Line Flow Violations Research Articles

Contingency Constrained Optimal Power Flow by Hybrid Optimization Technique Using FACTS Device

Optimization algorithms are very important for the Optimal Power Flow (OPF). They could be divided into two classes: traditional local search methods and heuristic global ones. Interior point (IP) algorithm has been known as one of the most prominent and fastest method, but its local exploitation characteristic leads to the fact that it could be easily trapped by local optimum. However, heuristic methods such as Adaptive Particle Swarm Optimization (APSO) possess better convergence quality although their convergence speed is not good enough. This paper presents an Interior point method (IPM) and Adaptive particle swarm optimization (APSO) based hybrid method to solve the contingency constrained optimal power flow (OPF) in power systems incorporated with Flexible Ac Transmission Systems (FACTS). A versatile FACTS device TCPS (Thyristor controlled phase shifter) is considered. In the solution process APSO coupled with IPM to keep the power flows within their security limits. This Hybrid OPF algorithm with TCPS effectively relieves line flow violations under different single line contingencies. Severity Index is used as an objective function to be minimized to improve the security of the power system. The efficiency of proposed algorithm is illustrated by carrying simulation studies on IEEE 30 bus system .This analysis reveals that the proposed algorithm is quite simple and efficient for solving OPF problem.

Hybrid fuzzy-neural network-based composite contingency ranking employing fuzzy curves for feature selection

Maintaining power system security in the deregulated and unbundled electricity market is a challenging task for power system engineers. The idea is to short-list critical contingencies from a large list of contingencies and to rank the contingencies expected to drive the system towards instability. Timely corrective measures can then be planned to save the system from collapse and blackout. This paper presents a simple multi-output fuzzy-neural network for contingency ranking in a power system. A fuzzy composite performance index (FCPI), formulated by combining (i) voltage violations, (ii) line flow violations and (iii) voltage stability margin is being proposed in this paper for composite ranking of contingencies. The proposed approach is very effective in handling contingencies lying on the boundary between two severity classes. Feature selection using fuzzy curves has been employed to reduce the dimension of the network. The performance of the proposed method has been tested on a 69-bus practical Indian power system.

Solution to security constrained unit commitment problem using genetic algorithm

In this paper Optimal Power Flow (OPF) with line flow constraint is incorporated in solving the Unit Commitment (UC) problem using Genetic Algorithm (GA). In this proposed approach the problem is solved in two phases. In the first phase unit commitment is solved with prevailing constraints, without line flow constraint by genetic algorithm. In the second phase the violations in the lines are minimized for a committed schedule using GA based OPF. The resulting solution minimizes line flow violations in the critical lines under unit’s decommitted hours by adjusting the unit generations. In this paper, a 66-bus Indian utility system with 12 generating units and 93 transmission lines is considered to exhibit the effectiveness of the proposed approach.

A demand side approach for congestion management in competitive environment

AbstractThis paper proposes an approach for transmission congestion management (CM) in a deregulated power system. Transmission congestion mitigates network efficiency and results in increasing electricity price. Congestion can be effectively eliminated through several methods either by building a new transmission line or by increasing the capacity of the original line between congested zones. This paper evaluates the using of Demand Response (DR) programs in order to managing the congestion. For this purpose, a coordination process between GENCOs and the Independent System Operator (ISO) is considered. In the proposed approach, the coordination is modeled as a two‐stage process. At first, GENCOs apply price‐based unit commitment and submit their bids to the ISO for maximizing their profits. Then, the ISO clears the market using Day‐Ahead Demand Response Program (DADRP). Now, if any transmission violation exists, the ISO will run re‐dispatching of GENCO bids using Emergency Demand Response Program (EDRP) for minimizing the CM cost as well as omitting line flow violations. Numerical studies based on IEEE 57‐bus system are performed for the evaluation of the method. Copyright © 2009 John Wiley & Sons, Ltd.

Optimal supply curve bidding using Benders decomposition in competitive electricity markets

This paper describes a new approach for optimal supply curve bidding (OSCB) using Benders decomposition in competitive electricity markets. The inclusion of physical unit constraints and transmission security constraints will assure a subsequent feasible solution for the problem. We decompose the problem into a base-case OSCB (without unit and network constraints) and subproblems for checking the feasibility of unit and network constraints. For a given base-case OSCB schedule, line flow violations are minimized by adjusting units’ generation and phase shifters. In case transmission violations cannot be removed, additional linear constraints are introduced in the master problem in the form of price signals for rescheduling OSCB. An IEEE 24-bus system is used to demonstrate the effectiveness of the proposed approach.

A Novel Approach for Optimal Power Flow Using Bender’s Decomposition in a Deregulated Power Market

This paper describes a novel approach for the optimal power flow (OPF) problem in a deregulated power market using Bender's decomposition. Transmission constraints may represent intrautility flows in a generating company. The inclusion of transmission security (i.e., network) constraints will ensure a subsequent feasible solution for the OPF problem. We decompose the problem into a base-case OPF (without network constraints) and subproblems for checking the feasibility of the network constraints. For a given base-case OPF schedule applied to the subproblems, we minimize line-flow violations by adjusting phase shifters and generating units. In case the current mix of scheduled units cannot remove transmission violations, additional constraints will be introduced in the master problem for rescheduling OPF. Different systems are used to demonstrate the effectiveness of the proposed novel OPF approach.

New approach for dynamic optimal power flow using Benders decomposition in a deregulated power market

This paper proposes a novel Benders decomposition model of DOPF and applies Linear programming (simplex) method to solve it. Transmission constraints may represent intra-utility flows in a GENCO. The inclusion of transmission security (i.e. network) constraints will assure a subsequent feasible solution for the DOPF problem. We decompose the problem into a base-case DOPF (without network constraints) and subproblems for checking the feasibility of the network constraints. For a given base-case DOPF schedule applied to the subproblems, we minimize line flow violations by adjusting phase shifters and generating units. In case the current mix of scheduled units cannot remove transmission violations, additional constraints will be introduced in the master problem for rescheduling DOPF. A case study shows that the proposed model and algorithm is simple, fast and optimal.

Congestion management coordination in the deregulated power market

This paper describes a coordination process between GENCOs and the ISO for congestion management and reducing the risk of failure to supply loads. The algorithm underlining the coordination technique is the security-constrained price-based unit commitment (SPUC) which is implemented in two stages. At first, GENCOs apply priced-based unit commitment (without transmission security constraints), schedule their generating units and submit their bids to the ISO for maximizing their profits. The ISO obtains transmission information as well from TRANSCOs via OASIS. The ISO executes congestion management and contingency analysis for minimizing line flow violations and the risk supplying loads. If transmission flow violations persist after the adjustments are made, the solution would provide a signal to GENCOs for modifying their initial bids. Accordingly, additional constraints will be introduced in GENCOs for rescheduling generating units and submitting modified bids to the ISO. Two 36 unit GENCOs are used to demonstrate the efficiency of the proposed algorithm.