Smart-grid (SG) is a new revolution in the electrical utility industry (EUI) over the past decade. With each moving day, some new advanced technologies are coming into the picture which forces the utility engineers to think about its application to make the electrical grid become smarter. Artificial intelligence (AI) techniques such as machine learning (ML), artificial neural network (ANN), deep learning (DL), reinforcement learning (RL), and deep-reinforcement learning (DRL) are the few examples of above-mentioned advanced technologies by which large volume of collected information being processed, and deliver the solution to the complex problems associated with EUI. In recent times, DL for artificial intelligence applications has gained huge attention in the diverse research area. The traditional ML techniques have several constrained for processing the data in raw form. However, the DL provides the options to process the raw data without extracting and selecting the feature vector. The DL techniques belong to a new era of AI development. This article presents the taxonomy of DL algorithms available in the literature applied to different problems in EUI. The main objective of this survey is to provide a comprehensive idea to the researcher/utility engineer about the applications and future research scope of DL methods for power systems studies.

智能电网（SG）是过去十年来电力行业（EUI）的一场新革命。日新月异，一些新的先进技术应运而生，迫使公用事业工程师考虑其应用，以使电网变得更加智能。诸如机器学习（ML），人工神经网络（ANN），深度学习（DL），强化学习（RL）和深度强化学习（DRL）等人工智能（AI）技术是上述高级技术的少数示例技术，通过这些技术可以处理大量收集的信息，并为与EUI相关的复杂问题提供解决方案。近年来，用于人工智能应用的DL在不同的研究领域引起了极大的关注。传统的ML技术在处理原始格式的数据时受到一些限制。但是，DL提供了处理原始数据的选项，而无需提取和选择特征向量。DL技术属于AI开发的新时代。本文介绍了适用于EUI中不同问题的文献中可用的DL算法分类。这项调查的主要目的是向研究人员/公用事业工程师提供有关DL方法在电力系统研究中的应用和未来研究范围的全面思路。本文介绍了适用于EUI中不同问题的文献中可用的DL算法分类。这项调查的主要目的是向研究人员/公用事业工程师提供有关DL方法在电力系统研究中的应用和未来研究范围的全面思路。本文介绍了适用于EUI中不同问题的文献中可用的DL算法分类。这项调查的主要目的是向研究人员/公用事业工程师提供有关DL方法在电力系统研究中的应用和未来研究范围的全面思路。