Combined compromise solution and blockchain-based structure for optimal scheduling of renewable-based microgrids: Stochastic information approach

In this paper, a novel secured architecture is developed based on the blockchain technology for the energy management program (EMP) of renewable-based microgrids. Indeed, the blockchain technology has been used for securing the data transaction among the agents, e.g., generators, consumption points, and the central control unit of the microgrid according to the hash function concept. To make the proposed framework more realistic, a stochastic framework based on fuzzy cloud theory is developed to capture the uncertainty effects from the renewable energy sources, as well as market electricity price and the hourly load demand. Each drop in the fuzzy cloud recognizes a deterministic framework for the EMP with a specific probability value. The EMP in a renewable microgrid with different types of power sources such as wind turbine (WT), photovoltaics (PV), storage, fuel cell (FC), and microturbine (MT) in a stochastic environment is a challenging task that requires a global solver for getting to the optimal operating point. To this end, a smart optimization method based on the theta-firefly algorithm (theta-FA) is designed which would look for the optimal solution in the polar space rather than the traditional Cartesian space. In addition, an adaptive modification approach based on local and global search operators is devised which can help the algorithm to make a mature optimization process. Two different scenarios are simulated in the paper to assess the different aspects of the proposed architecture in typical renewable microgrids incorporating the WT, PV, FC, MT, and storage.