DEMAND SIDE MANAGEMENT OF RENEWABLE ENERGY INTEGRATED SMART GRID USING LOAD SHIFTING TECHNIQUES

Journal of Critical Reviews ◽

10.31838/jcr.07.10.546 ◽

2020 ◽

pp. 3193-3199

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Smart Grid ◽

Energy Management ◽

Demand Side Management ◽

Energy Resources ◽

Management Approach ◽

Demand Side ◽

Load Shifting ◽

The Impact

The Paris Agreement on Climate Change has led to introduction of new reforms for clean power plan such as decarbonization of power sector, planned decommissioning of thermal power plants and inclusion of renewable energies for power production. But this desired integration of renewable energy resources to power system faces two technical challenges: variability and uncertainty. An effective energy management with help of smart grid engineering can be the key for its beneficial use. Demand Side Management (DSM) is a valuable strategy for energy management in smart grid. It supports numerous smart grid functionalities for instance electricity market control, Load scheduling, managing decentralized distributed energy resources. Identifying energy consumption patterns and to sketch electricity load profiles can be achieved through numerous DSM based programs. Load shifting based DSM can be linked to consumer’s behavior in understanding their pattern of energy consumption. Here, the practiced load shifting based demand side management approach can help in maximizing power efficiency, sustaining power reliability and resiliency of renewable sources. This paper reviews the various energy management strategies developed to minimize the impact of renewable energy intermittency using Load Shifting Demand Side Management (DSM) approach.

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Hourly load shifting approach for demand side management in smart grid using grasshopper optimisation algorithm

IET Generation Transmission & Distribution ◽

10.1049/iet-gtd.2019.0566 ◽

2020 ◽

Vol 14 (5) ◽

pp. 808-815 ◽

Cited By ~ 3

Author(s):

Majid Jamil ◽

Sonam Mittal

Keyword(s):

Smart Grid ◽

Demand Side Management ◽

Demand Side ◽

Load Shifting ◽

Optimisation Algorithm

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Perspectives and Intensification of Energy Efficiency in Commercial and Residential Buildings Using Strategic Auditing and Demand-Side Management

Energies ◽

10.3390/en12234539 ◽

2019 ◽

Vol 12 (23) ◽

pp. 4539 ◽

Cited By ~ 2

Author(s):

Kumar ◽

Brar ◽

Singh ◽

Nikolovski ◽

Baghaee ◽

...

Keyword(s):

Energy Efficiency ◽

Energy Consumption ◽

Energy Management ◽

Residential Buildings ◽

Effective Means ◽

Demand Side Management ◽

Demand Side ◽

Specific System ◽

Energy Data ◽

Energy Auditing

With the ever-growing power demand, the energy efficiency in commercial and residential buildings is a matter of great concern. Also, strategic energy auditing (SEA) and demand-side management (DSM) are cost-effective means to identify the requirements of power components and their operation in the energy management system. In a commercial or residential building, the major components are light sources and heating, ventilation, and air conditioning. The number of these components to be installed depends upon the technical and environmental standards. In this scenario, energy auditing (EA) allows identifying the methods, scope, and time for energy management, and it helps the costumers to manage their energy consumption wisely to reduce electricity bills. In the literature, most of the traditional strategies employed specific system techniques and algorithms, whereas, in recent years, load shifting-based DSM techniques were used under different operating scenarios. Considering these facts, the energy data in a year were collected under three different seasonal changes, i.e., severe cold, moderate, and severe heat for the variation in load demand under different environmental conditions. In this work, the energy data under three conditions were averaged, and the DSM schemes were developed for the operation of power components before energy auditing and after energy auditing. Moreover, the performance of the proposed DSM techniques was compared with the practical results in both scenarios, and, from the results, it was observed that the energy consumption reduced significantly in the proposed DSM approach.

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Grid-Tied Distributed Generation Systems to Sustain the Smart Grid Transformation: Tariff Analysis and Generation Sharing

Energies ◽

10.3390/en13051187 ◽

2020 ◽

Vol 13 (5) ◽

pp. 1187 ◽

Cited By ~ 1

Author(s):

Fernando Yanine ◽

Antonio Sánchez-Squella ◽

Aldo Barrueto ◽

Antonio Parejo ◽

Felisa Cordova ◽

...

Keyword(s):

Renewable Energy ◽

Energy Consumption ◽

Energy Storage ◽

Smart Grid ◽

Power Control ◽

Energy Management ◽

Distributed Generation ◽

Electric Utility ◽

Green Energy ◽

Supply Capacity

In this paper a novel model is being proposed and considered by ENEL—the largest electric utility in Chile—and analyzed thoroughly, whereby electric power control and energy management for a 60-apartments’ residential building is presented as an example of the utility’s green energy program, part of its Smart Grid Transformation plan to install grid-tied distributed generation (DG) systems, namely microgrids, with solar generation and energy storage in Santiago, Chile. The particular tariffs scheme analysis shown is part of the overall projected tentative benefits of adopting the new scheme, which will require the utility’s customers to adapt their consumption behavior to the limited supply of renewable energy by changing energy consumption habits and schedules in a way that maximizes the capacity and efficiency of the grid-tied microgrid with energy storage. The change in behavior entails rescheduling power consumption to hours where the energy supply capacity in the DG system is higher and price is lower as well as curtailing their power needs in certain hourly blocks so as to maximize DG system’s efficiency and supply capacity. Nevertheless, the latter presents a problem under the perspective of ENEL’s renewable energy sources (RES) integration plan with the electric utility’s grid supply, which, up until now and due to current electric tariffs law, has not had a clear solution. Under said scenario, a set of strategies based on energy homeostasis principles for the coordination and control of the electricity supply versus customers’ demand has been devised and tested. These strategies which consider various scenarios to conform to grid flexibility requirements by ENEL, have been adapted for the specific needs of these types of customers while considering the particular infrastructure of the network. Thus, the microgrid adjusts itself to the grid in order to complement the grid supply while seeking to maximize green supply capacity and operational efficiency, wherein the different energy users and their energy consumption profiles play a crucial role as “active loads”, being able to respond and adapt to the needs of the grid-connected microgrid while enjoying economic benefits. Simulation results are presented under different tariff options, system’s capacity and energy storage alternatives, in order to compare the proposed strategies with the actual case of traditional grid’s electricity distribution service, where no green energy is present. The results show the advantage of the proposed tariffs scheme, along with power control and energy management strategies for the integration of distributed power generation within ENEL’s Smart Grid Transformation in Chile.

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

Sensors ◽

10.3390/s19204443 ◽

2019 ◽

Vol 19 (20) ◽

pp. 4443 ◽

Cited By ~ 2

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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