E.E. El-Araby

A new formulation for FACTS allocation for security enhancement against voltage collapse

This paper proposes a new formulation for var planning problems, including the allocation of FACTS devices. A new feature of the formulation lies in the treatment of security issues. Different from existing formulations, we directly take account of the expected cost for voltage collapse and corrective controls, in which the control effects by the devices to be installed are evaluated together with the other controls such as load shedding in contingencies to compute an optimal var planning. The inclusion of load shedding into the formulation guarantees the feasibility of the problem. The optimal allocation by the proposed method implies that the investment is optimized, taking into account its effects on security in terms of the cost for power system operation under possible events occurring probabilistically. The problem is formulated as a mixed integer nonlinear programming problem of a large dimension. The Benders decomposition technique is tested where the original problem is decomposed into multiple subproblems. The numerical examinations are carried out using AEP-14 bus system to demonstrate the effectiveness of the proposed method.

A comprehensive approach for FACTS devices optimal allocation to mitigate voltage collapse

This paper presents a comprehensive approach for optimal allocation of FACTS devices against voltage collapse. The objective is to install a minimum number and sizes of FACTS so that the preventive and corrective control are made possible based on the available VAR sources and new FACTS devices for a set of contingencies. The corrective control is to stabilize the system for the contingencies that drive the system to unstable zone, where the fast devices are merely used for these situations. The preventive control is assumed based on the slow and fast devices for the cases with an inadequate security margin. The problem is formulated as mixed integer nonlinear programming problem, where a hybrid method based on genetic algorithm/successive linear programming (GA/SLP) is used to find the optimal solution.

Application of metaheuristic methods to reactive power planning: a comparative study for GA, PSO and EPSO

This paper proposes the application of metaheuristic methods to Reactive Power Planning (RPP). RPP involves optimal allocation of reactive sources to satisfy voltage constraints during normal and contingency states. The main objective of the proposed RPP is to make a trade-off between economy and security by determining the optimal combination of fast and slow controls (load shedding, new slow and fast VAR devices). The overall problem is formulated as a large scale mixed integer nonlinear programming problem. The proposed RPP problem is a combinatorial optimization problem, which cannot be solved easily by conventional optimization methods. Metaheuristic methods are reported to be efficient to solve combinatorial optimization problems. Among the well-known metaheuristic methods, this paper discovers the efficiency of Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Evolutionary PSO (EPSO) in solving the proposed RPP problem. The proposed approaches have been successfully tested on IEEE 14 bus system and a comparative study is illustrated.

Optimal procurement of VAR ancillary service in the electricity market considering voltage security

This paper presents a competitive bidding scheme for procuring VAR service in the electricity market with the consideration of voltage security in normal and post-contingency states. To determine the most beneficial VAR contracts that satisfy the required level of system security and ensure adequate payment for the VAR service, an optimization problem that simultaneously minimizes the total payment of the procured VAR and operating costs in all transition states while maintaining a set of physical constraints including voltage security margin is developed. The global solution of the proposed formulation is obtained using a hybrid genetic algorithms/successive linear programming (GA/SLP) method.

Voltage security constrained reactive power planning considering the costs and performance of VAR devices

This paper deals with optimal allocation of fast and slow VAR devices under different load levels. These devices are utilized to maintain system security in normal and contingency states, where corrective and preventive controls are implemented for the contingency cases. Load shedding and fast VAR devices are used in the corrective state in order to quickly restore system stability even though they are expensive, while cheap slow VAR devices can be used in the preventive state to obtain the desired security level. The main objective of this paper is to make a trade-off between economy and security by determining the optimal combination of fast and slow controls (load shedding, new slow and fast VAR devices). To meet the desired security limits, a variety of constraints have to be considered during the investigated transitions states. The proposed RPP problem is a combinatorial optimization problem, which cannot be solved easily by conventional optimization methods. Swarm optimization methods are reported to be efficient to solve combinatorial optimization problems. This paper discovers the efficiency of Particle Swarm Optimization (PSO) and Evolutionary PSO (EPSO) in solving the proposed RPP problem. The proposed approaches have been successfully tested on IEEE 14 bus system and a comparative study is illustrated.

