مجله کیفیت و بهره وری صنعت برق ایران
سال دهم شماره 3 (پیاپی 24، پاییز 1400)

Charging stations are one of the most important pieces of equipment for electric vehicles (EV). One of the most important challenges of charging stations is their optimal location, which practically puts the operation of the system components in the maximum area. Distribution networks are the final link in the electricity supply chain for consumers. Therefore, the economic and technical efficiency of these networks guarantees a stable and secure future in the electricity industry. In this regard, it is very important to study the role of EVstations. This paper investigates, the optimal location of charging and discharging stations and the optimal operation planning of Evs in a distribution network. The effective factors in choosing the location and the optimal charging and discharging rate in the stations are a combination of technical and economic issues. Regarding technical issues, the minimization of losses, the minimization of voltage drop in feeders and the uniformity of the network load curve were considered. In the economic field, the stations were located and the charging and discharging rates were determined in such a way that the charge and discharge costs in the stations and the total cost paid for the purchase of power were minimized as much as possible. In order To manage the load on the consumer side and to unify the load curve, the price-based demand response program was considered and implemented in the simulations.To find the optimal working point, genetic metaheuristic algorithms, genetic combination-particle swarm and genetic combination-colonial competition were used. All simulations were performed in MATLAB software To evaluate the proposed methods, validation was performed in each part on the IEEE standard testing system with a bus number of 69.

A compressor is a machine that is used to increase the pressure of various gases. How to increase the pressure depends on the compressor type. One of the functional problems of centrifugal compressors is the phenomenon of the surge, which is still an obscure and unknown phenomenon that can induce mechanical or thermal stress in the system and cause a lot of damage. This type of aerodynamic instability reduces the compression ratio at both ends of the compressor, thereby reducing the overall efficiency of the system. In general, when a surge occurs, it causes process turbulence, the degradation of overall compressor efficiency, the reduction of compressor life due to mechanical damage to seals, bearings, rotor, and impellers, and the loss of internal freedoms and sensitive mechanical parts of the system. Therefore, surge control is one of the challenges of compressor control and expands the operating range of compressor operation. A map compressor consists of two axes, horizontal and vertical, as well as a set of curves that show the horizontal axis of the flow (capacity) and the vertical axis, head or pressure. Compressors must change their speed to change the output flow. For each speed, there is a minimum point and a maximum flow point within which the compressor operation is stable and predictable. The maximum capacity point is called the stone wall point and the minimum capacity point is called the vertex point. The surge line (SL) of a compressor is formed by connecting the surge points at different speeds. If the compressor works on the right side of the surge line, it is in a steady state, but if it works on the left side of the surge line, it is in an unstable or surge state. Using methods based on active surge control, the instabilities leading to the surge can be eliminated, and the area of stable performance of the system can be extended to the surge line, and thereby the stable area of the system can be widened. This paper uses a dynamic model of centrifugal compressors with a recycle valve, as well as a proportional-integrator-derivative (PID) controller and a sliding mode controller, to control the surge phenomenon with a compressor control approach based on the surge control line. A new sliding surface is defined for controlling sliding mode, and it is controlled by using recycle valve and a compressor inlet valve. A quadratic Lyapunov function is used to ensure the stability of the intended slip surface. The two approaches of inlet and recycle valve are expressed individually and collectively. The results of simulation in MATLAB state that among the compressor with a PID controller and the compressor with sliding mode, the latter outperforms the former in controlling the compressor at different speeds. Based on the comparison of the results, the amplitude of the control signal in the sliding mode is less than PID and the system reaches a stable state with less energy consumption, which shows better control by the sliding mode than by PID

One of the main issues of Iran is power deficiency in hot months. Due to the ever-increasing demand for energy and its consumption, it is of critical importance to optimize power-generating systems, improve their efficiency, address their drawbacks. This research aims at studying the effect of adsorption systems on the performance of the unit (its production power and efficiency) in the climate of Yazd by simulating a G13 Alstom generator in thermoflow. The results showed that using absorption systems-reduced the inlet air temperature by 20ºC, which, in turn, increased overall production power by 20.38% in comparison to when there was no cooling of the inlet air. This system also improved the aforementioned unit’s efficiency by 1.88%. The fog system was also simulated in this research. The results demonstrated that the absorption system showed a better efficiency in comparison to the fog system by 5.32%. To ascertain the validity of the model, it was validated against the real operational data for the G13 unit in base load and in different environmental conditions, as well as against the data present in the documents associated with the Yazd Power Plant. One of the novelties of this study is using heat in the craft unit outlet, which is currently released to air. If this system is applied to the unit, the efficiency of the craft unit and power plant will be improved. Moreover, this will reduce the emission of environmental pollutants into the air, which will ultimately cause a major reduction in social expenses.

