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Showing 9 results for Smart Grid

S. Jadid, O. Homaee, A. Zakariazadeh,
Volume 10, Issue 2 (10-2013)
Abstract

Voltage control is one of the imperative issues in the smart distribution control system. While traditional distribution network is equipped with communication and monitoring equipment, the online voltage control can be perfectly achieved. With using these smart grid technologies, the distribution voltage control schemes should carry out intelligently and cover the undesirable effect of high penetration of renewable distributed generation. This paper presents a new approach that improved the conventional voltage control models. The proposed approach needs measuring and communication equipment less than other methods, and can cover the renewable distributed generation impact on distribution network. The proposed online voltage control model was tested on typical distribution network. The results show that the proposed model can stabilize voltage in predefined range in different consumer load fluctuation conditions and variable renewable generation levels.


Masoud Shokrnezhad, Siavash Khorsandi,
Volume 13, Issue 2 (7-2016)
Abstract

The challenging characteristics of Smart Grid such as the vast size of covered area and tight requirements of reliability (higher than 0.98) and delay (in terms of second and millisecond) impede the procedure of communication network designing. This paper investigates the problem of network designing subject to the reliability constraint. The main contribution is dividing the problem into two sub-problem, Primary Topology Design Sub-problem (PTDS) and Reliability Assurance Sub-problem (RAS). In PTDS a primary network of routers is devised to cover all network nodes using linear programming and RAS makes the primary topology reliable by adding more routers through a repetitive procedure. The main idea of RAS is balancing degrees of nodes in the network graph. Results show that the provided approach devises a fairly optimal network in an acceptable time.


Azin Shojaei, Dr Mehdi Moallem, Dr M. Hosein Manshaei,
Volume 17, Issue 2 (6-2020)
Abstract

Abstract:  
In this paper, a new day ahead energy management system is proposed for a smart grid in which distribution company and residential customers are involved. The interaction between customers and the distribution company is modeled as a single leader-multiple followers Stackelberg game. The leader of Stackelberg game is the distribution company which calculates the price of energy by maximizing its profit in a stochastic optimization framework. The residential customers, who are the followers of Stackelberg game, consider the common constraint of maximum aggregated load regulating in their optimization problem and thus play a general Nash game with each other. It is proved the customers’ general Nash game is strongly monotone and consequently has a unique equilibrium. To achieve the unique Stackelberg equilibrium, the best response-based energy management algorithm is devised, and its convergence condition is proved. It is also proved that the Stackelberg equilibrium is an optimal social equilibrium, in which the sum of customers’ cost is minimized, and the profit of the distribution company is maximized. The proposed energy management mechanism decreases the maximum aggregated load by 21.89% and increases the load factor by 27.72%.
Fargol Nematkhah, Dr Farrokh Aminifar,
Volume 19, Issue 1 (4-2022)
Abstract

Electricity demand has increased drastically during recent years. Expansion of power generation and transmission systems to address the growing demand for electricity is a lengthy process and requires extensive capital investment. Moreover, conventional methods of power generation can cause severe environmental issues. Discussed concerns have attracted considerable attention to demand-side management (DSM) policies by which system operators can monitor and control consumers in order to better match the electricity demand with power supply conditions. Meanwhile, power systems are going through a transition period due to the high penetration of renewable energy resources (RERs) and widespread use of smart devices. To remain efficient, DSM policies need to adapt to these transformations. Transactive energy (TE) is a newly-introduced DSM policy which is intended for the changing environment of power systems and is able to maintain the dynamic power balance in smart grids. This paper studies the reasons that led to the initiation of DSM programs. Further, the concept of demand response (DR) is elaborated and various types of DR programs and the existing challenges toward these programs are evaluated. Last but not least, TE is introduced as a general form of DR and the benefits and challenges that implementation of TE frameworks may bring about are analyzed.
Dr Akram Beigi, Amin Akbarian,
Volume 19, Issue 1 (4-2022)
Abstract

The electricity smart grid market is complex and dynamic. Brokers, which mediate the sale of electrical power between retailers and wholesalers, are widely used in new markets for smart grids. Due to the complexity and distribution properties of the market in smart grid networks, multi-agent systems are appropriate to solve its problems. In these approaches, we have autonomous agents exchanging information with other agents all 24 hours of a day. These agents encounter major challenges including diverse consumption patterns of consumers, price changing according to consumption patterns, and the amount of electricity consumed during the day. In this paper our goal is to increase profit in the electricity grid market while modeling the components of the electricity market with multi-agent systems. In the proposed method, we first process the customer diversity using a sequential clustering method suitable for time series data. Then, for each cluster, we apply an active policy reinforcement learning algorithm named Actor-Critic reinforcement learning. Finally, we evaluate the impact of the reward shaping on the profit earnings and we offer an hourly tariff for each cluster according to their respective consumption time
Ms. Fargol Nematkhah, Dr. Farrokh Aminifar, Prof. Mohammad Shahidehpour,
Volume 19, Issue 1 (4-2022)
Abstract

