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Deregulation policy has caused some changes in the concepts of power systems reliability assessment and enhancement. In this paper, generation reliability is considered, and a method for its assessment using intelligent systems is proposed. Also, because of power market and generators’ forced outages stochastic behavior, Monte Carlo simulation is used for reliability evaluation. Generation reliability, merely focuses on interaction between generation complex and load. Therefore, in this research, based on market type and its concentration, reserve margin, and various future times, a Neuro-Fuzzy system is proposed for evaluation of generation reliability which is valid and usable for all kinds of power pool markets. Finally, the proposed method is assessed on IEEE-Reliability Test System; and generation reliability indices of various markets are evaluated with different reserve margins and different load levels.

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In this paper, first, a new criterion, titled “surplus percent of the customers” is defined for static transmission expansion planning in restructured power systems. Then by a simple example, the new criterion is compared with some already presented market-based criteria and it is shown that the new criterion can realistically evaluate the transmission network expansion from the market view. In this paper the bid of market participants (producers and consumers) to sell and buy power are considered as random variables with known probability density functions. Then the expectation of the surplus percent is introduced as an index for measuring the competitiveness of each transmission expansion plan. Then a least-investment cost expansion plan that increases the surplus percent to its ideal or near ideal value is searched. In this paper a fast method is also presented to calculate the expectation of the surplus percent using Monte-Carlo simulation with a predefined approximation. The results of applying the proposed method are illustrated for an example 8-bus power system.

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Tanks in water distribution networks are used to store water for emergency conditions, fire flow demand and demand oscillations controll. Construction of tanks spends a lot of money and therefore using whole volume of tanks is essential while operation. Otherwise, if tank volume will be more or less than what is required during operation, tank reliability is reduced. Accordingly, in this paper, a new relationship for tank reliability according to water level variation in tanks is defined. Therefore, maximum water level in tanks is defined as the decision variable. The definition of tank reliability is as follows. At first, the values of maximum level for each tank is computed such a way that optimal use is provided from balancing volume of tanks. In fact, for these maximum level values, maximum reliability is acheived for each tank. Now if during optimization process, a value lower than these computed maximum level is selected for decision variables, tank reliability is reduced. To compute the value of tank reliability, the values of tank water level for the selected decision variables is devided by the values of tank water level for maximum tank reliability. Also, because water level variation can effect on pressure and water age in demand nodes, this effect is investigated by considering hydraulic and quality reliability. In fact, variation of water level in tanks changes node demand pressures and in result actual node demands. Also, variation of water level or on the other hand variation of storage volume affects on water age in demand nodes. Besides, in order to investigate the simultaneous effect of water level variation on hydraulic and quality reliability, a relationship is also defined for integrated reliability. Definition of integrated reliability is to investigate whether there is optimum maximum tank level values that both hydraulic and quality reliability is improved simultaneusly while tank construction costs is minimum. Optimal management of tanks in water distribution networks to provide required water of consumers with desired quality is of high importance. To acheive this, optimization is defined as a powerful tool. In this paper, by focusing on operation phase, multiobjective optimization of water distribution performance is performed in which tank costs is considered as the first objective and tank reliability, node hydraulic reliability, node water age reliability and integrated reliability is considered as the second objective. Ant colony algorithm is codified in Microsoft Visual C++ for optimization due to its simplicity and high performance. The validity of the edited algorithm is tested on mathematical functions and proved to be applicable on water distribution networks. The created trade-off curve from multiobjective optimization helps the decision makers to select the top choice based on the importance of their own criterion whether it is hydraulic or quality.