CONGESTION Risk MANAGEMENT is one of the most important subjects of Transmission MANAGEMENT in deregulated power system and world electricity market, especially markets of zonal or local pricing in which Firm Transmission Rights (in other words Financial Transmission Rights) are the main elements. In this study, considering subjects of Financial Rights of Transmission CONGESTION, methods of OPTIMUM proposal of different Rights by participants of transmission rights second auction of electricity Market in short period (weekly) for CONGESTION Risk MANAGEMENT will analyzed. At the end, a proposed method in a typical network is tested and the numerical right values shown.

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.

In the deregulated power systems, transmission CONGESTION is one of the significant and main problems of the electrical networks which can cause incremental cost in the energy. This problem has resulted to new challenging issues in different parts of power systems which there was not in the traditional systems or at least had very little importance. Transmission CONGESTION happens when the maximum available power transmission capacity is lower than the consumption side. As CONGESTION happens, the system power losses are increased which can cause problem in the voltage constraints. Therefore, this paper proposes a new method to handle the optimal MANAGEMENT and control of CONGESTION problem by the use of distributed generations (DGs). In this regard, the optimal size and location of DGs are investigated using the powerful bacteria foraging algorithm (BFA) as a new intelligence-based optimization technique to solve the CONGESTION problem on the three IEEE 14-bus, 30-bus and 57-bus test systems. The simulation results show the high speed, fast convergence and accurate performance of the proposed algorithm to solve the CONGESTION problem in the system.

In this paper a new strategy for CONGESTION MANAGEMENT is presented. Generally, in CONGESTION MANAGEMENT programs all considered contingencies are deterministic or stochastic. Therefore, CONGESTION MANAGEMENT cost is increased. In the proposed algorithm, CONGESTION MANAGEMENT program is divided to two parts, Primary and Secondary CONGESTION MANAGEMENT. Also, contingencies are divided in two groups. In the first group, the contingencies that should be managed by preventive actions are considered and the others are taken into account in the second group. The first group of contingencies is in primary CONGESTION MANAGEMENT. The secondary CONGESTION MANAGEMENT program starts from the nearest time to market run time. So, the secondary CONGESTION MANAGEMENT uses corrective actions for managing secondary group contingencies. Also, the secondary CONGESTION MANAGEMENT is capable of covering most uncertainties, especially load variations. The proposed method reduces CONGESTION MANAGEMENT cost.

One of the problems with today's TCP/IP networks is their transmission system. If the bandwidth of a network is full, human and physical factors must be used for a new transmission system with a higher capacity to provide its bandwidth, which is very time consuming and costly. In this article, we proposed a method that in addition to the optimal use of available bandwidth, if the network capacity is full, it will be automatically transferred to a higher bandwidth network. For this purpose first, by designing a fuzzy PID controller for the existing network, it is tried to CONGESTION control them and make use of it. It can be seen that the proposed controller performs much better in terms of an output response, following the queue length, stability and uncertainly, compared to the classical controller. If the input data to the network is increased, more packets are lost and this reduces the quality of the network. To solve this problem by using bandwidth MANAGEMENT, by considering the threshold for packets loss in each network, if exceeding this limit, the existing network is switched to a network with a higher capacity and the problem of bandwidth and network quality is solved and causes subscriber satisfaction.

In trading electrical energy in deregulated power systems, violation of operation constraints such as transmission lines flow limits is possible. These conditions have been called “CONGESTION”. One of the most important responsibility of Independent System Operator (ISO) is CONGESTION MANAGEMENT in a manner that all the system equipments be operated in their nominal ranges. In this paper, using topological generation distribution factor, participation of each generator in power flow in each line is calculated. Then, by means of decomposition of nodal price and mentioned factor, the effect of generation in each bus on the locational marginal price in all buses of the system are calculated. And the CONGESTION price is calculated based on re-dispatch in constant demand. In this paper a new method is introduced to dedicate CONGESTION price to each generatorand by this method a fair CONGESTION cost allocation is implemented. The method has been tested on IEEE 24-bus test system and the results have been demonstrated.

CONGESTION MANAGEMENT is deal with in this paper. The algorithm proposed is based on active and reactive power dispatches of critical nodes, determined from a detailed sensitivity analysis. The electricity market considered is a hybrid model, in which firm transmission rights may also be observed. The proposed algorithm is assessed and its capabilities evaluated for a typical test system.