Optimal combined load forecast based on multi-criteria decision making methods
Owing to the importance of load forecasting, accurate models for electric power load forecasting are essential to the operation and planning of a utility company. Their main idea is to establish the mathematical optima model for forecasting, intend to match the data, and make predict error least,...
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| Format: | Thesis |
| Language: | English English English |
| Published: |
2013
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| Subjects: | |
| Online Access: | http://eprints.uthm.edu.my/6623/1/24p%20AHMAD%20KHAIRUL%20RADHI%20KAMARUZAMAN.pdf http://eprints.uthm.edu.my/6623/2/AHMAD%20KHAIRUL%20RADHI%20KAMARUZAMAN%20COPYRIGHT%20DECLARATION.pdf http://eprints.uthm.edu.my/6623/3/AHMAD%20KHAIRUL%20RADHI%20KAMARUZAMAN%20WATERMARK.pdf http://eprints.uthm.edu.my/6623/ |
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| Summary: | Owing to the importance of load forecasting, accurate models for electric
power load forecasting are essential to the operation and planning of a utility
company. Their main idea is to establish the mathematical optima model for
forecasting, intend to match the data, and make predict error least, and attain superior
forecast result. This paper present the analyzing of soft method such as decision
making analyses to solve load forecast in power system demand that are unstructured
problems of multi-factors. The combined forecasting problem is treated as multihierarchies
and multi-factors evaluation by composing qualitative analyses and
quantitative calculation. In addition, the experiences and judgments of experts will be
collected to implement judgment matrices in group decision making. This paper
proposed the soft method based on Analytic Hierarchy Process (AHP), Fuzzy
Analytic Hierarchy Process (Fuzzy AHP) and Technique for Order Preference by
Similarity to Ideal Solution (TOPSIS) to carry out long middle term load demand
combined forecast. A hierarchy structure has been established by analyzing various
factors that affect the load forecast. It is the key to determine the combined weight
coefficients in the optimal combined forecasting method. Fuzzy complementary
judgment matrixes of pair-wise comparison will be formed by expert in each
hierarchy and be converted to a fuzzy consistent matrix. The eigenvector can be
calculated using its general formula and be regarded as weight coefficient in
combined forecasting. The combined forecast methods based on the Analytic
Hierarchy Process (AHP), Fuzzy Analytic Hierarchy Process (Fuzzy AHP) and
Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are of clear
hierarchy structure, sufficient judgment information and simple calculation formula.
The forecasting examples show that this method is practical, convenient and
accurate. |
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