RENEWABLE ENERGY INTEGRATION FOR SMART HOMES BY LOAD MANAGEMENT
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DESIGN DETAILS
The objective of the Demand side management (DSM) strategy is to increase the use of RES, increase the economic benefit and reduce the power imported from the main distribution grid or minimize the peak load demand. The objective load curve is taken as an input by the DSM system and demands for the control action to meet the desired load consumption. The algorithm is completely independent of the criteria that is used for generating the objective load curve. The connection moments of each shiftable device are scheduled by DSM.
Timing pricing i.e ToU, prices are well known in advance may be a year ahead and establishes a variable price structure for peak, shoulder, and off-peak hours and low peak hours. RTP vary on an hourly basis depending on the energy demand of the market. Variable peak pricing is a hybrid of the two and establishes variable pricing in the day. Energy can be efficiently consumed, and the power consumption can be efficiently minimized by voluntary reduction of home electric consumption based on energy awareness and automatic or manual reduction of home idle appliances. Smart meters and HEM are deployed so that consumers may respond according to the behaviour of energy markets and reduce their energy consumption at peak prices.
This design is based on finding the optimal approach for scheduling the power usage of smart appliances based on the ToU pricing scheme using Genetic Algorithm that is developed using Matlab. The model is simulated in time of use pricing environment for three cases: 1) traditional homes; 2) smart homes; and 3) smart homes with renewable energy sources. Using Matlab 2020a version simulation results are evaluated for optimal schedules the appliances resulting in electricity bill and peaks reductions.
REFERENCES
Reference Paper-1: An Intelligent Load Management System with Renewable Energy Integration for Smart Homes
Author’s Name: Nadeem Javaid, Ihsan Ullah, Mariam Akbar, Zafar Iqbal, Farman Ali Khan, Nabil Alrajeh, and Mohamad Souheil Alabed
Source: IEEE: Special Section on The New Era of Smart Cities: Sensors, Communication Technologies, and Applications
Year:2017
DOWNLOAD the Matlab(P-code) encrypted code from the below URL,
https://drive.google.com/file/d/14Zb3-6g4JHyZNL7B8woSXLO1z1dntLpQ/view?usp=sharing
SIMULATION VIDEO DEMO
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