Load forecasting, dynamic pricing and DSM in smart grid: A review
Renewable and Sustainable Energy ReviewsPublished 11 November 2015
Ahsan Raza Khan, Anzar Mahmood, Awais Safdar, Zafar A. Khan, Naveed Ahmed Khan
Citations444
SJR quartileQ1
SJR score3.90
SNIP4.08
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TL;DR
A comprehensive and comparative review of the LF and dynamic pricing schemes in smart grid environment, including Real Time Pricing (RTP), Time of Use (ToU) and Critical Peak Pricing (CPP) are presented.
Abstract
Load forecasting (LF) plays important role in planning and operation of power systems. It is envisioned that future smart grids will utilize LF and dynamic pricing based techniques for effective Demand Side Management (DSM). This paper presents a comprehensive and comparative review of the LF and dynamic pricing schemes in smart grid environment. Real Time Pricing (RTP), Time of Use (ToU) and Critical Peak Pricing (CPP) are discussed in detail. Two major categories of LF: mathematical and artificial intelligence based computational models are elaborated with subcategories. Mathematical models including auto recursive, moving average, auto recursive moving average, auto recursive integrated moving average, exponential smoothing, iterative reweighted mean square, multiple regression, etc. used for effective DSM are discussed. Neural networks, fuzzy logic, expert systems of the second major category of LF models have also been described.
Keywords
Engineering
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