Medium voltage network planning considering distributed generation and demand side management

2012 ◽  
Author(s):  
N. Rotering ◽  
J. Beyer ◽  
A. Moser ◽  
T. Smolka ◽  
P. Duisberg
Keyword(s):  
Distributed Generation ◽  
Network Planning ◽  
Demand Side Management ◽  
Demand Side ◽  
Medium Voltage

scholarly journals Effect of Demand Side Management on the Operation of PV-Integrated Distribution Systems

2020 ◽  
Vol 10 (21) ◽  
pp. 7551
Author(s):  
Jaser A. Sa’ed ◽  
Zakariya Wari ◽  
Fadi Abughazaleh ◽  
Jafar Dawud ◽  
Salvatore Favuzza ◽  
...  
Keyword(s):  
Distributed Generation ◽  
Smart Grids ◽  
Distribution Systems ◽  
Electrical Energy ◽  
Demand Side Management ◽  
Test System ◽  
Demand Side ◽  
Direct Load Control ◽  
Wide Range ◽  
Load Shape

In this new era of high electrical energy dependency, electrical energy must be abundant and reliable, thus smart grids are conducted to deliver load demands. Hence, smart grids are implemented alongside distributed generation of renewable energies to increase the reliability and controllability of the grid, but, with the very volatile nature of the Distributed Generation (DG), Demand Side Management (DSM) helps monitor and control the load shape of the consumed power. The interaction of DSM with the grid provides a wide range of mutual benefits to the user, the utility and the market. DSM methodologies such as Conservation Voltage Reduction (CVR) and Direct Load Control (DLC) collaborate in the reduction of plant generation and reciprocally to the comprehensive cost. The aim of this paper is to investigate the effects caused by the implementation of DSM on the operation of PV-integrated distribution systems. The algorithms of CVR, DLC and the combination of CVR and DLC were implemented using OpenDSS and MATLAB. The effectiveness of the aforementioned schemes was verified on IEEE 30-Bus test system. Various possible integration scenarios between Photovoltaic (PV) and DSM schemes are illustrated. The optimal integration of such schemes constraining the reduction of energy consumed by the user and utility is presented. The results show that the implemented DSM algorithms provide a noticeable reduction in energy losses and reduction in consumed energy.

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