مجله کیفیت و بهره وری صنعت برق ایران
سال دوازدهم شماره 4 (پیاپی 33، زمستان 1402)

The development of photovoltaic solar systems as one of the solutions for electricity supply in the form of sustainable and modern development has attracted much attention in recent years. Nevertheless, since these systems are located in open environments, they are exposed to a set of external harsh conditions and stresses during their working period. Ultraviolet radiation, fluctuating temperature, and humidity cycles, rain, snow and hail, wind, dust and sand storms, or salt deposition can severely affect the efficiency of photovoltaic power plants and the lifespan of these systems. Accurate prediction knowledge of the types of possible failures for these systems can lead to better management of the systems and their higher productivity. Therefore, in the present study, a content analysis method was used to review previous research in this field to categorize and explain the types of failures reported for these systems as well as the reasons for such failures and the affected components. The studies conducted in this field showed that among the degradation mechanisms related to weather and environment, the degradation mechanisms of ethylene vinyl acetate copolymer, and the stability relationships of this material in silicon-based solar panels have been investigated. The effects caused by the degradation of this polymer such as color change, layering, bubble formation, and corrosion, and their relationship with polymer structure, and chemical, mechanical, optical, and electrical properties have also been studied. The results of this research have been presented to researchers and decision-makers in the field of photovoltaic solar systems and the efficiency of the electricity industry.

Energy management between renewable energy sources and energy storage systems is challenging especially in different operating modes in stand-alone DC microgrid. In this paper, a new energy management system strategy based on law and fuzzy logic is proposed for a stand-alone DC microgrid with hybrid energy storage system (HESS) consisting of battery and supercapacitor (SC). The design of the proposed system is simple and does not require the mathematical model of the system. The main advantages of the proposed strategy are: high DC link voltage reference tracking in the presence of source and load power disturbances, keeping the battery and supercapacitor charge level within the permissible range, preventing battery and supercapacitor from overcharge/discharge and controlling the battery charging/discharging rate. Moreover, the proposed strategy increases battery life span while decreasing its current stress by using high charge/discharge cycles in SC and providing the majority of the output current through it. The proposed technique has been simulated in MATLAB and results show the priority of this method from the abovementioned points of view.

The inertia constant, a key parameter that makes power systems robust to disturbances and disruptions, has today been changed by factors such as the influence of renewable generation units and the reduction of traditional synchronous generators. Changes in the inertia of a power network play an important role in its performance, and a lack of knowledge of its status will have severe consequences for the network's online protection and control systems. Hence, knowledge of its online changes is essential for transmission system operators. This paper presents an online inertia estimation method that is based on inter-area electromechanical oscillations and simultaneously estimates the network inertia constant and the system damping coefficient. Unlike the previous methods that have used the flow of active power between two areas, the oscillation parameters are extracted from the voltage angle of the buses, improving the accuracy of the estimate. For this purpose and based on the classical swing equation, the relationship between the inertia constant of the system and the electromechanical oscillation parameters is first determined by the Prony technique. Then, the network equivalent inertia and damping coefficient are estimated. The efficiency and accuracy of the proposed method are verified by DigiSilent and MATLAB software and in several scenarios implemented on the IEEE 39-bus standard network. The simulation results show the appropriate accuracy of the proposed method. It is shown that the results of estimating the inertia and damping coefficient based on the active power signal have an average error percentage of 10 and 17.32, respectively. After using the voltage angle signal, the results are improved to 9.03 and 11.94, respectively. Due to the simplicity and small burden of calculations, the presented method can be easily used by network operators.

