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نتیجه جستجو - سیستم مدیریت انرژی

تعداد مقالات یافته شده: 53
ردیف عنوان نوع
1 A review of hierarchical control for building microgrids
مروری بر کنترل سلسله مراتبی برای میکرو گریدهای ساختمان-2020
Building microgrids have emerged as an advantageous alternative for tackling environmental issues while enhancing the electricity distribution system. However, uncertainties in power generation, electricity prices and power consumption, along with stringent requirements concerning power quality restrain the wider development of building microgrids. This is due to the complexity of designing a reliable and robust energy management system. Within this context, hierarchical control has proved suitable for handling different requirements simultaneously so that it can satisfactorily adapt to building environments. In this paper, a comprehensive literature review of the main hierarchical control algorithms for building microgrids is discussed and compared, emphasising their most important strengths and weaknesses. Accordingly, a detailed explanation of the primary, secondary and tertiary levels is presented, highlighting the role of each control layer in adapting building microgrids to current and future electrical grid structures. Finally, some insights for forthcoming building prosumers are outlined, identifying certain barriers when dealing with building microgrid communities.
Index Terms: Electricity market | Energy management system | Optimisation algorithms | Renewable energy source | Prosumer
مقاله انگلیسی
2 A new stochastic gain adaptive energy management system for smart microgrids considering frequency responsive loads
یک دستاورد تصادفی جدید سیستم مدیریت انرژی تطبیقی ​​برای میکروگریدهای هوشمند با توجه به بارهای پاسخگو فرکانس-2020
Islanded microgrids as flexible, adaptive and sustainable smart cells of distribution power systems should be operated in accordance to both techno-economic purposes. Motivated by this need, the microgrid operators are in charge to elevate the active accommodation of both demand-side and supply-side distributed energy resources. To that end, in this paper, a new flexible frequency dependent energy management system is proposed through which distributed generators have time varying droop controllers with a gain-adaptive strategy. Besides to cope economically with uncertainty arise frequency excursions, a new, comfort-aware and versatile frequency dependent demand response program is mathematically formulated and conducted to the energy management system. It is aimed to co-optimize the microgrid energy resources such a way the day-ahead operational costs are managed subject to a secure frequency control portfolio. The presented model is solved using a two-stage stochastic programming and by a tractable efficient mixed integer linear programming approach. The simulation results are derived in 24-h scheduling time horizon and implemented on a typical test microgrid. The effectiveness of the proposed hourly gain assignment and frequency responsive load management program has been verified thoroughly by analyzing the results.
Keywords: Hierarchical control structure | Islanded microgrids | Droop gain scheduling | Frequency responsive loads | Two-stage stochastic optimization
مقاله انگلیسی
3 Home energy management system based on task classification and the resident’s requirements
سیستم مدیریت انرژی خانگی بر اساس طبقه بندی وظیفه و الزامات ساکنان-2020
In this paper, an approach for home energy management system is introduced that is based on task classification. The problem is to find the best task activation plan regarding the resident’s requirements and appliances constraints, considering time of use pricing. We show that to have a best task activation plan it is necessary to specify four specific values for each task. In this regard, a quadratic utility function is derived based on the law of diminishing marginal utility in microeconomic. With the parameters such as sensitivity index and monetary equivalent value, each task’s utility function can be configured in accordance to the resident’s personal preferences. In this model, the concept of tasks interaction are also taken into account, for the first time. The problem is transformed to a mixed integer nonlinear programming problem, so that the available commercial solvers can successfully solve it in an acceptable solving time. The outputs of numerical examples show that they are reasonable and can be considered as optimal or near optimal results. The results indicate that the less sensitive the resident is to changing his/her desire task parameters, the more profit he/she will get. It is also shown that by increasing the monetary equivalent value, the task activation is shifted toward the times that are more preferable or has more favorite environment conditions. These results as well as the acceptable solving times, show that the proposed approach can be a promising model for home energy management systems in the future smart homes.
Keywords: Home Energy Management System (HEMS) | Load scheduling | Smart grid | Task classification | Utility function | Time preference effect
مقاله انگلیسی
4 Multi-objective robust energy management for all-electric shipboard microgrid under uncertain wind and wave
مدیریت انرژی چند منظوره قدرتمند برای ریز شبکه برد حامل تمام برقی تحت باد و موج نامشخص-2020
An all-electric ship (AES) uses diesel generators and energy storage system (ESS) to meet both propulsion and service loads. Thus, it can be viewed as a mobile microgrid. During the operation of an AES, significant uncertainties such as water wave and wind introduce considerable speed loss, which may lead to severe voyage delays. To fully address this issue, a new robust energy management model is proposed to coordinately schedule an AES’s power generation and voyage considering the uncertain wave and wind. Two objectives are minimized simultaneously: the fuel consumption (FC) and energy efficiency operational indicator (EEOI). The problem is formulated as a bi-level robust optimization model after certain constraint decomposition. Normal boundary intersection method is utilized to solve this multi-objective programming. Compared with existing joint scheduling methods, the proposed method can fully guarantee the on-time rates of AES in various uncertain scenarios and providing high-quality Pareto solutions.