Due to the progress of renewable energy technologies and the intention of energy policymakers to use these clean and cheap resources, many studies have focused on ways to take advantage of these energies. Limitations, such as low capacity, output power uncertainty, and sustainability problems, make the use of distributed energy resources costly and difficult. Among distributed generation resources, renewable energy resources such as wind energy and solar energy are more environmentally friendly and are used more than other technologies. Despite the many advantages of these resources, their output power depends on such factors as wind speed and solar intensity, which cannot be accurately predicted. For this reason, the infiltration[MSH1]  of high levels of these resources into power systems increases system uncertainty and can reduce reliability while system reliability is very important for power system designers and operators, as well as energy consumers. To solve these problems, a new concept, named virtual power plant, is proposed. A virtual power plant is a collection of distributed energy resources that come together to participate in the market. Virtual power plants can efficiently coordinate, aggregate, and manage different distributed energy resources such as distributed generation, energy storage systems, and controllable loads. These plants are flexible agents for a range of distributed energy sources that can be used in wholesale markets to provide services to system operators. The energy management system is the heart of a virtual power plant that coordinates the flow of power from generators, controllable loads, and energy storage devices. This paper proposes a full model for optimal planning of a virtual power plant if uncertainties of distributed generation sources such as wind and solar energy, as well as electrical vehicles, are considered. To prevent the negative effects of the presence of electric vehicles on electricity networks, especially in virtual power plants, it is necessary to charge these vehicles in a controlled manner and with careful planning. In addition, the demand response whose modeling is based on price-based demand response for non-users and encouragement-based for electric vehicles is optimized on two scenarios, and a 32-bus network is studied. The main goal of the research is to maximize the profit of the virtual power plant for the simultaneous use of load response and electric vehicles with the capability of connecting to the grid.

Advanced Metering Infrastructure (AMI), as one of the components of smart power distribution networks, is used to send and receive the consumption, demand, voltage, and current between subscribers and electricity power distribution companies. To set up AMI, various wireless technologies have been used as the telecommunication network infrastructure in different countries. These technologies vary in terms of technical specifications, such as bit rate, frequency, latency, and coverage area. The selection of a technology among them requires a comprehensive study of specific technical requirements of the power distribution network, wireless technology development, and specific economic conditions of each country. From this viewpoint, we first review the research conducted on the design of smart grid telecommunications infrastructure. Then, we review the deployed wireless technologies based on their physical specifications and the way of access to the wireless medium. To differentiate their field of performance properly, we divide the technologies into three categories: short-range, medium-range, and long-range; in addition, we divide them into two groups: licensed and unlicensed operating frequency. Then, we examine the  topology and medium access mechanism of each technology in terms of its transmission delay and transmission capacity; from an executive point of view, we prioritize a set of qualitative criteria for selecting wireless telecommunication technology of AMI in Iran including having technology support in our country, being an open-source technology, having low network setup and maintenance cost, data transmission rate, interference, security and passive defense, ease of design and scalability, medium-access mechanism, and battery life. Then, we compare the wireless technologies, nominated for the telecommunication infrastructure of AMI, based on the proposed criteria. Finally, we suggest some of the most appropriate ones for the congested and geographically extended network of AMI.

The electricity industry is one of the most important infrastructure industries in any country, which is very important due to its capitalization, increasing efficiency and productivity. Accordingly, the main idea of ​​this study is to present a new model for evaluating the efficiency of regional electricity companies in Iran by combining the concept of organizational dual power and network data envelopment analysis technique. The proposed model is based on the concept of dual power. Dualism is one of the newest topics in the field of organizational and management issues, which can be defined as the organizationchr(chr(chr('39')39chr('39'))39chr(chr('39')39chr('39')))s ability to focus on exploitation (use of existing capabilities) and exploration (discovery of new capabilities). In this study, with the help of network models of data envelopment analysis, the internal processes of 16 regional electricity companies in the form of two stages of "design and development" and "operation" in 1397 were analyzed and the ambiguity and efficiency of companies were calculated. The results of evaluating the efficiency of companies with the proposed model indicate that although the average of the entire electricity industry has an acceptable score in equilibrium and combined dual power, but the balance dual power score of regional power companies shows between the efficiency of design and development sectors and There is a significant difference in the operation of companies, and not paying attention to the reasons for this difference can challenge the electricity industry in carrying out its missions in the coming years.