Dynamic security constrained var planning for competitive environments

This paper presents a formulation for VAR planning method for guaranteeing secure power system operation in competitive environments. The formulation is useful for the evaluation of reactive power value, for effective investment of slow and fast VAR devices, for the examination of pricing and procurement of VARs through market. Since load shedding is the last resort for keeping security, the annual expectation of the load shedding cost is used as a security index to evaluate the overall benefits of VAR resources which respond in dynamic state transitions in contingencies. The proposed formulation takes into account the multiple benefits of reactive power in a single problem, which may be useful to evaluate the real value of the VARs. It is demonstrated that the maximum cost saving is achieved by a balanced installation of SC and SVC with keeping a specified security level. A VAR procurement method through market is also investigated using the formulation.

A PSO Approach for VAR Planning Considering the Slow and Fast VAR Devices Prices

This paper deals with optimal allocation of fast and slow VAR devices under different load levels. These devices are supposed to be utilized to maintain system security in normal and contingency states, where corrective and preventive controls are implemented for the contingency cases. Load shedding and fast VAR devices are used in the corrective state in order to quickly restore system stability even they are expensive, while cheap slow VAR devices can be used in the preventive state to obtain the desired security level. The main objective of this paper is to make a trade-off between economy and security by determining the optimal combination of fast and slow controls (load shedding, new slow and fast VAR devices). To meet desired security limits, huge number of constraints during the investigated transitions states, have to be considered. Therefore overall problem is formulated as a large scale mixed integer nonlinear programming problem, which cannot be solved by conventional optimization methods. Due to proved effectiveness of particle swarm optimization method (PSO) in performing difficult optimization tasks, this paper discovers the efficiency of PSO approach in solving our problem. The approach proposed has been successfully tested on IEEE 14 bus system.

Optimal VAR expansion considering capability curve of DFIG wind farm

This paper develops an optimal planning tool for VAR devices in the presence of a doubly fed induction generator (DFIG) based wind farm. The probabilistic wind power output associated with the capability curve of DFIG wind generator has been incorporated in the proposed formulation in order to examine its effect on the new VAR devices investment cost and compare the results with the current practice of the regulated power factor range of 0.95 leading and 0.95 lagging. The proposed method is stated as an optimization problem so that the objective function is to simultaneously minimize the sum of the annual investment cost of the new VAR devices as well as the annual expected energy loss cost. The objective function is achieved while simultaneously satisfying the investment constraints of the new VAR devices and several operating constraints including the effect of the wind park active power output and its associated VAR capability limits as well as the voltage security limits to enhance power system voltage stability.

Optimal scheduling of VAR devices considering wind power variability

This paper deals with the optimal short-term scheduling of VAR devices considering the volatile nature of wind power generation. These devices are utilized to maintain the voltage security in the forecasted wind power output case and its associated possible scenarios representing the wind power forecast errors. The random reactive power consumption associated with the wind power variability is included in the proposed formulation to demonstrate its impact on the power system voltage security. The problem is formulated as an optimization problem, where the objective function is to minimize the sum of the energy losses cost and operational cost of the reactive power devices. The consideration of the possible scenarios increases greatly the problem size. Therefore, Benders decomposition technique is employed to break down the intact problem into a master problem representing the hourly forecasted wind power and slave sub-problems relevant to possible volatility scenarios. The optimal VAR dispatch is obtained by iterating between the master problem and slave sub-problems. The proposed approach has been successfully tested on IEEE 14 bus system.

Optimal VAr expansion considering ATC using Strength Pareto Evolutionary Algorithm

This paper presents the application of Strength Pareto Evolutionary Algorithm (SPEA) to find the optimal solution of VAr expansion problem considering the enhancement of Available Transmission Capacity (ATC). The problem is formulated as a nonlinear constrained multi-objective optimization problem. The aim is to obtain an optimal allocation of VAr devices that is optimal in terms of minimizing the total incurred cost and maximizing the amount of ATC. To procure the exact cost of the VAr expansion problem, operation and control costs during all system transition states are calculated. Corrective/preventive controls are utilized to maintain the desired voltage security level. Installation of new VAr devices is proved to improve the amount of ATC, on the other hand it increases the investment cost which conflicts with the objective function of VAr expansion problem. Therefore, an evolutionary technique called SPEA is used to optimize the objective functions simultaneously. The proposed approach has been successfully tested on IEEE 14 bus system.