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Wireless cellular networks are emerging to take a strong stand in attempts to achieve pervasive large scale obtainment, communication, and processing with the evolution of the fifth generation (5G) network. Both the present day cellular technologies and the evolving new age 5G are considered to be advantageous for the smart grid. The 5G networks exhibit relevant services for critical and timely applications for greater aspects in the smart grid. In the present day electricity markets, 5G provides new business models to the energy providers and improves the way the utility communicates with the grid systems. In this work, a complete analysis and a review of the 5G network and its vision regarding the smart grid is exhibited. The work discusses the present day wireless technologies, and the architectural changes for the past years are shown. Furthermore, to understand the user-based analyses in a smart grid, a detailed analysis of 5G architecture with the grid perspectives is exhibited. The current status of 5G networks in a smart grid with a different analysis for energy efficiency is vividly explained in this work. Furthermore, focus is emphasized on future reliable smart grid communication with future roadmaps and challenges to be faced. The complete work gives an in-depth understanding of 5G networks as they pertain to future smart grids as a comprehensive analysis.Energies 2019, 12, 2140 2 of 17 a need for an information system network that covers all the substations connected with the user facilities and the utilities. This provides the required system analysis with the needed reliable communication systems, which is an important building block of smart grid visibility.According to the communication standards, different communication technologies [11,12] can be classified based on either wired and wireless communications. Presently, wireless communications are preferred over wired communications for various reasons and in distinct applications with the reliability of cost at lower rates. This enhances infrastructure and provides readily available connections, even in remote areas. There are diverse factors, such as operational costs, environmental concerns, and availability of resources, to consider when choosing a proper, stable communication system. The voluminous and steady growth of communication technology over past decades is clearly explained in Figure 1. The development of new communication infrastructure with the existing wireless technologies can be more advantageous in smart grids. This provides advanced infrastructure where the need to spend additional cost and time [13] can be avoided. This establishes up-gradation of new wireless communication technologies for future smart grid communication systems [14][15][16][17][18][19]. For the past four decades-and marching towards the new wave of the technological era-growth of communication technologies has been an inevitable part of all modes of applications. To address prominent issues for developing new generation cellular communications, certain para...

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Demand response modelling have paved an important role in smart grid at a greater perspective. DR analysis exhibits the analysis of scheduling of appliances for an optimal strategy at the user's side with an effective pricing scheme. In this proposed work, the entire model is done in three different steps. The first step develops strategy patterns for the users considering integration of renewable energy and effective demand response analysis is done. The second step in the process exhibits the learning process of the consumers using Robust Adversarial Reinforcement Learning for privacy process among the users. The third step develops optimal strategy plan for the users for maintaining privacy among the users. Considering the uncertainties of the user's behavioral patterns, typical pricing schemes are involved with integration of renewable energy at the user' side so that an optimal strategy is obtained. The optimal strategy for scheduling the appliances solving privacy issues and considering renewable energy at user' side is done using Robust Adversarial Reinforcement learning and Gradient Based Nikaido-Isoda Function which gives an optimal accuracy. The results of the proposed work exhibit optimal strategy plan for the users developing proper learning paradigm. The effectiveness of the proposed work with mathematical modelling are validated using real time data and shows the demand response strategy plan with proper learning access model. The results obtained among the set of strategy develops 80 % of the patterns created with the learning paradigm moves with optimal DR scheduling patterns. This work embarks the best learning DR pattern created for the future set of consumers following the strategy so privacy among the users can be maintained effectively.INDEX TERMS Demand response, best strategy, robust adversarial reinforcement learning, renewable energy. NOMENCLATURE n i S -Strategy for set of users In -Incentives announced () n  -cost function for the model and   -Best policy parameters for learning , tt hl -reward and incentive function in learning i   -Policy strategy ( , ) n v  -Optimization function for pricing and cost analysis RL-Reinforcement Learning ADP -Approximate Dynamic Programming RARL -Robust Adversarial Reinforcement learning GNI -Gradient Based Nikaido -Isoda Function

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