N. Afsari; S.J. SeyedShenava; H. Shayeghi
Abstract
The inevitable emergence of intelligent distribution networks has introduced new features in these networks. According to most experts, self-healing is one of the main abilities of smart distribution networks. This feature increases the reliability and resiliency of networks by reacting fast and restoring ...
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The inevitable emergence of intelligent distribution networks has introduced new features in these networks. According to most experts, self-healing is one of the main abilities of smart distribution networks. This feature increases the reliability and resiliency of networks by reacting fast and restoring the critical loads (CLs) during a fault. Nevertheless, the stochastic nature of the components in a power system imposes significant computational risk in enabling the system to self-heal. In this paper, a mathematical model is introduced for the self-healing operation of networked Microgrids (MGs) to assess the risk in the optimal service restoration (SR) problem. Electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) and their stochastic nature besides the distributed generation units (DGs), the ability to reconfiguration, and demand response program are considered simultaneously. The objective function is designed to maximize the restored loads and minimize the risk. The Conditional Value-at-Risk (CVaR) is used to calculate the risk of the SR as one of the most efficient and famous risk indices. In the general case study and considering $\beta $ equal to the 0, 1, 2, 3, and 4, expected values of SR for the risk-averse problem is 21.2, 20, 19.3, 19.1, and 19\% less than the risk-neutral problem, respectively. The formulation of the problem is mixed-integer linear programming (MILP), and the model is tested in the modified Civanlar test system. The analysis of several case studies has proved the performance of the proposed model and the importance of risk management in the problem.
E. Naderi; S.J. SeyedShenava; H. Shayeghi
Abstract
This paper presents the output voltage control and execution of a novel non-isolated high step-up (NIHS) DC-DC converter connected to a solar photovoltaic (PV) based DC microgrid system. The proposed converter provides a high output voltage conversion ratio over smaller duty cycles, small inductors, ...
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This paper presents the output voltage control and execution of a novel non-isolated high step-up (NIHS) DC-DC converter connected to a solar photovoltaic (PV) based DC microgrid system. The proposed converter provides a high output voltage conversion ratio over smaller duty cycles, small inductors, low cost, and high efficiency to enhance the level of the generated voltages of PV. Also, to overcome the drawback of PV, the detailed operation of maximum power point tracking (MPPT) for the novel boost DC-DC converter topology is presented. A control algorithm, modified perturb and observe (MP&O), is put forward to assure that the maximum power is extracted from PV at any environmental condition. It regulates the output voltage of the PV system to the desired DC bus voltage. This technique is compared with the Incremental Conductance (INC) and conventional P&O algorithm in terms of their computational complexity and oscillations near maximum power point (MPP) using MATLAB & Simulink. The focus is on the continuous conduction mode of the proposed converter. To demonstrate the effectiveness of the proposed converter, operation modes, and technical analysis are conducted. Also, the experimental results of a 200 W-12V/120V, 25 kHz prototype are given and discussed to justify the suggested converter.
E. Naderi; A. Dejamkhooy; S.J. SeyedShenava; H. Shayeghi
Abstract
Recently due to technical, economical, and environmental reasons, penetration of renewable energy resources has increased in the power systems. On the other hand, the utilization of these resources in remote areas and capable regions as isolated microgrids has several advantages. In this paper, a hybrid ...
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Recently due to technical, economical, and environmental reasons, penetration of renewable energy resources has increased in the power systems. On the other hand, the utilization of these resources in remote areas and capable regions as isolated microgrids has several advantages. In this paper, a hybrid microgrid, which includes photovoltaic (PV)/wind/energy storage, is investigated. It has been located in Iran-Khalkhal. The purposes of this study are optimal energy management and sizing of the microgrid. Since the magnitude of the harvested renewable energy deals severely and complexly with season and climate issues, planning of the system based on their specific values is an oversimplification. Therefore, in addition to conventional constraints such as environmental and operational ones, estimation of the wind speed at the site is considered. The Monte Carlo method is employed to model and estimate wind behavior. Also, for regulating production and demand in the microgrid the Demand Response (DR) program is conducted to improve the contribution of the renewable energy resources. The planning is constructed as an optimization problem. It is formulated as a Mixed Integer Linear Programming (MILP). By solving it, the size and production magnitude of energy sources, as well as storage conditions, are determined. Finally, the proposed method is simulated by GAMS for all seasons of two scenarios. The results show desirable energy management and cost reduction in the studied grid.
A. Afraz; B. Rezaeealam; S.J. SeyedShenava; M. Doostizadeh
Abstract
The scheduling of electricity distribution networks has changed dramatically by integrating renewable energy sources (RES) as well as energy storage systems (ESS). The sizing and placement of these resources have significant technical and economic impacts on the network. Whereas the utilization of these ...
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The scheduling of electricity distribution networks has changed dramatically by integrating renewable energy sources (RES) as well as energy storage systems (ESS). The sizing and placement of these resources have significant technical and economic impacts on the network. Whereas the utilization of these resources in the active distribution network (ADN) has several advantages, accordingly, the undesirable effects of these resources on ADN need to be analyzed and recovered. In this paper, a hybrid ADN, including wind, PV, and ESS, is investigated in 33 buses IEEE standard system. First of all, optimal energy management and sizing of the RES and ESS are the purposes. Secondly, as demand response (DR) is another substantial option in ADNs for regulating production and demand, an incentive-based DR program is applied for peak shaving. Forasmuch as this method has uncertainty, due to its dependence on customer consumption patterns, the use of inappropriate incentives will not be able to stimulate customers to reduce their consumption at peak times. Accordingly, the climatic condition uncertainty, which is another factor of variability on the production side, is minimized in this paper by relying on the Monte Carlo estimation method. Besides, the optimization problem, which is formulated as optimal programming, is solved to calculate the optimal size and place of each RESs and ESS conditions regarding power loss, voltage profile, and cost optimization. Furthermore, a geometric, energy source and network capacity, and cost constraints, are considered. The results confirm the effectiveness of proposed energy management and cost reduction in the studied test system.
Micro Grid
A.M. Dejamkhooy; M. Hamedi; H. Shayeghi; S.J. SeyedShenava
Abstract
A stand-alone microgrid usually contains a set of distributed generation resources, energy storage system and loads that can be used to supply electricity of remote areas. These areas are small in terms of population and industry. Connection of these areas to the national distribution network due to ...
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A stand-alone microgrid usually contains a set of distributed generation resources, energy storage system and loads that can be used to supply electricity of remote areas. These areas are small in terms of population and industry. Connection of these areas to the national distribution network due to the high costs of constructing transmission lines is not economical. Optimal utilization and economic management of production units and storage devices are important issues in isolated microgrids. During optimum utilization, of renewable energy harvesting is maximized and fuel cost of diesel units reduces as much as possible. In this paper, the optimization problem is designed and solved as Linear Programming (LP). The cost of diesel generator unit depends on its production. Also, the fact is considered that the efficiency of diesel generator units is not constant for all amount of production. As a solution for this challenge demand side management plans have been proposed. On the other hand, load uncertainty is considered in this paper. Several scenarios are simulated by GAMS software for different conditions of a typical microgrid. The simulation results show the success of the proposed method in reducing costs and fossil fuel consumption and increasing the consumption of renewable energy.
