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ردیف | عنوان | نوع |
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1 |
Intelligent energy management in off-grid smart buildings with energy interaction
مدیریت انرژی هوشمند در ساختمانهای هوشمند خارج از شبکه با تعامل انرژی-2020 The energy interaction between smart homes can be a solution for developing renewable energy systems
in residential sections and optimal energy consumption in homes. The main objectives of such energy
interactions are to increase consumer participation in energy management‘ boost economic efficiency‘
increase the user’s satisfaction by choosing between electricity sellers and buyers‘ and reduce the
electricity purchased from the grid especially at peak hours. Thus, the innovations of this study includes
defining an energy exchange method between smart buildings in an off-grid mode considering
renewable energy systems, considering both thermal and electrical equilibrium and studying the
lightning loads. it is assumed, here, that smart homes are off-grid‘ and the critical loads are supplied by
the energy transfer between the homes using mixed integer linear programming. A compromise between
the cost and time interval for using home appliances is considered to provide consumer’s comfort.
An objective function is introduced considering programmable and non-programmable loads‘ thermal
and electrical storages and lighting loads aiming to optimize the cost of energy between different smart
buildings. Based on the method, which is tested in two different cases not only does the total cost of the
smart buildings decrease but also the cost is reduced significantly when lightning loads are managed. Keywords: Energy management | Smart homes | Smart microgrid | Energy storage system | Wind turbine |
مقاله انگلیسی |
2 |
Techno-economic evaluation of PV based institutional smart microgrid under energy pricing dynamics
ارزیابی فنی و اقتصادی میکروگرید هوشمند نهادی مبتنی بر PV تحت پویایی قیمت گذاری انرژی-2020 The solar photovoltaic (PV) system with battery energy storage have a lot of potential to provide reliable
and cost-effective electricity and to contribute in micro-grid operation. However, the operational performance
of such type of micro-grid system depends on many factors (e.g. techno-economic sizing,
energy management among the sources, market energy prices dynamics, energy dispatch strategies,
etc.). In this paper, a typical Indian institutional energy system has considered for techno-economic
performance evaluation for operating as a smart micro-grid under market energy pricing dynamics.
The institutional energy system has integrated PV, battery storage and DG for operating as a smart microgrid.
An operational energy dispatch strategy for micro-grid has proposed and evaluated for maximizing
the local energy resources utilization with contemplation of peak demand and grid outage conditions
under market energy pricing dynamics. With techno-economic sizing of PV, battery and DG of considered
system; the peak demand has reduced by 10%, DG contribution by 92% and annual energy savings
by 45% compare to operation of base system. With proposed energy management strategy, the annual
battery energy throughput has increased from 0.4% to 10%, and the DG’s contribution has decreased from
7% to 5% with 10% reduction in levelized cost of energy (CoE) compare to case with techno-economic
sizing of PV, battery and DG for considered system. With inclusion of electrical energy pricing dynamics
scenario, it has observed that the CoE has increased by 89% with change in time-of-use (ToU)
tariff from 100% to 200% and considering energy-selling price to the grid at 100%. However, 8% reduction
in the CoE has observed, when the energy-selling price to grid has increased from 100% to 200% at ToU of
100%. The results from this work are going to be useful for developing electrical tariff policies for promoting
the PV based institutional micro-grid system under market energy pricing dynamics. Keywords: Smart micro-grid | Market energy pricing dynamics | Techno-economics | Solar photovoltaic | Energy management strategy |
مقاله انگلیسی |
3 |
Optimal energy management in the smart microgrid considering the electrical energy storage system and the demand-side energy efficiency program
مدیریت بهینه انرژی در میکروگرید هوشمند با توجه به سیستم ذخیره انرژی الکتریکی و برنامه بهره وری انرژی طرف تقاضا-2020 Smart MicroGrids (MGs) are known as a powerful platform for exploiting the Electrical Energy Storage Systems
(EESSs). On the other hand, the Energy Efficiency Programs (EEPs) are recognized as an integral and highly
valuable element of smart MGs investments and operations. While the EEPs are known to be long-term programs,
they affect the short-term programs such as day ahead energy management. In this paper, the optimal energy
management program model associated with EESSs and EEPs namely EMPEESSs
EEPs has been proposed. The problem
takes the investment rate on the EEPs into account while solving optimal energy management problem. To do
this, the EEPs have been applied to the demand model. Furthermore, the proposed demand model has been used
in the optimal energy management of the smart microgrids. The proposed objective function has been modeled
as Mixed Integer Non-Linear Programming (MINLP) for the optimal energy management. Moreover, the GAMS
