The satisfaction parameter corresponding to a constraint describes the degree of enforcement of that constraint. By maximizing the minimum of these satisfaction parameters, the objective as well as the constraint enforcements are maximized. The SFLP method of RPO is efficient and reliable in scheduling systems having severe under-voltages and insufficient reactive power, as the method is capable of maximizing the enforcement of the violated load bus voltage constraint...

Impact of FACTS Controllers on the Dynamic Stability of Power Systems Connected with Wind Farms

The increasing power demand has led to the growth of new technologies that play an integral role in shaping the future energy market. Keeping in view of the environmental constraints, grid connected wind turbines are promising in increasing system reliability. This paper presents the impact of Flexible A.C. Transmission System (FACTS) controllers on the dynamic stability of power systems connected with wind energy conversion systems. The wind generator model considered is a variable speed doubly - fed induction generator model. The stability assessment is made first for a three phase short circuit without the FACTS controllers in the power network and then with the FACTS controllers. The dynamic simulation results yield information on (i) The impact of faults on the performance of induction generators/wind turbines. (ii) The change in controllable parameters of the FACTS controllers following the disturbance. (iii) Transient rating of the FACTS controllers for enhancement of rotor speed stability of induction generators and angle stability of synchronous generators.

A fast method for optimal reactive power flow solution

Abstract A fast successive linear programming (SLP) method for minimizing transmission losses and improving the voltage profile is proposed. The method uses the same compactly stored, factorized constant matrices in all the LP steps, both for power flow solution and for constructing the LP model. The inherent oscillatory convergence of SLP methods is overcome by proper selection of initial step sizes and their gradual reduction. Detailed studies on three systems, including a 109-bus system, reveal the fast and reliable convergence property of the method.

Short-term hydrothermal scheduling of power systems with a pumped hydro plant using the local variation approach

Abstract In light-load seasons, the operational planning problem of hydrothermal scheduling with a pumped hydro plant for the next days demand in a power system is concerned with the determination of generation schedules for the hydro, thermal and pumped hydro plants to meet the daily system demand so that the total fuel cost of the thermal plants over the day is minimized subject to the operating constraints associated with the thermal, hydro and pumped hydro plants as well as the security constraints. The security constraints include network security constraints and the generator outage induced security constraint. This paper presents a new problem formulation by including the generator outage induced security constraint on water storage level to operate the pumped hydro plant as a spinning reserve unit and a method for the selection of the initial trajectory for the pumped hydro plant. The effective algorithm used comprises a judicious combination of the participation factor method and the linear programming method. The algorithm is very effective in enforcing security constraints and gives an optimal generation/pumping schedule which can be readily implemented for the next day. A comparison of results obtained with and without the outage induced security constraint is made on a nine-bus system.

Towards on-line optimal reactive power scheduling using ANN memory model based method

In an attempt towards on-line implementation of optimal reactive power scheduling (ORPS), a fast method using a mix of ANN based bi-directional associative memory (BAM) model and corrective control algorithm (CCA) is proposed. Sufficient number of previously encountered system states and their optimal control settings obtained through a conventional method are stored in the BAMs weight matrix in the encoded form. Then, the BAM is put on-line. Given any arbitrary system state, the BAM recalls the closest previously encountered system state and its corresponding optimal settings. The optimal settings are corrected for any operational constraint violation using the CCA and are implemented. The method was tested on a modified IEEE 30 bus system. Twelve sets of system states and their optimal settings were stored. Given any arbitrary system state, the BAM successfully recalled the closest stored system state and its optimal settings which were corrected for violations using the CCA. The time taken was approximately one tenth of that of the conventional method demonstrating the usefulness of the proposed method.

A systematic method for eigenstructure assignment and application to response shaping

The simultaneous assignment of eigenvalue and eigenvector in a dynamic system using a constant-gain state-feedback controller is formulated as a static optimization problem. Response shaping by adequately damping the dominant modes or by eliminating the uncontrollable modes is possible in this formulation. Systematic solution through a standard LP routine makes the method attractive for practical implementation. The proposed eigenstructure-assignment algorithm is illustrated through two examples, one of which is the stabilization of a single machine connected to an infinite-bus power system.