Intelligent Techniques Demand Side Management and Flexibility

Comparing current power systems with the past time, more complexity can be observed, like large integration of renewable energy sources with fluctuated production curve, distributed generation, and also higher demand. Intelligent techniques are active movements of controlling the grid in a secure, reliable, and efficient way. An optimized energy network can be defined as the positive interaction of three main layers: physical power system, energy management, and socioeconomic operation. The management layer accounts for ensuring the reliability and security of the energy supply and is highly interconnected with the last layer to handle the optimized power flow in the system. Dramatic changes in the universal energy landscape have made demand side management (DSM) a challenging field that may face several limits. On the other hand, intelligent DSM aims to modify consumption time profile and grid connection parameters to achieve savings in electricity charges despite encountering instability on the grid and consequent disruptions to services. The initial step of this purpose is to carry out an analysis of the demand curve and consumer behavior that is simplified by artificial intelligence (AI) algorithms which can overcome some unexpected behavior. Implementation of different policies in DSM provokes consumers for peak demand reduction and energy-saving; however, it is worth mentioning that in smart grids, loads can also be produced and are known as active loads. The basics of DSM will be discussed in this chapter, and ultimately, the application of an AI-based DSM in performing faster response on a real-time basis to trace consumption 184 patterns and forecasting it, demand response strategies, and managing power outages will be explained and clarified.