In electrical industry, companies are looking for ways to reduce costs while improving and maintaining reliability of equipment in repair and maintenance category. In this paper condition-based maintenance model in parallel electricity distribution network is studied. A single control limit is determined for all components to minimize a total expected cost during planning horizon subject to reliability constraint of the whole parallel system. Considering the covariate values on the component’s deterioration, proportional hazard model is adopted and we provide a closed-form of analytical solution for the reliability of tampered failure rate load-sharing system. It means failure of one component will affect the failure rate of other components. In this research between both inspection points, if component fails, a minimal repair action must be performed, so we have two cost types for each component; the cost of minimal repair and the cost of replacement. At each inspection point, the failure rate is measured and compared with the optimal control limit decided in the previous step. If it exceeds the control limit, the system must be replaced and the replacement cost is considered, but if it does not exceed the control limit, it will continue to work until the next inspection point without performing any maintenance. Inspection points are performed based on amount of failure age-dependent and the value of covariate variables in time intervals. Modeling a multi-component system is challenging due to the interdependence of the failure behavior among the components and determining the optimal control limit for preventive replacement. Although different research works have been done in the literature on condition-based maintenance models, there is a research gap in considering the failure dependency of components. Most of them consider independent failure between the components or the degree of failure dependency is precisely specified.  It can cause inefficient analysis and incorrect assessment of the situation.
The proposed nonlinear programming model has been evaluated with MATLAB software. This plan helps the technicians to control the reliability of the system and the operation of the components at a higher level by considering the failure dependency between the components during the inspection periods. Furthermore, they are informed about failures earlier, before incurring the replacement costs. The results show that the network reliability of the proposed model has a better performance than the basic model. At the end, in order to confirm the effectiveness of the approach, a case study of the electrical panel is examined.

Reactive power has countless benefits for power systems, which are called reactive power sub-services. One of these services is voltage control. The main goals in this research are to find the suitable price for reactive power and set the voltage of the buses in the allowed range and at the same time consider the suitable amount of reactive power in the generation buses as a reserve for technical and voltage support in the power system. In order to optimize the objective functions, the gray wolf optimization algorithm has been used and 33 bus radial distribution system has been considered and it has been assumed that the load of the power system changes during 24 hours and it is assumed that in this distribution network, generators are placed in some buses. The simulation results show that in addition to the cost of reactive power being minimized, a suitable amount of reactive power is also stored in the generation buses and the voltage deviations of the buses are also minimized.

In the optimization problems of intelligent distribution systems where there are many variables and parameters, providing an efficient algorithm that has the ability to converge and solve in large networks is one of the main challenges of researchers. In this paper, a compound integer quadratic optimization model for improving the performance of large-scale distribution network using demand-side management problem, energy storage system, battery-to-metro system, optimal control of OLTC and SVR tap-trans and distributed generation resources. Fossil and renewable are offered alongside capacitor and shunt reactors. The considered multi-objective function is a scenario-based stochastic model, which accurately models the uncertainties in renewable energy sources. According to the considered problems and also the model of large networks of 118 and 874 buses, most of the algorithms are not able to converge due to the existence of many variables. In this article, the optimal performance of the proposed hybrid evolutionary algorithm is shown on large distribution networks, which is able to reach global optimal solutions compared to similar algorithms.

With the increasing penetration of renewable energy sources such as wind and photovoltaic generation in future microgrids, challenges arise due to variable weather conditions. In this paper, a model is proposed to optimize the performance of microgrids under the worst-case scenario of renewable energy source failures using a bi-level optimization. In the upper-level problem, optimization is carried out in terms of energy loss reduction, load shedding in the load management program, as well as optimal charging and discharging of energy storage systems. The lower-level problem considers maximizing the utilization of renewable energy. A bi-level optimization solution method is proposed, which involves binary variables at both levels and is solved using a non-dominated sorting genetic algorithm (NSGA-II). The proposed model and algorithm are implemented using the Julia programming language. The performance of the model is examined under various conditions using a 33-bus microgrid, and the optimization results demonstrate the optimal performance of the microgrid under the worst-case scenario of renewable energy source failures.

Considering the significant effect of human resources in the growth and achievement of goals in Iran's electricity organization and the special position of this organization in the country's economic cycle, human resources model in Iran's electricity organization seems necessary.
In this research designed and presented the maturity model of human resource management processes in Iran's Electricity Organization (Tavanir Company; one of the specialized parent companies of the Ministry of Energy in the electricity sector). In order to improve various aspects of human resource management in Iran's electricity organization, as well as in order to identify its strengths and areas that can be improved, there is a need for a "maturity model of human resource management processes" and indicators in this regard.
The maturity model of human resource management helps the electricity organization to determine the evolution of its human resources measures and to manage its continuous human resources development programs.
The method used in this research is the Content Analysis Method, and the Delphi Method was used to score the 7 levels of the model. The main findings of this research was to find a model to measure the maturity of the human resources management in Iran's electricity organization.
In the main model, elements such as general job skills, communication, technical skills, management, leadership, qualities and finally productivity show the levels of maturity development in the said organization.
In the second model, which is implicitly obtained from the examination and analysis of the main topic of the research, the organization's priorities are; Being within expectations, exceeding expectations and being outstanding, are determined.