An Experimental Fuzzy Inference System for Global Grid Electricity Peak Power Load Forecasting Third Core Module of First Console on G2P3S

Year 2017, Volume: 1 Issue: 2, 75 - 101, 03.12.2017

Burak Omer Saracoglu

https://doi.org/10.30521/jes.338575

Cited By: 7

Abstract

Our World gives several symptoms of climate change.
Devastating draughts increase (negative for World (-)), global mean temperature
increase (-), lightning strikes increase (-), sea ice cover melt (-), tree mortality
increase (-), and forest degradation increase (-) have been observed for
decades. They are all negative measures for continuity of life. Diversity of
species has been decreasing, so that life on Earth is dying. Only responsible
specie for this situation is humankind. This study presents a small footstep to
prevent this situation. Modeling of a 100% renewable power grid on World
(Global Grid) is eminent. Annual peak power load (Gigawatt: GW, Kilowatt: kW)
(peak demand or load) forecasting in power demand side is crucial for global
grid modeling. This study presents an experimental fuzzy inference system for
the third core module (100 years’ power demand forecasting) of the first
console (long term prediction) of Global Grid Peak Power Prediction System (G²P³S).
The inputs (world population, global annual temperature anomalies °C) and the
output (annual peak power load demand of Global Grid in GW) are modeled with
seven triangular fuzzy input membership functions and seven constant output
membership functions. The constant Sugeno-Type fuzzy inference system is used
in the current experimental model. The maximum absolute percentage error (MAP)
is calculated as 45%, and the mean absolute percentage error (MAPE) is found as
39% in this experimental study. The MAP and MAPE of the
first core module model (Type 1) were 0,46 and 0,36. The MAP and MAPE of the
second core module model (Interval Type 2) were 0,46 and 0,36. As a result,
this study is a good start for the third core module of the first console on Global
Grid Peak Power Prediction System research, development, demonstration, &
deployment (RD³) project. This experimental study also warns
humankind in this subject. Hopefully, the most polluting societies on our World
such as China, United States, India, Russia, Japan, Germany, South Korea, and
Canada take urgent actions to start to build the foundations of 100% renewable
power global grid by organizing a global grid consortium.

Keywords

Scilab, Sugeno, Takagi-Sugeno-Kang, Fuzzy inference system, Global grid, Peak power

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