Keywords: All-electric ship | Mobile microgrid | Robustness | Energy management system | Joint generation and voyage scheduling | Uncertain wave and wind
مقاله انگلیسی
5 Machine to machine performance evaluation of grid-integrated electric vehicles by using various scheduling algorithms
ارزیابی عملکرد ماشین به ماشین از وسایل نقلیه برقی شبکه یکپارچه با استفاده از الگوریتم های مختلف برنامه ریزی-2020
For smart cities, electric vehicles (EVs) are promisingly considered as a striving industry due to its pollution-less behaviours and easy-to-maintain characteristics. A seamless management system is necessary to manage the energy between EV and various parties participating in the grid operation. To facilitate the energy system in a distributed and coordinated way, a machine-to-machine (M2M) system can be considered as the key component in future intelligent transportation systems. Due to the ubiquitous range and data speed, a fourth-generation (4G) cellular-based long-term evaluation (LTE) system inspires us to select it as a potential carrier for M2M communication. However, various simulation and analytical modelling end up with the conclusion that the maximum 250 EVs can be connected under an LTE base station. These limitations or scalability limits may result in a terrible mix-up in future smart cities for over dense roads. In this paper, we measured various M2M quality of services performance for exceeding the number of EVs by using three popular algorithms (proportional fair scheduling, modified largest weighted delay first scheduling and exponential scheduling). The result shows that the proportional fair scheduler has the highest packet loss ratio (PLR) and delay time as compared to other two schedulers.
Keywords: DLS | Electric vehicle | Energy management system | EXP | M2M communication | M-LWDF | PF | PLR
مقاله انگلیسی
6 Optimization & validation of Intelligent Energy Management System for pseudo dynamic predictive regulation of plug-in hybrid electric vehicle as donor clients
بهینه سازی و اعتبار سنجی سیستم مدیریت انرژی هوشمند برای تنظیم پیش بینی شبه دینامیکی پلاگین در خودروهای برقی هیبریدی به عنوان مشتری دهنده-2020
In developing countries, policies for discarding the existing Internal Combustion (IC) Engine vehicles for faster adoption of Electric Vehicles’ not only creates burden on the existing power grid but also is impractical. The conversion of Conventional IC Engine based Online Taxis or public transport vehicles into Plug-in Hybrid Electric Vehicles donor clients, to participate in Vehicle to Grid & Vehicle to Vehicle power transfer model, is the solution. These vehicles would not only have emissions within compliance standards but would also reduces the load on the power grid meanwhile making an income through power transfer. The Intelligent Energy Management System (IEMS) developed makes use of a Non Dominated Sorting Genetic Algorithm (NSGA-II) based Pseudo dynamic predictive regulation approach on the powertrain to optimize the emissions, fuel cost and traction battery SoC. If the vehicle intends to participate in power transfer, the IEMS would predetermine the amount of SoC that would be used for an upcoming journey using Global Positioning System(GPS) data interconnected with a server unit which enables the IEMS to optimize the operating conditions of the vehicle. The modelled IEMS performance is tested for a given driving cycle with varying traffic levels on a virtual simulation environment using the IPG CarMaker software. A prototype with a 150 cc, 7.5 kW IC engine integrated to a 3 kW BLDC traction motor is developed and the response to the predictive model is evaluated and found to provide 27.66%, 13.73% and 7.72% equivalent energy to micro grid for low, medium and high criticality conditions for the user.
Keywords: Vehicle to grid | NSGA-II optimization | State of charge | Emission | GPS | Real-time validation
مقاله انگلیسی
7 Smart charging of electric vehicles considering photovoltaic power production and electricity consumption: A review
شارژ هوشمند وسایل نقلیه برقی با توجه به تولید انرژی فتوولتائیک و مصرف برق: بررسی-2020
Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potentially impact the overall energy performance of the buildings. Thus, a high penetration of both PV and EVs poses new challenges. Understanding of the synergies between PV, EVs and existing electricity consumption is therefore required. Recent research has shown that smart charging of EVs could improve the synergy between PV, EVs and electricity consumption, leading to both technical and economic advantages. Considering the growing interest in this field, this review paper summarizes state-of-the-art studies of smart charging considering PV power production and electricity consumption. The main aspects of smart charging reviewed are objectives, configurations, algorithms and mathematical models. Various charging objectives, such as increasing PV utilization and reducing peak loads and charging cost, are reviewed in this paper. The different charging control configurations, i.e., centralized and distributed, along with various spatial configurations, e.g., houses and workplaces, are also discussed. After that, the commonly employed optimization techniques and rulebased algorithms for smart charging are reviewed. Further research should focus on finding optimal trade-offs between simplicity and performance of smart charging schemes in terms of control configuration, charging algorithms, as well as the inclusion of PV power and load forecast in order to make the schemes suitable for practical implementations.
