Mehdi Eghbal

FACTS Devices Allocation With Control Coordination Considering Congestion Relief and Voltage Stability

This paper presents an optimal allocation method for flexible ac transmission system (FACTS) devices for market-based power systems considering congestion relief and voltage stability. The purpose of the FACTS devices installation is to provide benefit for all entities accomplished by both minimizing annual device investment cost and maximizing annual benefit defined as difference between expected security cost (ESC) with and without FACTS devices installation. Different from previous approaches, the proposed method accurately evaluates the annual cost and benefits obtainable by FACTS devices installation by formulating a large-scale optimization problem that contains power flow analyses for a large number of system states representing annual power system operations. In addition, dynamic state transitions caused by specified contingencies are also simulated in the optimization problem to evaluate the effect of FACTS control actions as well as the other coordinated controls. The expected cost consists of operating cost under normal and contingency states along with their related probabilities to occur. Maximizing social welfare is the objective for normal state while minimizing compensations for generations re-scheduling and load shedding as well as maximizing social welfare are the objectives in case of contingency. Although installation cost of FACTS devices is required, they are useful as cost free means, which can reduce effectively the annual costs for generations re-scheduling and load shedding.

Present status and future trends in enabling demand response programs

This paper addresses implementation of Demand Response (DR) programs in competitive electricity markets. An overview of present status of the application of DR programs in major electricity markets is provided. In this paper, An objective-wised classification of DR measures is proposed which is rooted in practical DR experiences. Market opportunities and associated barriers are investigated. Further, enabling technologies for implementing DR programs are discussed. Finally, the role of smart grid in enabling DR is highlighted.

Transmission expansion planning by meta-heuristic techniques: A comparison of Shuffled Frog Leaping Algorithm, PSO and GA

This paper presents the application of a memtic meta-heuristic optimization technique known as Shuffled Frog Leaping Algorithm (SFLA) to the problem of transmission network expansion planning. The main objective of the proposed problem is to minimize total cost by finding the place, number and type of new transmission lines required to ensure that the power system meets the forecasted demand in the most economic and reliable way. The proposed static transmission expansion planning problem is formulated as a mixed integer programming optimization problem to minimize the total cost comprised of investment cost of building new lines, congestion costs and the cost of load curtailment due to contingencies. The proposed algorithm has been successfully applied to IEEE RTS 24-bus test system and the performance of the proposed algorithm has been compared with other heuristic optimization techniques such as particle swarm optimization (PSO) and Genetic Algorithm (GA). The comparison results testify to the feasibility and efficiency of the developed algorithm in solving the transmission expansion planning problem.

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.

Wind Power Offering Strategy in Day-Ahead Markets: Employing Demand Response in a Two-Stage Plan

This paper deals with wind power offering strategies in day-ahead markets. A new plan is proposed in which a wind power producer participates in the day-ahead market while employing demand response (DR) to smooth its power variations. In this context, a new DR scheme is presented through which the wind power producer is able to achieve DR by establishing various DR agreements with DR aggregators. The proposed offering plan involves two stages: the first stage clears on the day-ahead market. The wind power producer decides on day-ahead offers as well as DR agreements with the aggregator. The second stage takes place on the balancing market. In a successive approach, the wind power producer determines its energy trading for each period until the whole day is covered. Additionally, proper DR agreements for each period are confirmed here. The proposed plan is formulated in a stochastic programming approach, where its validity is assessed on a case of the Nordic market.

Hybrid multi-terminal LCC HVDC with a VSC Converter: A case study of Simplified South East Australian system

The hybrid multi-terminal HVDC (MTDC) with a combination of LCC (Line Commutated Converter) and VSC (Voltage Source Converter) eliminates all the disadvantages of these two HVDC technologies. Complex control schemes are required to operate this system under different operating conditions. This paper presents control schemes for a hybrid MTDC to guarantee a safe operation under different loading conditions and when faults occur. The developed control scheme is implemented on the Simplified South East Australian 14 generator system in DIgSILENT PowerFactory environment. The simulation results demonstrate the effectiveness of the proposed control scheme in reducing the grid active power losses and significantly improving the system transient stability.

Transient stability assessment as boundary value problem

This paper proposes a method for transient stability analysis for multimachine electric power systems. Different from existing methods, a minimization problem with boundary values is formulated for obtaining critical conditions for transient stability, where a new numerical integration method is developed by modifying the trapezoidal formula to solve effectively the boundary value problem. The proposed method is to compute directly a trajectory on the stability boundary, which is referred to as critical trajectory in this paper. The critical trajectory to be obtained is the trajectory that starts from a point on a fault-on trajectory and reaches a critical point such as an unstable equilibrium point (UEP), or more exactly, controlling UEP (CUEP). The solution of the minimization problem provides the critical trajectory and the exact critical clearing time (CCT) without major approximation.

A comparative study of voltage stability for long distance HVAC and HVDC interconnections

This paper presents a comparative study of voltage stability indices for three different long transmission technologies. High Voltage AC (HVAC), hybrid High Voltage DC (HVDC) and bipolar HVDC lines are compared in terms of voltage stability and point of collapse. Each scenario is analyzed with different lengths of transmission lines and in different contingency conditions. The impacts of HVDC control modes and parameters on interconnection voltage stability are also examined. Simulations are carried out on a simplified Australian power system with CIGRE HVDC models using the Power Factory software package.

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.

FACTS devices allocation for congestion management considering voltage stability by means of MOPSO

This paper proposes a method for solving congestion management problem by optimally allocating FACTS devices. The problem is approached by utilizing optimization method which optimizes generation and installation costs while satisfying voltage stability index. The main contribution of this paper is to provide pareto optimal solutions which describe previous objectives during congestion and after congestion removed. Moreover, the method is able to rank optimal location in relieving congestion, to describe feasibility of solutions and to show better solution in improving voltage stability. Therefore, it is valuable for decision maker in determining locations and sizes of devices which gaining the benefit. Due to the complexity of the problem, Multi Objective Particle Swarm Optimization (MOPSO) is utilized to optimize devices allocation as master sub-problem; Sequential Quadratic Programming (SQP) is used to solve the operation sub-problem, and Point of Collapse method is applied to calculate load margin during contingency. The effectiveness of this technique is demonstrated in modified IEEE 14 bus system.