فهرست مطالب محمود فتوحی فیروزآباد

Due to the complexity of distribution networks, preventive maintenance is very important. Incentive regulation is also one of the factors influencing the performance of distribution companies, which in turn complicates maintenance planning. This paper addresses the issue of preventive maintenance planning to enhance reliability in the presence of reward and penalty as a motivational factor. Therefore, the profit function of the distribution company, which includes the cost of repairs and reward-penalty, is optimized. In the incentive model for measuring the performance, reliability indices are compared by feeders, and in contrast, the repair program is obtained for each feeder separately. Due to the different causes of feeder failure such as their structural properties and weather conditions, increasing the accuracy of performance comparison from companies to feeders, in addition to penalties and rewards assigning leads to maximise the impact of maintenance at the level of their reliability and is accompanied by cost savings. For this purpose, the information of a real network including 194 feeders is considered as primary data. After categorizing the feeders and calculating penalties and rewards, the profit from the provision of services are optimized by BPSO method. As a result, the preventive maintenance program is obtained separately for feeders for three general categories of frequent failures, which includes substation failure, line failure and tree branch collision in a period of 5 years. The optimization results show that the proposed method, while maximizing the profits of distribution companies, also improves their performance in terms of reliability.

The present context of the electric industry, characterized by competitive markets, privatization, and regulatory of technical requirements forces the power utilities to optimize their asset management practices and develop the requisite decision plans techno-economically. Practically approaching, this paper devises a new support tool based on a multiattribute decision making (MADM) framework in combination with analytical hierarchical process (AHP) to determine the most critical components of power transmission systems. Measure of system-wide reliability performance, outage cost, Locational marginal prices demonstrative of market fairness, and network losses are among the attributes considered in this paper for component criticality assessment. With the frequent existence of qualitative and quantitative attributes, the proposed approach can effectively help to deal with the existent uncertainty and conventional judgment vagueness. As verified in a case study on the IEEE Reliability Test System (IEEE-RTS), the proposed framework introduces its applicability and efficiency for the practical asset management optimizations in electric utilities.

Energy costs comprise considerable amount of operation costs in water distribution networks. Optimal management of energy costs to provide required water for consumers with desired quality is of high importance. To achieve this, optimization is defined as a powerful tool. In this paper, by focusing on operation phase, multi-objective optimization of water supply network considering hydraulic, quality and integrated reliability measures is performed. In each of these cases, the first goal is to minimize energy costs and maximization of each reliability measure is considered as the second objective. Therefore, it is necessary to set the performance schedule of the pumps over a period of time, one day, such a way that pumping schedual changes based on consumption variation during the day. In addition, it is required to maximize the hydraulic, quality and integrated reliability measures in the network. In this paper, in order to adapt more pump operating modes of pump station, both constant and variable speed pumps are used. In order to optimize performance of water distribution network, due to the high efficiency and simplicity of ant colony algorithm, the NA-ACO-CD (Non-Dominated Archiving Ant Colony Optimization with Crowd Distance) algorithm has been coded in Visual Studio C. The efficiency of NA-ACO-CD algorithm is tested with mathematical functions and proved to be applicable on water distribution networks. The proposed method is evaluated on Anytown water distribution network and required pareto curved are produced. It is concluded that the methodology cannot be attained to a combination of pump speeds such that all three pump, hydraulic and quality reliabilities will be maximized simultaneously.

Today, with development of different industries and tendency of human beings for urbanity, most of the modern cities have become crowded. This has led to many undesirable problems such as noise pollution which can affect the health of mankind. It has been proved that many physical and mental illnesses are possible side effects of the noise pollution. Transportation sector has been introduced as a main resource of noise pollution. In recent years, different technologies of electric cars and motorcycles have been considered as a new era in the transportation industry. Since, the noise pollution generated by these new technologies is negligible, it can be expected that by presence of these new technologies, the share of transportation sector in noise pollution of the cities would decrease. In this paper, we tried to investigate this important feature of electric transportation in Tehran. In this regard, three possible penetration scenarios including, low, average and high scenarios are defined for presence of electric cars and motorcycles in transportation sector of Tehran. It has been assessed how the noise pollution of this city would change considering these penetration scenarios. It has been shown that a remarkable improvement in noise pollution can be expected due to usage of these technologies.

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.

