Date of Award

1-1-2014

Document Type

Thesis

Degree Name

M.S.

Department

Electrical Engineering

First Advisor

Wenzhong Gao

Keywords

Different Countries Polices and Current Statuses, Latest Products, Neural Network, Short-term Load Forecasting, Smart Grid, Smart Meter

Abstract

Short-term load forecasting of power system has been a classic problem for a long time. Not merely it has been researched extensively and intensively, but also a variety of forecasting methods has been raised.

This thesis outlines some aspects and functions of smart meter. It also presents different policies and current statuses as well as future projects and objectives of SG development in several countries.

Then the thesis compares main aspects about latest products of smart meter from different companies.

Lastly, three types of prediction models are established in MATLAB to emulate the functions of smart grid in the short-term load forecasting, and then their results are compared and analyzed in terms of accuracy. For this thesis, more variables such as dew point temperature are used in the Neural Network model to achieve more accuracy for better short-term load forecasting results.

Provenance

Recieved from ProQuest

Rights holder

Jixuan Zheng

File size

81 p.

File format

application/pdf

Language

en

Discipline

Electrical engineering, Engineering, Energy

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