نوید تقی زادگان کلانتری

Today, with the growing demand for hybrid electric vehicles in microgrids, electricity supply, environmental issues, and rescheduling are among the challenges of microgrids that must be solved and suitable solutions provided. To overcome these challenges, this paper introduces a new multi-objective optimization model, which in the first objective, minimizes the total operation cost of the microgrid, and in the second objective, improves the reliability index by reducing the amount of energy not supplied. Due to these two objectives, a multi-objective evolutionary seagull optimization algorithm is used to find the optimal global solutions. In this regard, hybrid electric vehicles and demand response programs are used to smooth out distribution nodal prices and reduce CO2 emissions. The 69-bus distribution network has been used to evaluate the efficiency of the proposed method.

With the exponential penetration of renewable energy sources (RES), the need for compatible scheduling of these has increased from economic and environmental points of view. Due to the high-efficiency and fast-response features of combined heat and power (CHP) generation units, these units can immunize the system against RES fluctuations. To address the operational challenges associated with RES, this paper aims to schedule the arbitrage of cryogenic energy storage (CES) not only to maximize its owner but also to minimize RES variability. On the other hand, plug-in electric vehicles (PEV) are applied in the proposed model as responsible loads to smooth the system's load profile by changing the consumers' consumption patterns. The proposed problem is modeled as second-order cone programming and solved by the dominated group search optimization algorithm. To verify the applicability and effectiveness of the proposed approach, four different case studies have been executed.

Energy supply is the most important need of human societies because life is impossible without energy. Therefore, the operation of energy resources is a substantial subject in the management of these resources. On the other hand, energy resources are often interdependent, which can help their management. In other words, the integrated operation of energy resources can be useful in energy management. In this regard, “the energy hub” has been introduced as a new concept for the integrated operation of energy resources. Using the concept of an energy hub, this paper tries to reduce the energy supply costs of consumers and manage these resources by integrated and simultaneous operation of electricity, natural gas, and water. In modeling, various pieces of equipment, such as energy storage devices, combined heat and power systems, and renewable sources, are used. Power-to-gas technology is also used to produce hydrogen and natural gas from water and electricity to supply hydrogen loads and inject the natural gas produced into the gas network. Power-to-gas technology uses excess electricity produced by renewable sources to produce hydrogen, which is obtained from the breakdown of water molecules. Given that the technology requires carbon dioxide to produce natural gas, this can reduce air pollution. In addition, a demand response program is implemented to shift a part of the electricity and heat consumption from peak hours to off-peak hours in order to reduce operating costs. Load transfer can be done with different methods, such as incentive plans or load management on the demand side. This modeling is a mixed integer linear programming. As mentioned, the model presented in this article is linear, so it is necessary to linearize the nonlinear equations. In this modeling, a method called "the Cartesian" method is used for linearization. After linearization of the nonlinear equations, this problem has been solved by GAMS software using the CPLEX solver. The results show that the proposed model has a significant impact on reducing operating costs and air pollution. In other words, devices such as electric heaters, combined heat and power, and power-to-gas units could reduce operating costs by 22% by converting energy carriers into different forms of energy, thereby significantly reducing pollutant emissions into the air so that, in the presence of the power-to-gas unit, the amount of pollution in the air can be decreased by 26%.

Power transformers are one of the most vital and expensive devices in the electricity transmission and distribution network. Therefore, monitoring and evaluating their operational condition is a vital issue for managers in the electricity industry to prevent failure in the power distribution network, maintain their highly reliable performance, manage their assets, and increase the productivity of the network. The results of many research works have indicated that the useful life of a transformer is directly related to the life of its paper insulation system. The measurement of furan compounds released into the insulation oil due to the degradation of cellulose in insulation paper is a common method for assessing the operational condition of the transformers. High-performance liquid chromatography (HPLC) has been introduced as one of the relatively well-established methods for measuring furan compounds according to ASTM-D-5837. Regarding the need for high profession and expertise for operating and using HPLC system as well as the high price of this system, it is inevitable to develop fast, simple, cheap, and user-friendly systems and techniques with high precision without any need for high operator profession. The use of ultraviolet-visible (UV-Vis) spectroscopy has been proposed as a new, effective, and economically preferable alternative method for measuring the concentration of cellulose degradation compounds in insulation oil. However, the excessive turbidity of the oil in older transformers caused by the cellulose degradation products exerts a relatively high ambiguity on the results of this technique and may make its results somehow unreliable. In this paper, a new method is proposed to improve the optical spectrum results and solve the turbidity problem of the used oil samples. This method is composed of the dilution of oil samples with adequate solvents to overcome their high turbidity in combination with the fuzzy logic to evaluate the UV-Vis results. The proposed method was implemented on oil samples taken from 23 transformers. A fuzzy logic algorithm is used to estimate the furan compound contents from the optical spectrum of the oil. The comparison between the results of the method developed in this work and the results of HPLC analysis reveals a relative error as low as 11%, proving that the developed method can be a safe, fast, and cost-effective solution for electricity distribution network operators to assess and monitor the status of network transformers.

