AI Business Model is Emerging Energy Market and Smart Grid

• Published in: Applications of Big Data and Artificial Intelligence in Smart Energy Systems Vol. 2; pp. 169 - 192
• Main Authors: Raval, Aanal, Lohia, Agrima, Bhatt, Urvi Y.
• Format: Book Chapter
• Language: English
• Published: River Publishers 2023
• Edition: 1
• Subjects: General Engineering & Project Administration; General References; Software Engineering; smart grids; energy markets; machine learning; Artificial intelligence; grid management
• ISBN: 8770228272; 8770229953; 9788770228275; 9788770229951
• DOI: 10.1201/9781003440864-8

In recent years, AI has fascinated many different industries with its alluring solutions and problem-solving techniques. Among them, it is becoming more and more admirable in energy markets. Its stretching areas include assessing, investigating, and dominating the data of other users via the grid; its decentralization; tackling a large number of participants; maintaining its calculation balance by inspecting the flood of data; integrating electromobility; determining optimal times for the maintenance work of networks; minimization of cost and loss; lessening disturbances; forecasting by evaluating a vast variety of particulars like weather data or historical data; coordination of information about which virtual power plant consumes what amount of electricity and when; as well as handling the stable and green electricity grid. The primary tasks of these industries include blueprinting, installation, and maintenance to deliver a high-quality and secure energy supply. While executing these tasks, one of the greatest challenges faced is to withstand potential uncertainties, which in turn can affect forecasting, scheduling, operation control, and risk management. AI techniques can handle the whole ecosystem by providing proper planning, monitoring, maintenance, and support for a decision-making system. 170This chapter provides a detailed analysis of different models that solve the above issues for better study. Artificial intelligence (AI) has been progressively used in smart grids, trading of electricity, along with its sector coupling, heat, and transport. Based on applications, AI in the energy market can be divided into fleet and asset management, demand response management, renewable energy management, demand forecasting, precision drilling, and infrastructure management. AI can solve some of the issues of smart grid, such as low efficiency for energy, and poor interaction, security, and stability. AI involvement in blockchain includes local trade of energy in smart grid, billing and rewarding based on usage, plug-in vehicles, digital signature, and addressing its leakage and privacy issues. The two-way communication of smart grid is vulnerable to attacks like data injection, data theft, and electricity theft. Learning consumer consumption and behavior and making decisions on it are an obligation to the smart grid. This chapter discusses possible approaches of AI to energy applications with future directions.