جستجوی مقالات مرتبط با کلیدواژه « resiliency » در نشریات گروه « فنی و مهندسی »

Natural disasters and cyber-attacks pose many risks to the acceptable performance of power grids. In addition, the bitter experiences, gained from the recent Natural disasters in the country, lead to a greater focus on the concept of resilience. In this paper, a flexible method for improving the distribution network distribution resilience is proposed considering remote control switches and mobile power sources according to Tavanir Company policies. In the proposed method, changing the network configuration in real-time, controlling switches, and utilizing mobile power sources bring high flexibility and resilience to the network. The objective functions and constraints of the problem are completely linearized to reduce the complexity and solving time of the resilience problem. The mixed-integer linear programming method is used in the proposed method to optimize the objective functions. A modified IEEE 33-bus distribution system is utilized to evaluate the efficiency of the proposed method. According to the results, when the mobile power sources are located in the network based on the proposed method along with sending the repair team and operating switches after a disaster, the value of the objective functions and un-supplied loads are reduced by about 85 %. Therefore, the proposed method has a proper performance in increasing the resilience of distribution systems.

Economical and resilient operation of energy systems has always been one of the important and main priorities of the energy systems operators. However, with the progress made in various fields of energy systems, especially power systems, the discussion of resilience and reduction of energy not supplied has become more important. In other words, in addition to the supply of energy consumers, the issue of energy welfare is raised which is a function of the energy not supplied index. And according to that, the consumer expects the energy receives with maximum possible power quality and minimum outage. Therefore, in this paper a bi-objective optimization model is proposed to improve the economic performance of the energy hub system and to improve the resilience of electric consumers under adverse weather conditions, in which the operational cost of the hub energy is minimized and on the other hand, the consumer welfare index, which is a function of the energy not supplied index of the system, has been maximized. It is assumed that outage rate of electrical lines can be affected by weather conditions. To solve the optimization problem, the epsilon constraint method has been used and in the following, the fuzzy Max-Min method is used to select the optimal solution from among the set of solutions.

After extreme natural events like earthquakes, storms, and floods, the electrical distribution network may be isolated from the upstream grid. In such a situation, the electrical power of the upstream grid is lost and the available microgrids (MGs) are the only power sources. Since the power outputs of MGs are restricted, restoring all de-energized loads is impossible and restoring critical loads (CLs) becomes the most important concern of the distribution network operators. Therefore, in this paper, a new hour-by-hour restoration strategy for CLs restoration after a blackout is proposed. The desired objective functions include restored energy and switching operations. The proposed restoration strategy presents a restoration plan for each hour of the outage period. The efficiency of the proposed strategy is carried out on an IEEE 123-bus distribution network and the simulation results confirm the superiority of the proposed hour-by-hour restoration strategy over the other conventional restoration methods.

Due to the growing use of Plug-in Electric vehicles in transportation networks, scheduling the charge/discharge of electric vehicles in parking lots can have great impacts on the distribution network's resiliency. This paper presents a Bi-level optimization model to improve the resiliency of the distribution network that takes into account the interaction between the distribution network islanding problem and the charge/discharge scheduling of electric vehicles in available parking lots. In the upper-level problem, regarding the electrical loads and managing the charge/discharge of electric vehicles in electrified parking lots, the island boundaries are determined with the aim of maximize the load restoration. By knowing the islands' boundaries and restored parking lots from the upper-level problem, the changes in destination parking lots and travels characteristics are determined in lower-level problem to minimize the shortest path between the out-of-service destinations and in-service parking lots. The proposed model has been implemented and validated through applying several concurrent faults to the 118-bus active distribution network in presence of electric vehicles in the 25-node traffic network. A combination of mathematical programming and the evolutionary algorithm is applied to reach the final solution. The case studies' results confirm the efficiency of the proposed model for improving the resiliency of distribution networks with managing the charge/discharge of electric vehicle fleets in restored parking lots.

Resilience characteristics in power systems refer to the system's ability to withstand against severe disturbances with a low probability of occurrence. As extreme dust storms in the south and southwest in recent years have caused heavy damage to the IRAN's electricity industry, in this paper, a bi-level planning model is proposed to simultaneous hardening of distribution lines and substations against this phenomenon. In the first and second levels of the proposed model, the investment costs of distribution system hardening and total expected operating costs are minimized subject to financial and operational constraints, respectively. The planning results in different case studies have shown that the simultaneous hardening planning of substations and distribution lines can, in addition to reducing operating costs in the emergency conditions, play a significant role in reducing investment costs. The proposed model is implemented on a large-scale power distribution system in Khuzestan province, and the simulation results confirm the efficiency of the proposed scheme at different budget levels.

Wind power generation is making an increasingly significant contribution to global electricity production. The high penetration of wind power poses many operational and control challenges that affects the reliability and stability of power systems. In this Paper, the reported technical challenges caused by the grid integration of wind energy conversion system (WECS) and the proposed solutions methodologies represents. The wind-generating system components and architecture are investigated at the beginning of this article for analysis and stability studies purposes, then are addressed various technical challenges; each challenge is discussed individually, focusing on the bulk integration of wind energy into the power systems. Some solutions, including grids code, energy storage technologies, appropriate control strategies, and other methodologies employed to mitigate the effects of the integration, are also included. This review is ready-reckoner of essential topics for further research of wind energy and available technologies in this field. This review provides ready-reckoner of essential topics for grid integration of wind energy and available technologies in direction of overcome the related difficulties.