Keywords: Photovoltaics | Electric vehicles | Electricity consumption | Smart charging | Energy management system | Charging optimization
مقاله انگلیسی
8 Energy management system for hybrid PV-wind-battery microgrid using convex programming, model predictive and rolling horizon predictive control with experimental validation
سیستم مدیریت انرژی برای ریز شبکه هیبریدی PV-باد باتری با استفاده از برنامه نویسی محدب ، مدل پیش بینی و کنترل پیش بینی افق نورد با اعتبارسنجی آزمایشی-2020
The integration of energy storage technologies with renewable energy systems can significantly reduce the operating costs for microgrids (MG) in future electricity networks. This paper presents a novel energy management system (EMS) which can minimize the daily operating cost of a MG and maximize the self-consumption of the RES by determining the best setting for a central battery energy storage system (BESS) based on a defined cost function. This EMS has a two-layer structure. In the upper layer, a Convex Optimization Technique is used to solve the optimization problem and to determine the reference values for the power that should be drawn by the MG from the main grid using a 15 min sample time. The reference values are then fed to a lower control layer, which uses a 1 min sample time, to determine the settings for the BESS which then ensures that the MG accurately follows these references. This lower control layer uses a Rolling Horizon Predictive Controller and Model Predictive Controllers to achieve its target. Experimental studies using a laboratory-based MG are implemented to demonstrate the capability of the proposed EMS.
Keywords: Microgrid Energy Management | Battery Energy Storage System | Real-Time Battery Control | Convex Optimization | Model Predictive Control | Rolling Horizon Predictive Controller | Adaptive Autoregression Algorithm
مقاله انگلیسی
9 Energy saving based lighting system optimization and smart control solutions for rail transportation: Evidence from China
بهینه سازی سیستم روشنایی مبتنی بر صرفه جویی در انرژی و راه حل های کنترل هوشمند برای حمل و نقل ریلی: شواهدی از چین-2020
As the natural resources are becoming exhausted, energy consumption by metro systems dominates internal transportation resources in urban areas. The comprehensive exploration of energy improvements in lighting system energy is necessary. To evaluate the energy-saving potential and identify the efficiency improvement opportunities for lighting operations in metro systems, an intelligent energy management system for metro stations is examined through a case study in Nanchang city of China. First, the study explores the main factors influencing the lighting energy consumption of metro systems and analyses the lighting distribution in different station regions. Second, DIALux software is employed to optimize and monitor the best illuminating effect for hall lighting in the selected station. Third, an intelligent model is proposed for the lighting system based on the energy-saving scheme and solution using BECH energy analysis software combined with DIALux software. A thermal model is proposed to verify the energy and load performances. Results show that (1) the proper layout by means of DIALux software, can not only meet the functional demands of lighting but also reduce energy consumption; (2) intelligent lighting control system can improve the lighting energy-saving design, and the lighting control framework is capable of refined control; and (3) based on the performance analyses, the solution with the adopted DALI digital light adjustment is helpful for increasing passengers comfort and realizing the goals reduction.The novelty is to integrate the lighting energy saving solution with software within an intelligent management and verified its valuable application, it is practical for construction emission control
Keywords: Lighting system | Influence factors | Artificial intelligent control technology | Energy management system
مقاله انگلیسی
10 Intensive quadratic programming approach for home energy management systems with power utility requirements
رویکرد برنامه نویسی درجه دوم فشرده برای سیستم های مدیریت انرژی خانه با نیازهای ابزار برق-2020
This paper proposes a model of a home energy management system (HEMS) to meet utility requirements while maximizing home profit. It contributes to intensify the flattening effects on the exchanging power pattern with a constraint of a fair profit reduction among households. The proposed method first uses a normal mixed-integer linear programming approach to find out the highest profit a household can get under a condition of a generous power limitation. It is highly possible that the resulted power aggregated from numerous homes may negatively affect power system operation such as violating voltage limits and overloading transformers. Based on that highest profit, the utility proposes the same percentage number of profit reduction for all households. Then, each HEMS performs an intensive mixed-integer quadratic programming optimization to flatten the selling and buying profiles whilst constraining the home profit reduction to the percentage set by the utility. A simulation shows that the peak power demand at the substation transformer would reduce about 44% if each household suffered a reduction of just 10% of the highest possible home profit. Since the flattening effects are improved if increasing the home profit reduction, our method is a basis for the utility to determine a compensation or alternative incentives to shave the peak-load and flatten the demand curve.
Keywords: Home Energy Management System | Peak-load shaving | Smart household | Smart home | Rooftop solar
مقاله انگلیسی
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