software is used to solve the formulated optimization problem. The results of different scenarios confirm that the
EEPs and EESSs are effective programs for the smart MGs energy management. The results are analyzed, and the
best cost optimal solution is identified. Keywords: Energy Efficiency Programs (EEPs) | Electrical demand | Thermal demand | Distributed Generation (DG) | Energy storage | Energy management |
مقاله انگلیسی |
4 |
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 |
5 |
Design and Accomplishment of AI Control Strategy with API in Nearly Zero Energy Building Smart Grid
طراحی و تحقق استراتژی کنترل هوش مصنوعی با API در شبکه هوشمند ساخت تقریباً صفر انرژی-2020 With the development of the nearly zero energy
buildings (NEZB) technology, people have higher and higher
requirements for power management, for heat recovery
efficiency. In this paper, design and accomplishment of artificial
intelligent (AI) control strategy with application program
interface (API) protocol based on NEZB in smart microgrid
were proposed. The structure of supervisory control and data
acquisition (SCADA) system was designed to achieve online
monitoring of energy consumption and environment
parameters. The control strategy of power management and
heat recovery efficiency were carried out. Finally, the proposed
control strategy of smart microgrid is adopted in the actual
project and applied to several NEZB. Keywords : AI control strategy | API protocol | nearly zero energy building | heat recovery efficiency | smart microgrid |
مقاله انگلیسی |
6 |
Energy scheduling of a smart microgrid with shared photovoltaic panels and storage: The case of the Ballen marina in Samsø
برنامه ریزی انرژی از یک ریز شبکه هوشمند با پانل های فتوولتائیک مشترک و ذخیره سازی: پرونده مارینا بالن در سامسوی-2020 This paper focuses on the Model Predictive Control (MPC) based energy scheduling of a smart microgrid
equipped with non-controllable (i.e., with fixed power profile) and controllable (i.e., with flexible and
programmable operation) electrical appliances, as well as photovoltaic (PV) panels, and a battery energy
storage system (BESS). The proposed control strategy aims at a simultaneous optimal planning of the
controllable loads, the shared resources (i.e., the storage system charge/discharge and renewable energy
usage), and the energy exchange with the grid. The control scheme relies on an iterative finite horizon
on-line optimization, implementing a mixed integer linear programming energy scheduling algorithm to
maximize the self-supply with solar energy and/or minimize the daily cost of energy bought from the
grid under time-varying energy pricing. At each time step, the resulting optimization problem is solved
providing the optimal operations of controllable loads, the optimal amount of energy to be bought/sold
from/to the grid, and the optimal charging/discharging profile for the BESS.
The proposed energy scheduling approach is applied to the demand side management control of the
marina of Ballen, Samsø (Denmark), where a smart microgrid is currently being implemented as a
demonstrator in the Horizon2020 European research project SMILE. Simulations considering the marina
electric consumption (340 boat sockets, a service building equipped with a sauna and a wastewater
pumping station, and the harbour master’s office equipped with a heat pump), PV production (60kWp),
and the BESS (237 kWh capacity) based on a public real dataset are carried out on a one year time series
with a 1 h resolution. Simulations indicate that the proposed approach allows 90% exploitation of the
production of the PV plant. Furthermore, results are compared to a naïve control approach. The MPC
based energy scheduling improves the self-supply by 1.6% compared to the naïve control. Optimization of
the business economy using the MPC approach, instead, yields to 8.2% savings in the yearly energy cost
with respect to the naïve approach Keywords: Microgrid | Demand side management | Renewable energy | Energy storage | Energy management | On-line scheduling | Model predictive control | Optimization algorith |
مقاله انگلیسی |
7 |
Development of Battery Monitoring System in Smart Microgrid Based on Internet of Things (IoT)
توسعه سیستم مانیتورینگ باتری در ریز شبکه های هوشمند مبتنی بر اینترنت از اشیاء-2017 In this paper, battery monitoring system based on internet of things (IoT) has been developed to monitor the operational and performance of batteries in a smart microgrid system. This smart microgrid includes a battery pack, PV system, Intelligent Electronic Device (IED) hybrid inverter, grid connection and electricity load. The IoT developed in this work consists of a communication channel from and to IED, data acquisition algorithm, cloud system and Human Machine Interface (HMI). Data acquisition was scheduled to execute every minute as mentioned in IEC61724. The battery monitoring system information as part of battery management system (BMS) is displayed on a Human Machine Interface (HMI) using ExtJS / HTML5 framework which can be accessed using desktop or mobile devices. From analytical results, the average execution time for overall BMS-IoT based data acquisition to the cloud server is 19.54 ± 18.00 seconds. The result of availability monitored data in the cloud database server is 92.92 ± 6.00 percent, which shows satisfactory result for the reliability of BMS-IoT system data acquisition.
