جستجوی مقالات مرتبط با کلیدواژه « مدیریت انرژی » در نشریات گروه « برق »

This article introduces a two-stage linear model designed for the coordination of networked microgrids, aimed at optimizing energy management and enhancing profitability through proactive and corrective strategies. Initially, the first stage involves day-ahead hourly planning for microgrids, executed in a deterministic environment without accounting for uncertainties. Subsequently, the second stage addresses these uncertainties in real-time network operation through a stochastic programming approach. The model's objective function quantifies and incorporates the variations resulting from both the proactive and corrective phases. To handle uncertainties in wind and solar energy production as well as load demand, probability distribution functions derived from Monte Carlo simulations are utilized. From these, representative scenarios are chosen using a scenario reduction technique. Specifically, the K-means algorithm is employed for scenario clustering, with the Davies-Bouldin (DB) index facilitating automatic clustering. Additionally, load management is conducted via a demand response program. The proposed model stipulates that, within microgrids, only non-critical load levels can be modulated based on the network's economic benefit. This optimization model, formulated as mixed integer programming, is simulated and resolved in the GAMS software environment. The primary goal of this two-stage model is to achieve optimal energy management by balancing economic efficiency with robust network performance. The results obtained validate the model's effectiveness.

The issue of energy supply on the one hand and the environmental problems caused by the consumption of fossil fuels, on the other hand, have prompted researchers to turn to methods of reducing energy consumption as well as the use of renewable energy sources and hybrid vehicles. The time of several distributed generation units is optimal, but due to the uncertainties in phenomena such as solar radiation, to more accurately predict how the microgrid and its devices will work in the future to make appropriate decisions, a mechanism for processing and managing relevant data is. The answer to all these questions requires familiarity with a new concept called the "energy hub". Due to the wide scope of control of energy hub systems, in this article, while examining the definitions and concepts related to these systems, we have tried to design the control system so that the system is resistant to uncertainty and perturbation. The proposed method uses nonlinear predictive controllers. It is durable. Case study and simulation results in MATLAB software show well that the output variables of the modelled energy hub system have been able to be stable at a suitable time after input.

This paper presents the optimal planning of renewable hybrid systems including wind turbines and bio-waste energy units according to hydrogen and thermal storages considering feeding of electrical and thermal energies. Bio-waste unit is based on the operation of the combined power and heat system, which produces electrical and thermal energy at the same time. Hydrogen storage is hybrid of an electrolyze, hydrogen tank, and fuel cell. The proposed scheme minimizes the total annual investment and maintenance costs. It is subject to the operation model of the mentioned elements. In the operation model of sources and storage, renewable sources supply loads of energy, then storage uses to cover the gap between the load and renewable power profiles. This paper uses the hybrid solver of the Gray wolf optimizer and the sine-cosine algorithm to obtain a reliable optimal solution with a low standard deviation in the final response. Finally, based on numerical results according to Espoo in Finland data, the proposed scheme's capability is confirmed in the Economic extraction of a 100% renewable island hybrid system suitable for simultaneous supply of electrical and thermal energy.

In the upcoming research, the issue of consumption and energy management in residential buildings has been discussed using the energy hub system. The purpose of using energy hub is the simultaneous and optimal use of several energy carriers for the appropriate, reliable and economical supply of consumer needs while complying with the conditions of satisfaction and comfort of the residents. The optimization problem in this study is formulated as mixed integer linear programming. In order to solve the optimization problem of the optimization problem, Gam’s software has been used. During the implementation of problem solving, the effect of three conventional pricing models, including hourly, time of use and instant pricing, was investigated in Iran, and part of the results are presented in the form of tables and graphs. In all cases, the possibility of selling jointly produced electricity to the grid is included; Therefore, it is possible to pay more attention to the energy hub technology even in the climatic conditions and pricing policies of Iran, and by creating a suitable investment environment, especially in large residential complexes and building blocks, to increase security. Energy, reducing the consumption of fossil fuels and expanding the use of various energy sources in different regions helped.

