![]() Therefore, this paper fulfills the need and presents a comprehensive review of the state-of-the-art successful and distinguished intelligent control strategies-based RL in optimizing the management of power flow and distribution. Accordingly, there is an ongoing need to accomplish a clear, up-to-date, vision of the development level, especially with the lack of recent comprehensive detailed reviews of this vitally important research field. The reason is it does not need an accurate model for attaining an optimized solution regarding the interaction with the environment. Among the smart approaches, reinforcement learning stands as the most relevant and successful, particularly in power distribution management applications. ![]() Unlike other numerical or soft computing optimization methods, the control based on artificial intelligence allows the decentralized power units to collaborate in making the best decision of fulfilling the administrator's needs, rather than only a primitive decentralization based only on the division of tasks. Arguably, many challenges can be overcome, and benefits leveraged, in this transition by the adoption of intelligent autonomous computer-based decision-making through the introduction of smart technologies, specifically artificial intelligence. Intelligent energy management in renewable-based power distribution applications, such as microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important in the context of the transition toward the decentralization, digitalization, and decarbonization of energy networks. In a nutshell, a significant synthesis of Agent Based Modelling and Simulation (ABMS) resources has been performed in this review that stimulates further investigation into this topic. (2) Provide a usable reference that aids engineers, researchers, learners and academicians in readily selecting an appropriate agent-based modelling and simulation toolkit for designing and developing their system models and prototypes, cognizant of both their expertise and those requirements of their application domain. The original contribution of this survey is two-fold: (1) Present a concise characterization of almost the entire spectrum of agent-based modelling and simulation tools, thereby highlighting the salient features, merits, and shortcomings of such multi-faceted application software this article covers eighty five agent-based toolkits that may assist the system designers and developers with common tasks, such as constructing agent-based models and portraying the real-time simulation outputs in tabular/graphical formats and visual recordings. The key intent of this work is to present a comprehensive comparative literature survey of the state-of-art in software agent-based computing technology and its incorporation within the modelling and simulation domain.
0 Comments
Leave a Reply. |