Demand-Side Response Smart Grid Technique for Optimized Energy Use

2011 ◽  
pp. 137-163 ◽  
Author(s):  
Fouad Kamel ◽  
Marwan Marwan
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Electricity Market ◽  
Energy Use ◽  
Combustion Engine ◽  
Renewable Energy Sources ◽  
Management Strategies ◽  
Electrical Energy ◽  
Electricity System ◽  
Time Price

The chapter describes a dynamic smart grid concept that enables electricity end-users to be acting on controlling, shifting, or curtailing own demand to avoid peak-demand conditions according to information received about electricity market conditions over the Internet. Computer-controlled switches are used to give users the ability to control and curtail demand on a user’s premises as necessary, following a preset user’s preferences. The computerized switching provides the ability to accommodate local renewable energy sources as available. The concept offers further the ability to integrate charging electrical vehicles during off-peak periods, helping thus substantially improving the utilization of the whole electricity system. The approach is pursuing improved use of electrical energy associated with improved energy management, reduced electricity prices and reduced pollution caused by excessive use of combustion engine in transport. The technique is inherently restricted to take effect in frame of energy tariff regimes based on real-time price made to encourage and reward conscious users being proactively participating in holistic energy management strategies.

Demand-Side Response Smart Grid Technique for Optimized Energy Use

2013 ◽  
pp. 1614-1639
Author(s):  
Fouad Kamel ◽  
Marwan Marwan
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Electricity Market ◽  
Energy Use ◽  
Combustion Engine ◽  
Renewable Energy Sources ◽  
Management Strategies ◽  
Electrical Energy ◽  
Electricity System ◽  
Time Price

The chapter describes a dynamic smart grid concept that enables electricity end-users to be acting on controlling, shifting, or curtailing own demand to avoid peak-demand conditions according to information received about electricity market conditions over the Internet. Computer-controlled switches are used to give users the ability to control and curtail demand on a user’s premises as necessary, following a preset user's preferences. The computerized switching provides the ability to accommodate local renewable energy sources as available. The concept offers further the ability to integrate charging electrical vehicles during off-peak periods, helping thus substantially improving the utilization of the whole electricity system. The approach is pursuing improved use of electrical energy associated with improved energy management, reduced electricity prices and reduced pollution caused by excessive use of combustion engine in transport. The technique is inherently restricted to take effect in frame of energy tariff regimes based on real-time price made to encourage and reward conscious users being proactively participating in holistic energy management strategies.

Energy Management System for Hybrid Microgrids

2021 ◽  
Vol 69 (2) ◽  
pp. 21-30
Author(s):  
Nasreddine ATTOU ◽  
Sid-Ahmed ZIDI ◽  
Mohamed KHATIR ◽  
Samir HADJERI
Keyword(s):  
Energy Management ◽  
Electricity Market ◽  
Management System ◽  
Energy Demand ◽  
Renewable Energy Sources ◽  
Supply And Demand ◽  
Energy Sources ◽  
Variable Load ◽  
Energy Management System ◽  
Price Variation

Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

scholarly journals Energy management strategies for combined heat and electric power micro-grid

2016 ◽  
Vol 20 (4) ◽  
pp. 1091-1103 ◽  
Author(s):  
Marina Barbaric ◽  
Drazen Loncar
Keyword(s):  
Energy Management ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Optimization Technique ◽  
Management Strategies ◽  
Distribution Networks ◽  
Energy Storage System ◽  
Optimization Approach ◽  
Micro Grid ◽  
Additional Rule

The increasing energy production from variable renewable energy sources such as wind and solar has resulted in several challenges related to the system reliability and efficiency. In order to ensure the supply-demand balance under the conditions of higher variability the micro-grid concept of active distribution networks arising as a promising one. However, to achieve all the potential benefits that micro-gird concept offer, it is important to determine optimal operating strategies for micro-grids. The present paper compares three energy management strategies, aimed at ensuring economical micro-grid operation, to find a compromise between the complexity of strategy and its efficiency. The first strategy combines optimization technique and an additional rule while the second strategy is based on the pure optimization approach. The third strategy uses model based predictive control scheme to take into account uncertainties in renewable generation and energy consumption. In order to compare the strategies with respect to cost effectiveness, a residential micro-grid comprising photovoltaic modules, thermal energy storage system, thermal loads, electrical loads as well as combined heat and power plant, is considered.

scholarly journals OVERVIEW OF DISTANCE ENERGY TRANSMISSION MEANS FOR POWERING AGRICULTURAL MACHINERY TAKING INTO ACCOUNT FACTORS AFFECTING HUMAN SAFETY

2021 ◽  
Vol 4 (164) ◽  
pp. 10-13
Author(s):  
V. Halil ◽  
S. Zakurdai ◽  
V. Scurikhin ◽  
O. Donets ◽  
D. Zubenko
Keyword(s):  
Combustion Engine ◽  
Renewable Energy Sources ◽  
Electrical Energy ◽  
Electric Transport ◽  
Electric Motors ◽  
Agricultural Machinery ◽  
Transport Equipment ◽  
Agricultural Equipment ◽  
Electric Traction ◽  
The Impact

