AI-Driven Dynamic Pricing Mechanisms for Demand-Side Management

Abstract

More and more people are realizing that dynamic price systems are good for controlling demand-side energy use. In this situation, artificial intelligence (AI) is very important for finding the best price methods to get results like managing loads, shaving off busy hours, and lowering costs. This essay looks at how AI-driven dynamic price systems could be used for demand-side control in the energy industry. AI programs, especially machine learning and optimization methods, are used to correctly predict future demand patterns by looking at past usage data, market conditions, weather patterns, and customer behavior. Based on these predictions, changeable price models are made to give people a reason to use less energy during busy times or switch their usage to off-peak times. There are different kinds of these pricing systems, such as important peak pricing, time-of-use pricing, and real-time pricing. AI also makes it possible to use customizable price strategies that are based on the needs and interests of each customer. AI algorithms can constantly change prices for each customer group by looking at things like readiness to pay, comfort preferences, and device usage patterns. This makes the system more engaging and satisfied while also making it more efficient overall. Also, demand response programs are made easier by AI-driven dynamic price systems that give customers real-time feedback and rewards.