Keywords: battery monitoring system | smart microgrid | communication protocol | battery system | internet of things |
مقاله انگلیسی |
8 |
مدیریت بهینه ریز شبکه های هوشمند نامتعادل با قید کیفیت توان در طول چند انتقال زمان بندی شده بین حالت های متصل به شبکه و جزیره ای
سال انتشار: 2017 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 26 در سال های اخیر کیفیت توان تحویل شده به مصرف کنندگان توجه زیادی را به خود جلب کرده است. در ریز شبکه ها که شامل بارها، تولید حاصل از منابع متداول و تجدید پذیر و ادوات ذخیره انرژی (ES) هستند، وجود بارهای غیر خطی می تواند منجر به آلودگی هارمونیکی در ولتاژهای شین دیگر اعضای ریز شبکه شود. این مسأله می تواند منجر به اثرات نامطلوبی مانند گرما، گشتاورهای توالی منفی و عملکرد نادرست ادوات حفاظتی شود. اگر برخی اعضای ریز شبکه نسبت به هارمونیک های ولتاژ حساس باشند، کیفیت توان تحویلی باید در الگوریتم های بهینه سازی ریز شبکه مورد توجه قرار گیرد. سیستم مدیریت انرژی (EMS) مسئول بهینه سازی متمرکز عملکرد ریز شبکه است. بهینه سازی هوشمند بارها توسط بهینه کردن مقادیر و بازه های تبادل توان و کاهش توان، پاسخ تقاضا (DR) نامیده می شود [1]-[3].
کلمات کلیدی: کیفیت توان (PQ) | پاسخ تقاضا (DR) | پخش بار بهینه توزیع (DOPF). |
مقاله ترجمه شده |
9 |
A control strategy for microgrid inverters based on adaptive three-order sliding mode and optimized droop controls
یک استراتژی کنترل برای اینورترهای شبکه میکرو بر اساس حالت کشویی تطبیقی سه مرتبه و کنترل افت بهینه سازی-2014 Robust control and seamless formation are the two crucial problems that affect smart microgrids. This
paper proposes a new solution for microgrid inverters in terms of circuit topology and control struc
ture. The combined three-phase four-wire inverter, which is composed of three single-phase full-bridge
circuits, is adopted in this study. The control structure is based on the inner adaptive three-order sliding
mode closed-loop, the immediate virtual output-impedance loop, and the outer power control loop.
Three significant contributions are obtained: (1) the microgrid inverters effectively reject both voltage
and load disturbances with the adaptive sliding-mode controllers regardless of whether the inverters
are operating in the grid-connected mode, islanding mode, or transition from the grid-connected mode
to the islanding mode; (2) the virtual output impedance loop is applied to make a resistive equivalent
output impedance of the inverters and to meet the requirements of the inverter parallel operation in
the islanding mode; (3) the proposed droop method reduces the line inductive impedance effects and
improves the power sharing accuracy by optimizing the droop coefficients. The theoretical analysis and
test results validate the effectiveness of the proposed control scheme
Keywords:
Microgrid inverter
Distributed generation (DG)
Adaptive three-order sliding-mode control
Droop control
Disturbance rejection
Nonlinear load |
مقاله انگلیسی |