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Accurate monthly electricity consumption forecasting (ECF) can help retailers enhance the profitability in deregulated electricity markets. Most current methods use monthly load data to perform monthly ECF, which usually produces large errors due to insufficient training samples. A few methods try to use fine-grained smart-meter data (e.g., hourly data) to increase training samples. However, such methods still exhibit low accuracy due to the increase in forecasting steps. © 1975-2012 IEEE  

This Paper presents a model for optimal locating and sizing of Distributed Generation (DG) for congestion management in deregulated electricity market. For reducing the solution space a priority list of candidate buses is formed and then optimal placement and sizing of DG in potential buses is discussed. In order to incorporate stochastic nature of power system in this study, Monte-Carlo method is used to simulate the effect of uncertainty of loads and system on the optimal location and size of the DGs in the network. The proposed method is applied to IEEE Reliability Test System (RTS). The impacts of load uncertainty on optimum DG size and location are studied  

Congestion management is one of the most important issues for secure and reliable system operations in deregulated electricity market. This paper presents a cost/worth analysis approach for optimal location and sizing of Distributed Resources (DRs) to mitigate congestion and increase security of the system. In order to reduce the solution space a priority of candidate buses is formed, then optimal location and sizing problem is discussed. To increase the accuracy of results, load duration curve is constituted and based on this curve different load levels are incorporated into this study. Proposed method considers economical factors such as congestion rent, deferred upgrading investment and... 

This paper propose a particle swarm optimization based algorithm for locating Unified power flow controller (UPFC), as well as set its parameters, with static point of view in deregulated electricity markets in order to reduce generation cost, voltage violation and manage congestion. The modeling of UPFC has been adapted based on power injection method. In order to verify and validate the effectiveness of the proposed method, it was applied to 24-bus Reliability Test System (RTS) and the results have been discussed  

This paper proposes a particle swarm optimization based algorithm for locating series FACTS devices in deregulated electricity markets in order to reduce and manage congestion. Line outage sensitivity factors are used to reduce the solution space and to pinpoint the lines which are more suitable for FACTS device placement. Total congestion cost and total generation cost are the two objective functions that are employed in the optimization process. In order to verify and validate the effectiveness of the proposed method, it was applied to IEEE 14-bus and IEEE 57-bus test systems. The results obtained by the proposed method were compared with those of congestion rent contribution method  

To make the energy market reliable and transactions deliverable, transmission owners must provide required ancillary services that are critical to ensure transmission open access, and to maintain an acceptable level of power system security. Spinning reserve is one of the most important ancillary services required to maintain system reliability in case of occurring a contingency. By definition, spinning reserve is the unloaded section of synchronized generation that is able to respond immediately to serve load. Studies indicate that spinning reserve requirements have significant impacts on the energy market. A new spinning reserve market structure is proposed in this paper to best utilize...