In recent two decades, restructuring and unbundling of vertically-integrated monopolies into separate generation, transmission and distribution entities were the most important issues of the power system, due to the excessive growth in electrical energy consumption and limited governmental funds. Aging equipment of power system and appearance of modern technologies in recent years have made new issues for system operators. As a response to these issues, smart grid is emerged to make two-way communication and even electricity flow between end-users and utilities possible. Reliability improvement of distribution networks, exploiting the sustainable energy resources, and energy efficiency are the three fundamental consequences of smart grid realization. In this paper, smart grid is treated as a new paradigm in electricity industry. Various technical and technological concepts, i.e. distributed generation (DG), plug-in hybrid electric vehicle (PHEV), distributed energy resource (DERs) are probed and their impacts on the planning and operation of the modern electricity industry is investigated in this paper. Finally, cyber security challenges are investigated in the smart grid area. Finally, cyber security challenges are investigated in the smart grid area.

Nowadays, development of industries and increment of urbanization which have led to population augmentation, air pollution and become a big problem. Air pollution has several negative impacts on human mind and body health and city environment. In recent years a great success in transportation technologies has been perceived. One of these technologies is utilization of electric batteries in existing internal combustion motors vehicles. Since electrical energy is a clean one, it is expected that air pollution decrease considerably by penetration of these vehicles in transportation system. In this paper, mentioned issue is scrutinized for city of Tehran. Three different scenarios with different level of penetration are considered. The results show that electric motorcycles can be used as a quick solution and electric cars can be used as an effective long-term solution for decreasing air pollution.

A method for concurrent clearing of energy and reserve market is presented in this paper. The proposed method considers two important objectives in an optimization problem; the first one is including the stochastic nature of power generation variations by applying a probabilistic clearing model and Monte-Carlo simulation; the second one is assignment of energy and reserve capacities to generating units with consideration of economic and reliability criterions. In the objective function of the considered problem، in addition to the offered costs for energy and reserve، the costs of non-delivered energy and non-delivered reserve are included. Solution results of the optimization problem can be applied as a guidance to provide incentives for generating companies to improve their reliability and have higher share in the market. The proposed method is validated through its application to a test system

Direct load control (DLC), which is an aspect of demand response, is an on-off pattern or a change in set points involved with special devices of customers offered by the system operators in a manner to optimize a number of objectives. In this paper, DLC is in hands of retailers acting as third party firms between the Disco and the customers attaining profit by purchasing power from the Disco and selling it to the customers. The retailers are also able to increase their profit controlling the customers’ load. Assuming the smart grid infrastructure it is possible for the customers to announce their contribution levels and incentive bids daily to the retailers by means of interfaces installed in each customer home. Considering the fact that the retailers are responsible to give incentives to the customers, optimizing the number of customers accepted and curtailed in each contribution level and bid is done by a mixed integer linear programming (MILP). The results show that the method is able to maximize the retailer’s profit and fairly transfer the aggregated load level peak while warranting customers’ conveniences considering some constraints.

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.

In a deregulated electric power system in which a competitive electricity market can influence system reliability, system analysts are rapidly recognizing that they cannot ignore market risks. This paper first proposes an analytical probabilistic model for the reliable evaluation of competitive electricity markets and then develops a methodology for incorporating the market reliability problem into composite power system reliability studies. The market reliability is evaluated using the Markov state space diagram. Since the market is a continuously operated system, the concept of absorbing states is applied to it in order to evaluate reliability. The market states are identified using market performance indices and the transition rates are calculated using historical data. The key point in the proposed method is the concept that the reliability level of a restructured electric power system can be calculated using the availability of the composite power system and the reliability of the electricity market. To illustrate an interesting feature of the proposed methodology, two case studies are carried out over a test system.

A new approach for optimal reserve determination and cost allocation in the pool-based and disaggregated market model using a well-being framework is presented in this paper. In the proposed method, customers have the chance to specify the risk level which they are willing to accept. Firstly, the energy market is cleared, and afterwards the reserve market is cleared such that the required risk levels of different customers are satisfied. Then, according to the required risk levels and the provided reserve, the cost of reserve is allocated between the different customers with different reliability requirements. For fairly managing the shortage between different customers in the real time operation by the system operator, the Interruption Factor is introduced for the first time in this paper. Although from the economic point of view reliability is a public good, using the concept of the interruption factor, different customers with different reliability requirements can be differentiated. Finally, the proposed method is applied to the IEEE-RTS to examine the applicability and effectiveness of the proposed method.

Wind generation is one of the most useful sources of renewable energy for the production of electrical energy. The technical characteristics of wind generation make existing conventional generation models not directly applicable. This paper presents an analytical method for the reliability assessment of the flat-rated wind turbine generation systems. An example of flat rating is that of the MOD-2, a second-generation class of wind turbines. The power-velocity characteristic of the flat-rated wind turbines is employed in this paper to model the operating behavior of the installed wind turbine generators. For wind-power potential estimation, the Weibull distribution model is used. The performance of the proposed model is demonstrated with case studies.