A systematical analysis on the dynamic pricing strategies and optimization methods for energy trading in smart grids

The smart grid (SG) is an enhancement of the traditional electrical grid. Its main objectives are diverse, focusing mainly on minimizing the energy cost, as well as energy consumption. The smooth integration of renewable energy balances energy production and consumption. Dynamic pricing (DP) becomes one of the important integrated solutions, which comes in line with the global efficiency and reliability of smart grids. DP incentivizes the consumer to participate in the energy scheduling decision, mainly in the real-time decision. Consumer represents the key challenge in the SG in perspective to make the energy system more efficient. Moreover, the success of smart grids relies mostly on the evolution of the widely used optimization methods. These include measures to encourage consumers and providers to be involved in the development of the SG. The main objective of this article is to review and analyze the recent research works regarding the pricing strategies and optimization methods utilized in the context of SG. A systematic analysis is thus performed by considering twofold views. First, it comprehensively approaches the pricing majors and visualizes the game theory used in real-time pricing. Second, it describes the optimization methods used in the smart grid context and compares them in terms of their complexity.