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Load Scheduling

RESEARCH

This is my capstone project which focused on efficient energy consumption in a home using load scheduling of home appliances. For a country like Ghana, where the utilities provided by the government are not enough for everyone, it is important that residential PV installations are embraced to reduce the number of grid energy dependents, and to reduce the cost of electricity for homeowners. However, for homeowners, allowing energy produced from PV installations to be pushed unto the grid without generating any revenue from it represents a loss. Therefore, maximum energy consumption of solar energy in a home would enable homeowners utilize as much solar energy from their solar installations while reducing the cost of electricity.

The objective of the study was to investigate and analyze the best scheduling algorithm for home appliances between Mixed Integer Linear Programming and Artificial Neural Networks. Particularly, the study had the following sub-objectives:

  1. The first part of the research investigated load consumption patterns of household appliances and classify them into schedulable and unschedulable loads.

  2. The second part scheduled the loads using MILP and ANN and a comprehensive cost benefit analysis, which is done to determine the best scheduling algorithm between the two.

Load Scheduling.png

Logic for Load Scheduling for Home Appliances.

Note that, Loads scheduled without solar are scheduled for off peak hours without compromising on user comfort

Optimal Scheduling.png
Scheduling of five.png

Loads scheduled with solar energy are as follows.

The same approach from scheduling without solar was used; however, here the solar energy produced was considered. Data of solar irradiance data for Ghana was downloaded from NASA’s website for an average day in May. The factors of my MILP model depend on:

  1. User Want

  2. Power Rating of the device

  3. Sunshine availability

The user want is an arbitrary number between 0 and 5, with 5 being the highest. If sunshine is available, with a user want of 3 and above, and the Power Rating of the device is less than the solar energy produced, the load would be scheduled for the solar energy to be consumed. If all conditions remain constant, however, the power rating of the device is higher than the solar energy produced. Under these conditions, the load is scheduled for grid. If the user want of the device is less than 3, then the load is not scheduled at all.

MILP Scheduled Loads.png

MILP Scheduled Loads with Solar Energy

ANN Scheduled Loads.png

ANN Scheduled Loads without Solar Energy

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