From the viewpoint of electricity distribution companies, electricity losses are the difference between the delivered energy and the output energy, or in other words, the difference between the energy purchased and the energy sold. Electricity statistics in Iran show a share of about 23 percent of electricity losses, half of which are related to the distribution network. Electricity distribution losses fall into two categories: technical losses and non-technical losses. Technical losses are the part of the losses that occur due to the nature of the equipment in the distribution network. In contrast, non-technical losses are the total loss of electricity that is not due to the electrical nature of the network. Due to the importance of different types of electricity losses, a lot of research has been done in this field in order to reduce these losses as much as possible. However, little research has been conducted on prioritizing waste reduction strategies. Electricity losses in Jiroft City, Kerman province are a concern for Southern Kerman Power Distribution Company as they lead to financial losses and reduce the company’s revenue. According to the received statistics, the energy delivered to this city in 2018 was 1005 million kilowatts, while the sales of the company in this city was 854 million kilowatts. Therefore, the amount of electricity losses in this city is 141 million kilowatts, which is equal to 15% of the delivered energy. Therefore, this company needs to prioritize these factors in order to focus and address the main causes of losses in this city. As a result, this study aims to prioritize the causes of electricity losses in Jiroft City. In this paper, by using previous research and interviews with experts in this field, the main criteria involved in decision making were identified, and they were then were weighted using analytical hierarchical process method. Then, the causes of power losses were identified using the documents of the company, and the effective factors were prioritized according to the weighted criteria using the TOPSIS method. The results showed that, in Jiroft City, among the factors of technical losses, the losses of meters and measuring devices and the losses due to the unbalanced load in phases and single-phase distribution of low pressure were in the first and second priority, respectively. Unauthorized use of electricity in hidden manner was also recognized as the most important cause of non-technical losses in this case study.

In today’s industrial world, it is indispensable to strengthen the power distribution network infrastructure against unexpected power losses and financial damages caused by earthquakes. This paper presents a new tri-level framework for multi-microgrid expansion planning (MMEP) against seismic risks stemming from the earthquake in which the lower level describes short-term corrective actions as the distribution network operator (DNO)’s reaction after the seismic risks to apply feeder reconfiguration and generation resource redispatch. The intermediate level meticulously models the destructive effects of seismic risks on the power distribution network components, such as substations, feeders, and distributed energy resources (DERs) through a well-defined seismic scenario generation method (SSGM). In the SSGM, with a new point of view, maximum horizontal ground acceleration is modeled using a reduction procedure in terms of effective seismic parameters, including soil type, seismic magnitude, occurrence depth, and surface distance. Additionally, and more importantly, the probability of complete destruction of the power distribution network components is estimated by predetermined fragility curves. Relying on maximum horizontal ground acceleration and probability of complete destruction, multiple seismic scenarios are generated by maximizing the technical-economic damage subject to structural constraints. Then, the worst-case seismic scenario is selected. In the third level, however, the resilient optimal microgrid expansion plans, as the long-term preventive actions after the seismic risks, are identified. The MMEP objectives, modeled through the third level, are the minimization of the investment and operation costs and maximization of participation profits while satisfying long- and short-term constraints over the planning horizon. A potent melody search algorithm (MSA) is widely employed to solve the proposed large-scale mixed-integer linear tri-level framework. The proposed planning framework is implemented on a standard 9-bus 33-kV test system to demonstrate the feasibility and effectiveness of the newly developed framework. The simulation results corroborate the effective performance of the proposed planning framework in improving the resilience of power distribution networks against seismic risks.

Smart grids all over the world aim at providing reliable and resilient power to customers. During major contingencies of large-scale natural disasters, Distributed Generations (DGs) play a key role in delivering a resilient and reliable supply of loads. Major natural disasters such as floods and hurricanes often cause lengthy interruptions in electricity distribution systems and degrade the level of service to end-users. The utilities have mainly focused on restoring the distribution system since the power grid is susceptible to natural disasters. A resilient systemchr('39')s primary purpose is to allow the restoration of out-of-service loads as soon as possible after an extreme event. The resilience of a power system can be defined as “the ability of the system to prepare and plan for absorbing the damage and adapting/recovering in order to prevent the impacts of similar events in the future”. Therefore, the resilience of a power system is briefly attributed to three aspects of prevention, survivability, and recovery.  Improvements in any or all of these features can enhance the overall resilience of the power system. This paper presents a self-healing restoration algorithm for power distribution systems exposed to extreme natural disasters. Indeed, an improved restoration algorithm in distribution systems in the presence of renewable and dispatchable DGs is proposed for enhancing the survivability of out-of-service loads due to extreme events, like natural disasters. The algorithm can analyze the effects of multiple faults, which arise due to a low-probability, high-impact event like a natural disaster. In the presented method, an optimal strategy is introduced to restore maximum loads with minimum switching operations and maximum load restoration under fault conditions. In order to consider uncertain parameters, a stochastic scenario-based approach is considered and the expected values as objectives are minimized to consider the effect of all scenarios. In the proposed method, the Genetic Algorithm (GA) is utilized as a powerful algorithm in optimization and how to implement and solve the proposed model by the GA is introduced. An evaluation of the proposed approach is conducted through a typical case study. A modified IEEE 33-node system is considered for this reason. The simulated results indicate that in the presence of microgrids and an automated switching-based distribution system, the systemchr('39')s resilience is improved significantly. However, the present study did not address microgridschr('39') dynamic response. In the event of extreme natural disasters, utilities can use the proposed algorithm to improve the recovery of out-of-service loads.