Due to importance of pigging operations for purposes such as monitoring-cleaning, which leads to an increase in the service life of pipeline networks, management, and optimization of energy consumption in oil and gas industries, providing accurate numerical models is a research need that has been very vital. Considering advantages of meshless methods, for the first time in this research a model is presented for evaluating the flow around the pig using the smooth particle hydrodynamics (SPH) method and the standard k-ε model to simulate the turbulence of the flow. Besides, the performance of the model based on the experimental study has been evaluated and validated. The results showed that the average error rate of the SPH model compared to the laboratory model was less than 5%, which indicated the research model's high accuracy and acceptable performance. After validating the performance of the research model, the simulation of the flow around the stationary and mobile pig was modeled, and the results were compared and evaluated with the existing numerical results. In addition, by using a meta-heuristic algorithm of gray wolves optimization (GWO), studies wereconducted on the relative diameter parameter of the bypass pig to achieve optimal values of this parameter. The results of the optimization model showed that the optimal relative diameter of the bypass pig was equal to d⁄D=0.418. The results of this research showed that the presented model had an acceptable accuracy in modeling the flow around the bypass pig in the pipe, and it could also be used as a reference model based on the SPH method for modeling the flow around the bypass pig.

This article presents a new energy management strategy (EMS) for optimal power allocation in the battery/supercapacitor hybrid energy storage (HESS) in DC microgrid applications. The proposed system is composed of a semiactive structure where the supercapacitor is directly connected to DC bus. In this structure, since the main purpose of the HESS is to maintain the DC bus voltage at the desired value, controlling the supercapacitor becomes more important. While, in the semi-active structure, there is no control on the supercapacitor. In this paper, by considering the supercapacitor current as a cost function in the optimization problem, this challenge has been solved. Also, in the case of microgrid excess power mode, a new cost function has been considered to charge the battery with a constant current to reduce the charging time and improve its lifespan. Another objective is to increase battery life by responding the supercapacitor to the sudden power changes and drawing a smooth current from the battery. In order to online determination of the optimal global solution, this multi-objective problem has been converted into a single-objective problem by use of the weighted method and then solved using KKT conditions. Therefore, real-time implementation is the main advantage of the proposed method. Finally, using simulation, the performance of the proposed method is compared with an adaptive cutoff frequency filter-based method and fuzzy logic method, in three 24 seconds different scenarios, in terms of the DC bus voltage regulation, the battery peak current, and the battery state of charge (SoC).

A complete understanding of the limits, barriers, and equipment available for the use of national energy resources is essential. This will increase the use of existing regional energy potential and pave the way for sustainable development. In this study, the Green Cottage power management system from a renewable energy source was designed and evaluated using a decision-making algorithm. Thirteen scenarios were extracted to Zero-energy building. The results show: If the penetration of renewable energy is 24% with an average daily fossil fuel consumption of 1.11 liters per year, the energy produced by the Hybrid renewable energy systems (HRES) is equal to 1697 kWh / yr and the net present value (NPV) is $ 5553.68 and the Internal rate of return (IRR) equals 21.49% with a payback period (PP) of 15.71 years. With the increase of renewable energy penetration to 54%, fossil fuel consumption became 0.694 liters and the annual production energy was equal to 1652 kWh / yr and the NPV was 19.5% with a PP of 17.61 years. Zero-energy building Energy Management with 100% renewable energy penetration, 1933 kWh / yr per year without emissions of environmental pollutants, and the NPV equal to -372.09 dollars. From the point of view of energy policy, if the feed-in tariff of renewable energy increases to more than $ 0.06, the implementation of this scenario will be economic.

In order to reduce the cost of electric power generation and also reduce greenhouse gas emissions in ships with electric propulsion system, renewable energy resources and energy storage systems are used along with thermal units. Therefore, in this paper, a stochastic mixed integer linear model has been suggested for optimal management of electrical energy of a ship with electric propulsion system, energy storage, heat generators and renewable solar resources with the aim of minimizing the cost of electricity production and determining the optimal ship speed. In this paper, the Monte Carlo simulation method is used to model the uncertainty in predicting the solar power and the ship's electric load. The proposed model is implemented and analyzed in GAMS optimization software. The simulation results show the efficiency of the proposed model and the introduced energy management strategy.

Reforming the consumption pattern and correcting extravagant behavior has been the concern of the Supreme Leader for about two decades, who warned about this issue many times and finally proposed 2008 as the year of reforming the consumption pattern. One of the issues that different countries are facing. It is an energy crisis. This crisis has prompted countries and organizations to have a different approach to this issue. In the meantime, many scientific and managerial solutions have been put into play. Among the factors that increase energy consumption is the lack of energy management. Based on this, energy management information systems have been used with hope and in this study, by reviewing the existing literature and considering Maheshshan Pisi's research group examines the information wires of energy management and information technologies in energy management, reducing the amount of energy consumption and also identifying the success factors of these systems. By using the results of this article, a new view can be obtained regarding the nature of information systems in energy management and saving, and a little new in the design of forward-looking strategies to create new competitive advantages by using the implementation and implementation of these success factors. Harvest systems.