One of the main goals of distribution network operators is to reduce the cost of operating the network and improve profit. In this paper, the problem of siting and determining the size of energy storage batteries are studied. The constituent components of the objective function of the placement problem include the profit from the operation of the distributed generation unit, the profit from the reduction of grid power losses, the cost of installing an energy storage system, and the profit from the reduction of energy purchased from the upstream network. The model used for positioning is based on the probabilistic behavior of solar radiation, energy consumers, and electricity market operators. To model the stochastic nature of the output power of solar power plants, the probability density function has been used, and to model the load and price of electricity, the scenario method has been used. The simulations were performed using MATLAB software. The proposed method can manage the generation of solar power plants using the siting and management of charge and discharge of batteries.

The integration of the distributed energy resources into a single entity can do with virtual power plants. VPP is a cluster of dispatchable and non- dispatchable resource with flexible loads which distributed in allover the grid that aggregated and acts as a unique power plant. Flexible load is able to change the consumption so demand response program is applied to use them to improvement of the power system performance. Virtual power plant generation has uncertainty and it make hard to schedule the VPP. To deal this matter Information gap decision theory hint us to optimal schedule of the VPP. To show the effects of VPP and DRP on power system operation cost a bi-level unit commitment with regard the VPPs and DRP is solved in modified IEEE 24 bus reliability test system. Results in presence of VPP and DRP in both IGDT strategies are compared with disregard VPP and DRP and effectiveness of the proposed model is reflected.

This paper presents a reliability assessment algorithm for radial distribution systems such as microgrids and distributed generation units. The effects of these units and system reconfigurations on distribution system reliability can be evaluated by using the proposed algorithm. The impacts of the location and capacity of the distributed energy resources of microgrids and sectionalizing switches on reliability indices are determined. Moreover, proper location is determined by the classification of load points in distribution system. An approach to identifying the out of the service section after a fault event is presented based on the adjacency matrices. The classification of nodes is obtained by identifying different adjacency matrices based on protective devices. At last, the reliability indices of radial distribution system are calculated.

The microgrid is a set of local energy producers and consumers that can be utilized with low cost and high reliability. In this paper, a robust multi-objective model is proposed to reduce operating costs and carbon emissions in which a smart grid utilizes a wind turbine and micro-turbine to feed its connected loads. The microgrid also uses a battery to store electrical energy in off-peak hours and to deliver energy in on-peak hours. On the other hand, it is connected to the main grid and can exchange energy with it. Consumers connected to this microgrid are divided into two groups. The first group is uncontrollable loads with certain load pattern and the second group is controllable loads that have certain energy consumption but can be controlled by the operating time. The proposed model is a mixed-integer linear programming problem and is simulated with the CPLEX solver in GAMS software. The results show that when the price of electricity is low, the loads are often supplied by grid electricity, and when the price of electricity is high, they are often fed by micro-turbines, batteries, and wind turbines.

This paper presents an optimal method of frequency load shedding (UFLS) based on the rate of change of frequency of load (ROCOFL) in islanded distribution networks (DN). The proposed method minimizes the average amount of penalties paid by the independent operator of the network by utilizing the relevant cost function. The function of islanded distribution network occurs after an error in the sub-transmission network and separation from the upstream network, in an emergency condition, is one of the most important facts that has been recently addressed. The use of installed intelligent equipment to measure and send information, related to power, frequency, frequency changes, voltage range, and condition of generator switches makes it possible to provide an appropriate protection for the islanded networks. The under frequency load shedding is used to improve the network frequency due to the imbalance in the network. In this paper, it is tried to use the two proposed control modules to eliminate the optimal load with the consideration of the minimum penalty. The method presented in this paper is evaluated in the sample network of 14-bus Danish distribution network.

In this paper, a novel structure based on Bridgeless AC/DC Converters for BLDC Motor is proposed. For now, to drive this kind of dc motors, step down and step up converters and converters with capability of increase and decrease in output voltage with bridgeless diode structures are presented. In this paper by using a novel structure, this possibility is provided to have a converter that can work in desired and separate states such as buck, boost or buck boost operations. In this paper focus will be upon buck-boost operation to access appropriate usage of both decrease and increase at output voltage advantages. Also this converter would not need to a diode bridge at primary of circuit. At output of this converter only a dc-link capacitor exists, that it will decrease the need of electrolytic capacitors that result to decreased circuit volume and cost. Removing of input diode bridge and input dc-link capacitor has caused to a better quality of input current waveforms. As well as, power factor for input power supply of this converter will work near to unit amounts.

In the recent years, integrations of renewable energy sources as well as plug-in electric vehicles are increased in the AC microgrid. Also, demand side management can be used to manage peak load in order to improve optimal performance of AC microgrid. Therefore, this paper proposes optimal operation of AC microgrid in the presence of plug-in electric vehicles under demand side management. The proposed model describes optimal operation of microgrid including the exchange power with the upstream grid, the production of DG units including wind turbines, battery storage, diesel generators, charging and discharging of electric vehicles and the manner of participation of large industrial consumers and aggregators of small consumers in demand side management that minimize the operation cost of microgrid. The proposed formulation is considered the mathematical model of various energy sources in a microgrid and the AC load flow constraints and the bus voltage and feeder current limitations has been considered.In the proposed model, charge and discharge management of plug-in electric vehicles and demand side management are simultaneously proposed to reduce operation cost of AC microgrid subject to technical and economic constraints. A 33-bus microgrid is used as test system in order to investigate effects of plug-in electric vehicles and demand side management on optimal operation of AC microgrid. The proposed model is formulated via mixed-integer non-linear programming which is solved using CPLEX solver under GAMS optimization software.

