Congestion management using grey wolf optimization in a deregulated power market

Transmission congestion issues became more severe and difficult to control as the power sector became more deregulated. The grey wolf optimization algorithm is proposed to relieve congestion by rescheduling generation effectively, resulting in the least congestion cost. The selection of participating generators is based on sensitivity, and the proposed technique is used to determine the best-rescheduled output active power generation to minimize line overload. The IEEE-30 bus system is used to test the proposed optimization technique. It has been demonstrated that when compared to other algorithms like the real coded genetic algorithm, particle swarm optimization, and differential evolution algorithm, the proposed approach produces excellent results in terms of congestion cost.

Optimal Fitting Method of Nonlinear Simultaneous Equations Considering Structural Tensor Image Modeling

For the purpose of resolving the phenomenon of network congestion in the process of many-to-one communication in multimedia networks at present, the optimal fitting method of nonlinear simultaneous equations (OFMNSEs) is applied to the multimedia transmission congestion control system in this paper. The rate control and resource scheduling are effectively combined, and a clustering network structure is used to activate the congestion control method in turn based on the cluster header and intracluster-related indexes. Finally, it can be known through the analysis of the simulation results that the OFMNSE algorithm put forward in this paper can improve the congestion issue of the multimedia network transmission process and reduce the packet loss rate of data during the transmission effectively under the condition of different relative cache sizes compared with the conventional algorithm.

A survey on recent advances in transmission congestion management

For the last few decades, the power sector has been restructuring throughout the world, and because of this, congestion is bound to take place in the network. Congestion can lead to market failure, violate transmission capability limits and high electricity prices, and end up threatening the power systems’ reliability and security. Increased congestion may also lead to unexpected price differences in power markets leading to market power. In a deregulated power market (DPM), the independent system operator (ISO)’s fundamental challenge is to preserve the power market’s reliability and safety by improving market efficiency when the network is congested. Therefore, congestion management (CM) is essential in DPM and is the key to the power system. This paper carries out a congestion management methods survey to bring together all recent publications in the DPM. It aims to help readers summarize progressive CM methods, along with traditional CM methods that have been discussed so far. In this paper, we have carried out a comparative survey of the various well-known CM methods.

Power System Zone Partitioning Based on Transmission Congestion Identification Using an Improved Spectral Clustering Algorithm

The ever-expanding power system is developed into an interconnected pattern of power grids. Zone partitioning is an essential technique for the operation and management of such an interconnected power system. Owing to the transmission capacity limitation, transmission congestion may occur with a regional influence on power system. If transmission congestion is considered when the system is decomposed into several regions, the power consumption structure can be optimized and power system planning can be more reasonable. At the same time, power resources can be properly allocated and system safety can be improved. In this paper, we propose a power system zone partitioning method where the potential congested branches are identified and the spectral clustering algorithm is improved. We transform the zone partitioning problem into a graph segmentation problem by constructing an undirected weighted graph of power system where the similarities between buses are measured by the power transfer distribution factor (PTDF) corresponding to the potential congested branches. Zone partitioning results show that the locational marginal price (LMP) in the same zone is similar, which can represent regional price signals and provide regional auxiliary decisions.