Network-on-chip provides an efficient communication platform for Systems-on-chip. The static power consumption is an important issue in these networks. Switching the power supply on virtual channels during idle time is a common method for reducing the network power consumption. The traffic load at the network level and non-continuous idle period of virtual channel have caused the sources to be switched on and off continuously, which leads to increase in power consumption and other overheads. This will be more important, in partially connected 3D chip networks in which a limited number of vertical connections has been used. In this paper, a routing algorithm is proposed who employs an appropriate policy for packet distribution, and reduces the load distribution in the network and creates a continuous idle time for the resources, result in suitable power management in the network. In this routing scheme the network is divided to north and south region and some restriction applied in usage of elevators in each region and try to increase the utilization of the used resources as well as the ideal time of low traffic paths. The simulation results, derived by BookSim, show the proposed method improve the network power consumption by 18% to 30% comparing previous algorithms, and the network delay has been reduced by 32%.

In this paper, a new energy management strategy is presented by using shunt active power filter (SAPF) in a multi-agent structure. This strategy is applied to a micro-grid connected to the grid and includes the problem of harmonic compensation. By examining the advantages and disadvantages of shunt active power filters and passive filters, as well as their efficiency in the multi-agent structure for power micro-grids, the reason for using shunt active power filters in the proposed method has been determined. Also, the performance of these filters for compensating current harmonics has been compared by examining the FFT results. In the used micro-grid, wind turbine generator and solar cell generator are used as renewable energy sources (RES) and two fuel cells are used to compensate for sudden and unplanned changes in the production power of these two generators. The energy management unit manages the active and inactive state of the two fuel cells according to the production power and consumption power of the micro-grid in such a way that the power exchanged between the micro-grid and the main grid is limited within an acceptable range. The simulation results show that the proposed method using local continuous controllers (in each agent) and central discrete controller (energy management system) has been able to perform well and while providing the required power of the micro-grid, at the same time, it performs the current harmonics compensation issue correctly.

In this paper, we study the microgrid network including solar energy, battery and supercapacitor using fuzzy controller. Due to the voltage changes in the DC bus, it is necessary to adjust the solar cell and the battery using the control method and converter. Also, with the help of batteries and supercapacitors, this equipment is used when there is a need for more power in the load. Supercapacitors are used for instantaneous times and batteries for longer periods of time to power output loads. A fuzzy control system is a control system based on the fuzzy-mathematical logic of a system that analyzes analog input values in terms of the logical variables they contain and is used in several parts of the system to improve performance. The simulation is performed in MATLAB / Simulink software and the output results confirm the accuracy and validity of the system used.

In recent years, attention to renewable energy and distributed generation has increased due to increased energy demand and environmental pollution. To this end, in the new power grid structure, consumers can also play a producer role. Considering that the number of prosumers in this structure is much more than traditional power networks, the need for a secure, transparent, fast, scalable platform for energy exchanges has greatly increased. Blockchain technology can provide such a platform due to its unique properties. Although there are many blockchain-based platforms in different countries in enregy field, but in Iran there is no such platform. Therefore, the main purpose of this paper is to design and implement a local pilot platform for peer-to-peer blockchain-based energy exchange, taking into account the specific conditions of Iran's electricity grid. The macro platform architecture is designed based on the concept of Minimum Viable Product (MVP) considering functional and non-functional requirements in the form of unified modeling language (UML) diagrams. The proposed platform pilot has been implemented in the form of 4 main elements including smart contract, user interface, blockchain platform, and blockchain and non-blockchain databases and has been evaluated and tested using different scenarios. These tests mainly include the unit test and the integrity test, which were successfully performed on the platform. This platform has been designed and implemented for the first time in Iran in accordance with the Ethereum protocol and based on microservice architecture. In addition to the ability to integrate with Ethereum-based systems, this platform is scalable due to its modular design.

