On Data-Driven Approaches for Demand Response

Abstract

This chapter presents a detailed investigation on the resources, use, and benefits of big data analytics in smart grid activities that enable the participation of demand side in energy management. It starts by elucidating these activities called demand-side management and demand response (DR) and their role in providing higher saving potential for both system operators and end users. It then explains the use of big data management techniques in order to handle the huge amount of data required for efficient DR applications. Afterward, the benefit of various clustering methods and classification methods in DR applications is evaluated by classifying them into four main groups according to their objectives. First, the role of big data analytics on the energy consumption behavior of end users and on the electric load classification is examined. Then, the support of DR programs relying on big data analytics is evaluated for demand and renewable energy generation forecasting as well as dynamic pricing. © 2018 Elsevier Inc. All rights reserved.