scholarly journals Supply Side Management vs. Demand Side Management of a Residential Microgrid Equipped with an Electric Vehicle in a Dual Tariff Scheme

Energies ◽  
2019 ◽  
Vol 12 (22) ◽  
pp. 4351 ◽  
Author(s):  
Alain Aoun ◽  
Hussein Ibrahim ◽  
Mazen Ghandour ◽  
Adrian Ilinca
Keyword(s):  
Electric Vehicle ◽  
Storage System ◽  
Electric Energy ◽  
Demand Side Management ◽  
Industrial Applications ◽  
Energy Model ◽  
Supply Side ◽  
Demand Side ◽  
Pv System ◽  
Power Sources

Fundamentally, two main methodologies are used to reduce the electric energy bill in residential, commercial, and even industrial applications. The first method is to act on the supply side by integrating alternative means of power generation, such as renewable energy generators, having a relatively low levelized cost of energy. Whereas, the second methodology focuses on the management of the load to minimize the overall paid cost for energy. Thus, this article highlights the importance of demand side management by comparing it to the supply side management having, as criteria, the total achieved savings on the overall annual energy bill of a residential microgrid supplied by two power sources and equipped with an electric vehicle. The optimization takes into consideration the cost of kWh that is paid by the prosumer based on an economical model having as inputs the outcomes of the energy model. The adopted energy model integrates, on the demand side, an intelligent energy management system acting on secondary loads, and on the supply side, a photovoltaic (PV) system with and without battery energy storage system (BESS). The outcome of this work shows that, under the right circumstances, demand side management can be as valuable as supply side control.

Optimal demand-side management with a multi-technology battery storage system

2018 ◽  
Vol 1 ◽  
pp. 345-349
Author(s):  
G. Fernández ◽  
◽  
H. Bludszuweit ◽  
J. Torres ◽  
J. Almajano ◽  
...  
Keyword(s):  
Storage System ◽  
Demand Side Management ◽  
Demand Side ◽  
Battery Storage

scholarly journals Autonomous Fuzzy Controller Design for the Utilization of Hybrid PV-Wind Energy Resources in Demand Side Management Environment

Electronics ◽  
2021 ◽  
Vol 10 (14) ◽  
pp. 1618
Author(s):  
Mohanasundaram Anthony ◽  
Valsalal Prasad ◽  
Raju Kannadasan ◽  
Saad Mekhilef ◽  
Mohammed H. Alsharif ◽  
...  
Keyword(s):  
Wind Energy ◽  
Energy Cost ◽  
Fuzzy Controller ◽  
Residential Buildings ◽  
Peak Load ◽  
Demand Side Management ◽  
Consumption Pattern ◽  
Demand Side ◽  
Pv System ◽  
Inference System

This work describes an optimum utilization of hybrid photovoltaic (PV)—wind energy for residential buildings on its occurrence with a newly proposed autonomous fuzzy controller (AuFuCo). In this regard, a virtual model of a vertical axis wind turbine (VAWT) and PV system (each rated at 2 kW) are constructed in a MATLAB Simulink environment. An autonomous fuzzy inference system is applied to model primary units of the controller such as load forecasting (LF), grid power selection (GPS) switch, renewable energy management system (REMS), and fuzzy load switch (FLS). The residential load consumption pattern (4 kW of connected load) is allowed to consume energy from the grid and hybrid resources located at the demand side and classified as base, priority, short-term, and schedulable loads. The simulation results identify that the proposed controller manages the demand side management (DSM) techniques for peak load shifting and valley filling effectively with renewable sources. Also, energy costs and savings for the home environment are evaluated using the proposed controller. Further, the energy conservation technique is studied by increasing renewable conversion efficiency (18% to 23% for PV and 35% to 45% for the VAWT model), which reduces the spending of 0.5% in energy cost and a 1.25% reduction in grid demand for 24-time units/day of the simulation study. Additionally, the proposed controller is adapted for computing energy cost (considering the same load pattern) for future demand, and it is exposed that the PV-wind energy cost reduced to 6.9% but 30.6% increase of coal energy cost due to its rise in the Indian energy market by 2030.

Smart Factory Meets Smart Grid: Cyber-Physical Compressed Air Systems Enable Demand Side Management in Industrial Environments

2015 ◽  
Vol 805 ◽  
pp. 25-31 ◽  
Author(s):  
Ralf Boehm ◽  
Johannes Bürner ◽  
Jörg Franke
Keyword(s):  
Business Models ◽  
Service Providers ◽  
Supply And Demand ◽  
Electric Energy ◽  
Demand Side Management ◽  
Compressed Air ◽  
Demand Side ◽  
Industrial Enterprises ◽  
Industrial Environments ◽  
Air Compressors

In electric energy systems based on renewable generation plants supply and demand often do not occur in the same period of time. Consequently demand side management is gaining importance whereby decentralized automation offers opportunities in industrial environments. Compressed air systems on industrial plants consist of air compressors, compressed air reservoirs and compressed air lines. With suitable dimensioning those industrial compressed-air systems can be used for demand side management purpose. As power consumption of industrial air compressors ranges between a few and several hundred kilowatts each, swarms of communicatively connected air compressors can contribute to the stabilization of power grids. To avoid costly production downtime it is to ensure, that a reliable, non-disruptive supply of compressed air can be maintained at all time. Industrial compressed air systems equipped with automation technology and artificial intelligence, which hereinafter are referred to as Cyber-Physical Compressed Air Systems (CPCAS), allow new business models for utilities, industrial enterprises, compressor manufacturers and service providers. In addition to basic operating parameters like current air pressure and status, those systems can process further information and create, for example, profiles on compressed air consumption over time. By enriching those profiles with data on pressure, volumes, system restrictions and current production requirements (plans), the CPCAS can identify the available potential for demand side management. Ipso facto predictive power on electricity consumption is increasing. By providing the information obtained to the power company or a service provider, savings in electricity costs may be achieved. Expenses within the industrial company may be lowered further as compliance with agreed load limits is being improved by automatic shutdown of air compressors upon reaching the load limit. Within this article the structure of the aforementioned Cyber-Physical Compressed Air Systems is presented in more detail, relations between the major actors are being shown and possible business models are being introduced.

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