Due to the stochastic nature of wind energy, allocating an appropriate investment incentive for wind generation technology (WGT) is a complicated issue. We propose an improvement on the traditional incentive, known as capacity payment mechanism (CPM), to reward the wind generators based on their performance exogenously affected by the wind energy potential of the location where the turbines are installed, and therefore, lead the investments towards locations with more generation potential. In CPM, a part of investment cost of each generator is recovered through fixed payments. However, in our proposal, wind generators are rewarded according to dynamic forecasts of the wind energy potential of the wind farm where they are located. We use an auto-regressive moving average (ARMA) model to forecast the wind speed fluctuations in long-term while capturing the auto-correlation of wind velocity variation in consecutive time intervals. Using the system dynamics (SD) modelling approach a competitive electricity market is designed to examine the efficiency of the proposed incentive. Performing a simulation analysis, we conclude that while a fixed CPM for wind generation can decrease the loss of load durations and average prices in long-term, the proposed improvement can provide quite similar results more efficiently.

In this paper a new concept has been proposed to consider “Energy Efficiency” as a new commodity. The new commodity is based on DSM (Demand Side Management) and especially the strategic conservation techniques in the Restructured environment.  In the proposed method the ability to improve efficiency is traded as a new commodity by some new players.The effect of new commodity trading is analyzed on the long-term market power reduction in parallel to available long-term solutions that mostly rely on generation solution.The numerical study according to real world data shows the potential and effectiveness of the proposed method.

Following the rise of the fuels that power plants consume in the deregulated market, an increase in the electricity prices would be expected. This article tries to study the effects of power plants’ fuel prices adjustment on the amount of increase in electricity prices in the market. The components of the deregulated power market were modeled in the systems dynamics method with the aim of finding a reasonable answer to the question of this research. The model encompasses three parts, namely demand, price and production run through powersim software. The change in the prices of fuels delivered to power plants is considered as the policy variable of the model. The results of running the model illustrated that it is anticipated that the price of electricity will reach 409 rials in a kilowatt per hour by the end of the period providing that the power plants’ fuel prices are not adjusted. If the prices of fuels delivered to power plants are adjusted, the power market prices will reach 556 and 585 rials in a kilowatt per hour by the end of the period, assuming that the price growth may be by 5 or 8 percent, respectively. In the final part of the paper, the effect of economic growth increase as well as that of value added taxation on power market is analyzed in the framework of a suggestion model. Therefore, in such a case, assuming a 6 and 8 percent price growth, the prices of power market will reach 611 and 641 rials in a kilowatt per hour by the end of the period.

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.

Transmission open access is one of the essential issues in restructuring of electric industry. In this way, pricing of transmission system should be performed in a fair and reasonable procedure. This paper describes the principle and implementation of a reliability based methodology for allocating the cost of transmission network. A probabilistic index is defined which measures the relative importance or reliability benefit of the unused (additional) capacity of each particular line for each transaction. The index is calculated based on contingency conditions analysis corresponding to line outages. Transmission embedded costs are allocated based on the contribution of each transaction to base capacity in normal condition and also to the additional capacity in contingency conditions using the defined index. Furthermore, the split between the capacity use and reliability margin costs is performed on a reasonable decision. As a result, the proposed methodology provides an equitable means of allocating the cost of transmission network among its users. The methodology is illustrated in a small power system and its conceptual and computational feasibility are shown.

In this paper a new steady state modeling of unified power flow controller (UPFC) is proposed. Using this model, factors that affect the objective function of electricity market as a result of UPFC installation in power grid has been decomposed into four components, including line series impedance increase, shunt reactive power compensation, in-phase component of series voltage and quadrature component of series voltage. An UPFC has been placed in different points of a test system and impact of each component on objective function of electricity market has been measured by simulation and compared with results from analytical method. Both active and reactive locational marginal prices are calculated and their relation with settings of UPFC series part has been studied.

Privatization of power sector and establishment of competition in power supplying process, raised unprecedented challenges in power system operation and planning fields, such as preventive maintenance scheduling which was formerly, in traditional environment, managed centrally by dispatching center. Dispatching center role having been changed in Restructured power systems, power producing companies play a more important role in PM scheduling process. The conflict between dispatching center being concerned about power system reliability and stability, and power generating companies profit maximization based behavior which cannot be defined properly thorough traditional optimization theory, may be modeled satisfactory thorough Game theory approaches. In this paper, after modeling and solving PM scheduling process thorough game theory, discusses about resultant equilibrium states and predicts different power generation technologies behavior.