In this paper, a comprehensive energy management model is proposed in order to the operation of a ‎modified 33-radial bus distribution system, in the presence of smart homes. In the proposed model, ‎smart home customers are able to participate in a demand response (DR) program and their comfort ‎index is also considered as the main constraint. The model also considers uncertainties related to the ‎load demand, the generation of renewable energy resources and electricity price. The Monte Carlo ‎simulation method and the ScenRed tool are utilized to generate and reduce the scenarios, respectively. ‎In order to mimic the actual operating conditions, in the simulation, the seasonal variations of load ‎and generation are considered and the operation problem is solved for four seasons.‎‏ ‏A linear AC ‎power flow is also used in the model. Finally, the problem is modeled as a mixed-integer linear ‎programming (MILP) problem and solved by the CPLEX solver in GAMS software. The simulation ‎results demonstrate that the model proposed in this study is a comprehensive framework for the ‎operation of distribution systems in the presence of smart homes, which not only reduces operating ‎costs but also increases the consumers’ comfort index.‎

Applying a hierarchical routing approach based on clustering technique and mobile sink has a great impact on reducing energy consumption in WSN. Two important issues in designing such an approach are cluster head selection and optimal allocation of mobile sinks to critical regions (i.e., regions those have low remaining energy and thus, high risk of energy hole problem). The limited number of mobile sinks should be utilized due to a high cost. Therefore, allocating the limited number of mobile sinks to the high amount of requests received from the critical regions is categorized as a NP-hard problem. Most of the previous studies address this problem by using heuristic methods which are carried out by sensor nodes. However, this type of solutions cannot be implemented in real WSN due to the sensors’ current technology and their limited processing capability. In other words, these are just theoretical solutions. Consequently, a semi-central genetic algorithm based method using mobile sink and clustering technique is proposed in order to find a trade-off between reduction of computation load on the sensors and increasing accuracy. In our method, lightweight computations are separated from heavyweight computations. While, the former computations are carried out by sensors, the latter are carried out by base station. Following activities are done by the authors: 1) cluster head selection by using effective environmental parameters and defining cost function of cluster membership, 2) mathematical modeling of a region’s chance to achieve mobile sink, and 3) designing a fitness function to evaluate the fitness of each allocation of mobile sinks to the critical regions in genetic algorithm. Furthermore, in our activities minimizing the number and length of messages are focused. In summary, the main distinguishing feature of the proposed method is that it can be implemented in real WSN (due to separation of lightweight computations from heavyweight computations) with respect to early mentioned objectives. The simulation results show the better performance of the proposed method compared to comparison bases.

Today, the use of distributed generation resources connected to the network has remarkable growth therefore network-connected to the converters must be able to provide services beyond the injection of power into network, including maintaining network stability. In this paper the control and management of energy for battery wind, photovoltaic and diesel connected to a three-phase network by activating the current limitation under unbalanced fault has been introduced. In this method injected currents are limited to a certain amount along the faults Also, the operation mode without tracking the maximum power point for the converter is included. This state is activated during severe faults, when the converter cannot control Maximum power of the system. Therefore, in a microgrid with, the operation of a fuzzy logic-based controller the transformation operation of DC to DC converter control is performed sparsely by two-way battery and distributed generation resources management. Also proportional resonance controller is used due to its proper performance. In fact, with the use of reference current generation, sinusoidal current with a total harmonic distortion (THD) value of less than 5% is injected. The results show that the control strategy along with energy management with multiple energy generation resources is able to limit and maintain DC link voltage within an acceptable range in addition to The existence of an asymmetric fault. Therefore, the fault crossing operation has been performed correctly without the operation of the protection relays and secondly in comparison with microgridsolely with the presence of one photovoltaic production source the process of injecting active and reactive power in the upstream network is more appropriate.

Sustainable energy generation, transmission, consumption, and storage is one of the most important concerns in modern world, which includes technical, economic, political, social and environmental aspects. The right approach to solve this challenging and multifaceted problem requires interdisciplinary fashions to power and energy systems that bridge the gap between all the stakeholders (i.e., researchers, engineers, politicians, citizens, industry owners, and others). In such interdisciplinary study, the new Energy Informatics field plays an important role in which various disciplines generally address the techno-economic challenges of energy and power systems throughout the whole chain from production to consumption and sale/purchase. The purpose of this article is to draw an overview and, of course, an accurate view of the field of Energy Informatics by addressing the educational/research opportunities/challenges and considering the current consequences and future directions of industrial innovations related to this innovative field. This study, beyond purely scientific perspectives and by including reflections with applied and industrial approaches, facilitates data analysis to realize education and research policy for this modern area. Initially, recommendations for the content of the Energy Informatics introductory course were drawn up and discussed to educate the new generation of professionals who must meet the interdisciplinary challenges of new and integrated energy systems of the future. Then, a preliminary proposal is made for the establishment of the National Energy Informatics Institute, in which the necessity and structure of such a center is discussed in order to have a precise policy making; preparing to enter the future world of energy.