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The power grid is rapidly transforming, and while recent grid innovations increased the utilization of advanced control methods, the next-generation grid demands technologies that enable the integration of distributed energy resources (DERs)—and consumers that both seamlessly buy and sell electricity. This paper develops an optimization model and blockchain-based architecture to manage the operation of crowdsourced energy systems (CESs), with peer-to-peer (P2P) energy trading transactions (ETTs). An operational model of CESs in distribution networks is presented considering various types of ETT and crowdsourcees. Then, a two-phase operation algorithm is presented: Phase I focuses on the day-ahead scheduling of generation and controllable DERs, whereas Phase II is developed for hour-ahead or real-time operation of distribution networks. The developed approach supports seamless P2P energy trading between individual prosumers and/or the utility. The presented operational model can also be used to operate islanded microgrids. The CES framework and the operation algorithm are then prototyped through an efficient blockchain implementation, namely, the IBM Hyperledger Fabric. This implementation allows the system operator to manage the network users to seamlessly trade energy. Case studies and prototype illustration are provided. [ABSTRACT FROM AUTHOR]

Energy systems are complex systems consisting of different decision making entities: policy makers (or system operators), generation companies, utility companies, and consumers. In this paper, the focus is on the decisions made by different market competitors, such as the energy generation companies (GENCOs) and their interactions with the policy makers. The goals of the independent system operators (ISOs) in a deregulated market are to minimize the policy cost and to maximize renewable energy penetration. The problem formulation presented in this paper is aimed toward helping the ISO in modeling the lower-level GENCOs' decision problems. GENCOs compete in energy production, while maximizing their net present values and minimizing their capital investments. The market players' decisions result in a lower-level market equilibrium problem, which is formulated as a complementarity problem. The existence and uniqueness of the solution for the lower-level problem are shown. The main aims of the paper are to study the effect of stakeholders' preferences on the solution of the complementarity problem, to analyze the effect of the ISO's design parameters on the generation equilibrium quantities, and to simulate the stochastic complementarity problem using different techniques. The applications of the proposed decision-making framework include computational modeling of policy design scenarios, such as in feed-in-tariff policies. [ABSTRACT FROM AUTHOR]