In this research, an optimal energy management model of a residential microgrid with the aim of resiliency and flexibility improvement is presented. Accordingly, a residential microgrid consisting of a solar power plant with energy storage system is considered. Each of houses in the microgrid has an electric vehicle. The residential microgrid is connected to the main grid and has been equipped with smart grid infrastructures. The outage of the main grid causes load shedding that consequently reduces the resiliency. Keeping the security of supply during these distortions is necessary. Therefore, in this paper, a new model of microgrid operation based on solar power plant and energy storage system is proposed. The efficiency of the proposed model is evaluated through numerical calculation of resiliency using a new index proposed in this paper. In addition, the proposed model improves the system flexibility. The amount of this improvement is evaluated using practical and accurate indicators including self-consumption and storage efficiency. The results show that the proposed model improves the resiliency in off-peak and peak hours by 4.7% and 9.75% respectively. Moreover, two indexes of flexibility, including self-consumption and storage efficiency, improve by 9.1% and 2.2% respectively.

The microgrid inertia as a result of tiny structure and barely tolerance variations, is fairly low. Thus, the maintenance of voltage stability and frequency specifically in islanded mode is extremely demanding. Even if these products have efficient control system, they can’t retain microgrid stability due to the low speed of response in primary sources of energy and communication delays of the links between outer unit and control system in distributed generation. Introducing a structure of fuzzy control arranged with neural network to balance between generation part and consumption part in micro grid is the main purpose of this paper. Using the fuzzy logic, this controller enables flexible operation of microgrids in both network and islanded modes. In the proposed control system, a trainable neural network in different operating conditions is responsible for fine tuning of the fuzzy logic system. Because of the sensitivity of the loads in the microgrid the proposed structure is designed to interact with the storage source in order to increase the response speed to the imbalance between production and consumption. This might prevent excessive voltage and frequency deviation, especially in the severe situations. With this controller, fluctuations in the production of renewable resources quickly compensated without a negative impact on resilience and instability of the microgrid, especially while disconnecting from the main network

One way to improve the distribution network resilience is to use mobile generators (MEGs) in the network. Such generators with the ability to move in the network and supply power to different parts increase the possibility of supplying important loads. However, due to the limited fuel of these generators, their movement will be limited, which will reduce their efficiency. Therefore, in this paper, considering this type of generators and also their limited fuel, an algorithm for their optimal displacement during the disaster is presented. Also, by considering fueling vehicles and planning to move them to inject fuel into these generators, an attempt has been made to reduce the effect of fuel restrictions on these generators. Finally, by simulating the proposed algorithm on the IEEE 33-bus network, taking into account the daily variable loads, the effectiveness of the proposed algorithm on improving the resilience of the distribution network is shown.

Accepetance of the fact that the working context of civil projects is challenging can enhance the resiliency capacity and will increase the project management concentration for improving and developing the software and hardware capabilities to facilitate project success achievement. This article is documented based on a research results in macro-hydropower plants projects management context to represent a new project management approach named as “Resilient Project Management”. Thematic analysis is the chosen research methodology in this study. Different qualitative and quantitative techniques are used in the study. Systematic literature reviewe, opened interviews and closed questionaries are the tools to gather datas inorder to demonostrate the framework. Results showed that there are six main demensions and related requirements to implements resilient project management approach in project management context. Management and leadership style, Organizational structure and human Resources, Working processes and resources, Performance index management and control, Maintenance management and readiness efforts and Chrises control and management are the dimensions of resilient project management approach.

Predicting the status of power grid components, especially overhead lines in response to extreme weather event, plays an important role in planning pre-resource allocation, as well as restoring loads more quickly at a faster time which can improve the power grid resilience. In this paper, a Multi-dimensional Support Vector Machine algorithm is proposed to predict outage overhead lines assuming storm paths. In this model, dimensions are based on five distinct features: the distance from building, distance from tree, distance from center of storm, storm speed and cable type. The result of the proposed model is the classification of overhead lines status into two out and operational statuses implemented on the 33-bus IEEE network. The results show that the proposed model predicts outage lines with high accuracy.

Islands are generally considered strategic points for enemy missile and drone strikes. Therefore, due to the vulnerability of these islands to such attacks and the need for sustainable energy supply, the concept of resilience is very important in the day-ahead scheduling of energy resources on the islands. On the other hand, with the increasing prevalence of emerging resources such as electric vehicles, electrical storage, and demand response programs in microgrids, the need for integrated scheduling to use the capacity of these resources to improve the resilience of these networks has increased. To this end, this paper examines a two-stage scheduling approach to reduce the daily operating costs and improve the resilience of an island microgrid integrated with wind turbines. In addition, the effects of coordinated scheduling of emerging energy sources, including grid-connected electric vehicles, an electrical storage system, and shiftable electrical demands are evaluated to improve the daily operating costs and system resilience. The resilience index is considered as the sum of the cost of load shedding and the cost of increased power production in the event of an enemy attack on the wind turbines. Therefore, the proposed model determines the best operation strategy under normal conditions in such a way that, in the event of an enemy attack on the wind turbines, the lowest cost of load shedding and the lowest cost of increasing production in the presence of emerging energy sources will be tolerated by the islanding microgrid.

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.