This article discusses the issues of autonomous operation of electrical agricultural equipment based on the transmission of electricity over a distance. The main point of this article is that tractors that work in the field are driven by electric motors, with the need to use expensive batteries. The issues of the impact and safety of this technology on the environment and humans are considered. The main problem of the creation, maintenance and operation of transport equipment, including agricultural equipment, is the high cost of maintenance and fuel, which are constantly increasing. In addition, the environmental problem, which has become so acute in recent years, global warming, the fuel crisis and the need to transfer all transport equipment to electric traction, make us look for new ways to solve the problem of environmental pollution and save resources, especially non-renewable energy sources. The use of electrical energy for traction of agricultural machinery that work in the fields or in other industries has been used for a long time, and in the early stages of the development of transport, it was electric transport that occupied the main part, before the invention of the internal combustion engine. Including at the Kharkov Tractor Plant there were developments (and still are), a prototype of the use of electric motors as the main unit for movement. Based on the above, it is obvious that electric traction for transport is obviously environmentally friendly and safe, although there are a number of limitations in this matter as well, but the unresolved problems of the limited use of the storage battery force us to look for new sources of energy. This article proposes to consider the possibility of using electric traction for agricultural machinery with the supply of operating tractors in the fields with the help of a directed electromagnetic wave with its transformation into electrical energy, which will be supplied to the electric motor.

scholarly journals Development of Home Energy Management Scheme for a Smart Grid Community

Energies ◽  
2020 ◽  
Vol 13 (17) ◽  
pp. 4288 ◽  
Author(s):  
Md Mamun Ur Rashid ◽  
Fabrizio Granelli ◽  
Md. Alamgir Hossain ◽  
Md. Shafiul Alam ◽  
Fahad Saleh Al-Ismail ◽  
...  
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Renewable Energy Sources ◽  
Operating Time ◽  
Power Sharing ◽  
Electricity Cost ◽  
Home Appliances ◽  
Optimal Power ◽  
Management Scheme ◽  
Home Energy Management

The steady increase in energy demand for residential consumers requires an efficient energy management scheme. Utility organizations encourage household applicants to engage in residential energy management (REM) system. The utility’s primary goal is to reduce system peak load demand while consumer intends to reduce electricity bills. The benefits of REM can be enhanced with renewable energy sources (RESs), backup battery storage system (BBSS), and optimal power-sharing strategies. This paper aims to reduce energy usages and monetary cost for smart grid communities with an efficient home energy management scheme (HEMS). Normally, the residential consumer deals with numerous smart home appliances that have various operating time priorities depending on consumer preferences. In this paper, a cost-efficient power-sharing technique is developed which works based on priorities of appliances’ operating time. The home appliances are sorted on priority basis and the BBSS are charged and discharged based on the energy availability within the smart grid communities and real time energy pricing. The benefits of optimal power-sharing techniques with the RESs and BBSS are analyzed by taking three different scenarios which are simulated by C++ software package. Extensive case studies are carried out to validate the effectiveness of the proposed energy management scheme. It is demonstrated that the proposed method can save energy and reduce electricity cost up to 35% and 45% compared to the existing methods.

scholarly journals A Smart Autonomous Time- and Frequency-Domain Analysis Current Sensor-Based Power Meter Prototype Developed over Fog-Cloud Analytics for Demand-Side Management

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4443 ◽  
Author(s):  
Yung-Yao Chen ◽  
Yu-Hsiu Lin
Keyword(s):  
Smart Grid ◽  
Energy Management ◽  
Electrical Energy ◽  
Demand Side Management ◽  
Current Sensor ◽  
The Internet ◽  
Load Identification ◽  
Demand Side ◽  
Power Meter ◽  
Iot Devices

Electrical energy management, or demand-side management (DSM), in a smart grid is very important for electrical energy savings. With the high penetration rate of the Internet of Things (IoT) paradigm in modern society, IoT-oriented electrical energy management systems (EMSs) in DSM are capable of skillfully monitoring the energy consumption of electrical appliances. While many of today’s IoT devices used in EMSs take advantage of cloud analytics, IoT manufacturers and application developers are devoting themselves to novel IoT devices developed at the edge of the Internet. In this study, a smart autonomous time and frequency analysis current sensor-based power meter prototype, a novel IoT end device, in an edge analytics-based artificial intelligence (AI) across IoT (AIoT) architecture launched with cloud analytics is developed. The prototype has assembled hardware and software to be developed over fog-cloud analytics for DSM in a smart grid. Advanced AI well trained offline in cloud analytics is autonomously and automatically deployed onsite on the prototype as edge analytics at the edge of the Internet for online load identification in DSM. In this study, auto-labeling, or online load identification, of electrical appliances monitored by the developed prototype in the launched edge analytics-based AIoT architecture is experimentally demonstrated. As the proof-of-concept demonstration of the prototype shows, the methodology in this study is feasible and workable.

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