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Hybrid Intelligent Technologies in Energy Demand Forecasting pp 1–24Cite as

Introduction

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Abstract

Electrical energy could be hardly stocked; therefore, electric load forecasting plays a vital role in the daily operational management of power utility, such as load unit commitment, energy transfer scheduling, contingency planning load shedding, energy generation, load dispatch, power system operation security, hydrothermal coordination, and so on (Xiao et al. in Energy 82:524–549, 2015 [1], Wan et al. in Power Energy Syst 1:38–46, 2015 [2]), to guarantee energy reliable and sufficient supply without interruptions. Particularly, in the power market free competitive era, the advanced forecasting technology can successfully assist planning the electric system expansion, well designed electric load flow, and can ensure the economical operation security and control of the electrical systems. In addition, with the emergence of load management strategies, it is highly desirable to develop accurate, fast, simple, robust and interpretable load forecasting models for these electric utilities to achieve the purposes of higher reliability and management efficiency. Therefore, it is essential that every utility can forecast its demands accurately.

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  1. Department of Information Management, Oriental Institute of Technology, New Taipei, Taiwan

    Wei-Chiang Hong

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Hong, WC. (2020). Introduction. In: Hybrid Intelligent Technologies in Energy Demand Forecasting. Springer, Cham. https://doi.org/10.1007/978-3-030-36529-5_1

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