This paper presents a novel approach for optimal planning of the multi microgrids (MMGs) under uncertainties in load and renewable power generation. The proposed approach is applied for optimally determining the size, type, number, and site of renewable and dispatchable distribution generation (DG) with optimal allocation of switch for clustering distribution systems into a number of microgrids to economical and reliable structure. The optimization aim is to minimize the totally microgrid planning cost including investment cost, operation and maintenance cost, power losses cost, the pollutants emission cost and the cost of energy not supply (ENS). The system uncertainties are considered using a set of scenarios and a scenario reduction method is applied to enhance a tradeoff between the accuracy of the solution and the computational burden. Cuckoo optimization algorithm (COA) is implemented to minimize the objective function as an optimization algorithm. Also, the effect of optimization coefficients on the planning problem and the robustness of the proposed algorithm are investigated using sensitivity analysis. The efficiency of the proposed method are validated on 33-bus distribution system and the obtained results show that the proposed framework can be considered as an efficient tool for planning of multi microgrids under uncertainty.

In this paper, a hybrid algorithm has been presented for energy management in multi-microgrid systems considering security constraints. The energy management system is responsible for accurately dispatching the amount of required energy among multiple microgrids and units in a muti-microgerid system. The energy management procedure is done hierarchically, in a way that each microgrid performs a local energy management, which determines surplus and shortage amounts of energy at each time interval. Accordingly, Independent System Operator (ISO), schedules the units. Each microgrid, contains a wind turbine (WT) and Photovoltaic (PV) panels as renewable and nondispatchable resources and a diesel generator as a dispatchable energy resource. Also an energy storage system (ESS) is responsible for balancing the produced and consumed energy. A demand response program (DRP) is performed through energy management system for the objective of MG load management and flattening the load curve and reducing the operation cost. Finally, the proposed approach is tested on IEEE 33-bus distribution test system, in presence of microgrids, using GAMS and MATLAB softwares. The simulation results would be presented in the final section to show the effectiveness of the proposed algorithm.

Microgrid (MG) supplied its local load with distributed energy resources at the low voltage system in distribution networks. Microgrid can be used in parts that are not allowed access to the electricity network with low investment cost. The used islanding MG in this research includes wind turbine and photovoltaic systems as renewable energy sources and hydrogen storage system (HSS). This paper proposes a new energy management strategy (EMS) for MG in the presence of the HSS considering the power uncertainties of renewable energy sources. The objective of proposed EMS is to minimize the operating costs of batteries, HSS and the costs associated with excess and undelivered energy considering the supplied load constraints. The considered technical constraints in this paper contain renewable energy sources limits and battery and HSS constraints. HSS includes electrolyzer (EL), hydrogen tanks and fuel cell (FC). Demand response program (DRP) is used to flat the load curve and optimal operation of MG. The proposed model on a MG is been implemented in GAMS software. The simulation results show that the operation cost of MG reduced by using of HSS and DRP.

Microgrid (MG) is one of the new topics in distribution networks in which electrical energy is locally supplied with distributed energy resources at the low voltage system. In this paper, islanding MG includes wind turbine and photovoltaic systems as renewable energy sources. Moreover, due to unavailability of power grid, the MG benefits energy storage batteries. Therefore, this paper proposes a new energy management strategy (EMS) for MG in islanding mode using the hydrogen storage system (HSS) which includes electrolyzer, hydrogen tanks and fuel cell (FC) in the presence of demand response program (DRP). The proposed EMS is based on the optimal operation of energy sources of MG with the objective of minimizing operating costs of batteries, HSS and the costs associated with excess and undelivered energy. Also, the uncertainties of demand, produced power of wind turbine and photovoltaic systems are modeled with scenario approach. Moreover, DRP is proposed with the objective of MG load management and flattening the load curve and thus reducing the operation cost. The proposed model is been simulated on a MG using GAMS software and the results show that by using HSS and DRP, the operation cost of MG in islanding mode is reduced.

Regarding the vast extension of information technology, communication systems and electronic instrumentation, the employment of phasor measurement units (PMUs) has been proposed for power system observability and wide-area protection. Nevertheless, the construction of communication channels and installation of PMU equipment are highly expensive and require optimizations. In this paper, first the constraints are proposed for the optimal PMU placement problem considering fault state observability of power system in presence of zero bus injection, and afterwards the mathematical formulation is presented. For more realistic modeling of power network, line outages have been considered. Finally, the proposed method is implemented on standard IEEE 9, 14, and 30 bus networks, and the enhanced results are represented.