Recent changes in electricity distribution networks, such as extensive penetration of renewable energy resources (RERs), have brought about new challenges for operators. Transition from centralized energy management schemes toward decentralized ones is one of the major transformations that has been made to improve the performance, sustainability, and resilience of distribution networks and to adapt them for their ongoing changes. Internet has made its way to electricity distribution networks through the Internet of things (IoT). This information technology has emerged in the distribution networks to better accommodate the operational and management transformations. As a result, the intrinsically decentralized technology of blockchain has gained momentum as a secure platform for information exchange through IoT in distribution networks. This paper initially introduces the blockchain technology and elucidates its operation. Further, it analyzes the transition of the distribution networks to what is called active distribution networks and their functionality. Next, blockchain is represented as an effective technology for maintaining the information security and also eliminating trusted third parties in managing distribution networks. Finally, peer-to-peer energy markets are explained as an application of blockchain technology in distribution systems.
Hamed Ziaei, Prof. Masoud Rashidinejad, Dr. Amir Abdollahi, Ebrahim Pirmoradi,
Volume 19, Issue 1 (4-2022)
Abstract

Traditional systems are faced with problems such as energy loss, growing in energy demand, reliability and security, so they are turning into smart grids (SGs) to solve these problems. SGs provide a bi-directional energy connection between service providers and consumer. On the other hand, SGs have various devices for monitoring, analysis and controlling in different parts of the network. Therefore, the SGs needs a communication infrastructure between these different devices. As a result, this connectivity will be achieved by a new infrastructure such as the internet of things (IoT). IoT helps SGs systems to perform various network functions throughout the generation, transmission, distribution, and consumption of energy by using IoT equipment (such as sensors, actuator, and smart meters), as well as by providing the connectivity, automation and tracking for such devices. In this paper, the day-ahead generation scheduling is optimized in the deregulated power market with IoT infrastructure where the goal is to maximize the profit of generation companies (GENCOs). Moreover, this paper has used the demand response (DR) programs to better explore the challenges ahead in the future of SGs with IoT infrastructure. The results help to assess the quality and efficiency of such a system.
Dr. Seyed Erfan Hosseini, Dr. Alimorad Khajehzadeh, Dr. Mahdiyeh Eslami,
Volume 20, Issue 4 (12-2023)
Abstract

Individual and public awareness of global warming and pollution has required the different sectors of industry to pay more attention to this issue and take some action in this regard. The electrical industry as the backbone of most other industries should devote more effort for pollution reduction. Unit commitment is the process of determining the state of the units for the day-ahead market. Therefore, managing unit commitment is the best option for contamination reduction. However, in the smart grid, customers can be part of the market via demand response programs. On the other hand, congestion is one of the main problems of the transmission network. Demand response programs could have a positive effect on congestion alleviation as they reduce the total power transmitted via the transmission system. 
In this paper, the effect of aggregated demand response programs as virtual power plants on operation cost, congestion and emission of network-constrained unit commitment is investigated. Moreover, the best rate of the incentive paid to the demand response programs participants is determined. In this study, according to the simultaneous implementation of the unit commitment problem and the demand response program, which is a complex nonlinear problem with continuous and discrete variables, the MILP method has been applied. Moreover, the transmission system is also considered to fully analyze the impact of demand response programs in the electricity market and its impact on reducing congestion. The recommended strategy is carried out on the IEEE 24 bus reliability test system to prove the effectiveness of demand response programs integration for cost and emission reduction.
Dr. Hamidreza Toodeji, Dr. Mohsen Jannati,
Volume 21, Issue 4 (12-2024)
Abstract

Modern voltage control strategies in the present distribution networks require efficient equipment as well as appropriate communication channels between these equipment, sensors and control centers, which has led to smart distribution networks with a complex cyber-physical nature. One of the efficient equipment for voltage control in modern distribution networks is the DSTATCOM, which uses using multilevel converters in its structure, provides many advantages, such as direct connection to the grid. A DSTATCOM with the multilevel converter requires a cyber-physical network between the controller and its components due to the presence of many controllable components, which makes it vulnerable to cyber-attacks, when connected to the present smart distribution networks. In this paper, a feedback linearization-based controller is developed for the cascaded multilevel DSTATCOM, and a discrete Kalman filter-based method is proposed to detect and compensate false data injection cyber-attacks on voltage sensors of the multilevel converter. The abilities of the proposed nonlinear controller to control the multilevel DSTATCOM as well as the reliable operation against false data injection attacks are verified through the simulation of a test power network in the MATLAB/Simulink environment.

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