Showing 5 results for Congestion Management
M. Esmaili, H. A Shayanfar, N. Amjady,
Volume 6, Issue 1 (3-2010)
Abstract
Congestion management in electricity markets is traditionally done using deterministic values of power system parameters considering a fixed network configuration. In this paper, a stochastic programming framework is proposed for congestion management considering the power system uncertainties. The uncertainty sources that are modeled in the proposed stochastic framework consist of contingencies of generating units and branches as well as load forecast errors. The Forced Outage Rate of equipment and the normal distribution function to model load forecast errors are employed in the stochastic programming. Using the roulette wheel mechanism and Monte-Carlo analysis, possible scenarios of power system operating states are generated and a probability is assigned to each scenario. Scenario reduction is adopted as a tradeoff between computation time and solution accuracy. After scenario reduction, stochastic congestion management solution is extracted by aggregation of solutions obtained from feasible scenarios. Congestion management using the proposed stochastic framework provides a more realistic solution compared with the deterministic solution by a reasonable uncertainty cost. Results of testing the proposed stochastic congestion management on the 24-bus reliability test system indicate the efficiency of the proposed framework.
M. Heydaripour, A. Akbari Foroud,
Volume 8, Issue 4 (12-2012)
Abstract
Congestion in the transmission lines is one of the technical problems that appear particularly in the deregulated environment. The voltage stability issue gets more important because of heavy loading in this environment. The main factor causing instability is the inability of the power system to meet the demand for reactive power. This paper presents a new approach for alleviation congestion relieving cost by feeding required reactive power of system in addition to re-dispatching active power of generators and load shedding. Furthermore with considering different static load models in congestion management problem with both thermal and voltage instability criteria, tries to the evaluated congestion management cost become more real, accurate and acceptable. The voltage stability is a dynamic phenomenon but often static tools are used for investigating the stability conditions, so this work offers new method that considers two snapshots after contingency to consider voltage stability phenomena more accurate. This algorithm uses different preventive and corrective actions to improve unsuitable voltage stability margin after contingency. The proposed method is tested on IEEE 24-bus Reliability test system, the simulation results shows the effectiveness of the method.
A. R. Moradi, Y. Alinejad-Beromi, K. Kiani,
Volume 13, Issue 1 (3-2017)
Abstract
Congestion and overloading for lines are the main problems in the exploitation of power grids. The consequences of these problems in deregulated systems can be mentioned as sudden jumps in prices in some parts of the power system, lead to an increase in market power and reduction of competition in it. FACTS devices are efficient, powerful and economical tools in controlling power flows through transmission lines that play a fundamental role in congestion management. However, after removing congestion, power systems due to targeting security restrictions may be managed with a lower voltage or transient stability rather than before removing. Thus, power system stability should be considered within the construction of congestion management. In this paper, a multi-objective structure is presented for congestion management that simultaneously optimizes goals such as total operating cost, voltage and transient security. In order to achieve the desired goals, locating and sizing of series FACTS devices are done with using components of nodal prices and the newly developed grey wolf optimizer (GWO) algorithm, respectively. In order to evaluate reliability of mentioned approaches, a simulation is done on the 39-bus New England network.
R. Gandotra, K. Pal,
Volume 18, Issue 3 (9-2022)
Abstract
The growing demand increases the maximum utilization of transmission and distribution lines which causes overloading, high losses, instability, contingency, and congestion. To enhance the performance of AC transmission and distribution systems FACTS devices are used. These devices assist in solving different issues of transmission lines such as instability, congestion, power flow, and power losses. Advancement in developed technology leads to the development of special application-based FACTS controllers. The main issues are concerned while placing the FACTS controller in the transmission and distribution lines to maximize the flow of power. Various methods like analytic method, arithmetic programming approaches, meta-heuristic optimization approaches, and hybrid approaches are being employed for the optimal location of FACTS controllers. This paper presents a review of various types of FACTS controllers available with both analytical and meta-heuristic optimization methods for the optimal placement of FACTS controllers. This paper also presents a review of various applications of FACTS devices such as stability improvement, power quality, and congestion management which are the main issues in smart power systems. Today’s smart power systems comprise the smart grids with smart meters and ensure continuous high quality of power to the consumers.
Sajal Debbarma, Dipu Sarkar,
Volume 20, Issue 0 (12-2024)
Abstract
Transmission line congestion is more severe and persistent in deregulated power systems than it is in traditionally controlled power systems. In a deregulated power market (DPM) scenario, transmission line congestion is one of the most critical problems. To guarantee the electricity system framework runs consistently and securely, the independent system operator (ISO) controls congestion. Congestion management (CM), which takes into account the inherent uncertainties of the restructured power system, is essential to the functioning and security of DPM. This article demonstrates how to control congestion with generation rescheduling. The system is designed in such a way that it helps the traders to compete and trade using the bid prices. Network security is maintained by keeping all constraints within the allowed limits via the Newton-Raphson load flow. An innovative Cheetah Optimizer is employed to handle the congestion management challenge. The weighted sum approach is used instead of multi-objective optimization to simplify the problem as a single-objective optimization and solve the issue for multiple instances of congestion and tested in an IEEE 30 bus system. The MATLAB software serves as a tool for modelling the full process, and the results acquired with Cheetah optimiser give better results than the conventional optimisation technique.
