9 research outputs found

    Decentralized Greedy-Based Algorithm for Smart Energy Management in Plug-in Electric Vehicle Energy Distribution Systems

    Get PDF
    Variations in electricity tariffs arising due to stochastic demand loads on the power grids have stimulated research in finding optimal charging/discharging scheduling solutions for electric vehicles (EVs). Most of the current EV scheduling solutions are either centralized, which suffer from low reliability and high complexity, while existing decentralized solutions do not facilitate the efficient scheduling of on-move EVs in large-scale networks considering a smart energy distribution system. Motivated by smart cities applications, we consider in this paper the optimal scheduling of EVs in a geographically large-scale smart energy distribution system where EVs have the flexibility of charging/discharging at spatially-deployed smart charging stations (CSs) operated by individual aggregators. In such a scenario, we define the social welfare maximization problem as the total profit of both supply and demand sides in the form of a mixed integer non-linear programming (MINLP) model. Due to the intractability, we then propose an online decentralized algorithm with low complexity which utilizes effective heuristics to forward each EV to the most profitable CS in a smart manner. Results of simulations on the IEEE 37 bus distribution network verify that the proposed algorithm improves the social welfare by about 30% on average with respect to an alternative scheduling strategy under the equal participation of EVs in charging and discharging operations. Considering the best-case performance where only EV profit maximization is concerned, our solution also achieves upto 20% improvement in flatting the final electricity load. Furthermore, the results reveal the existence of an optimal number of CSs and an optimal vehicle-to-grid penetration threshold for which the overall profit can be maximized. Our findings serve as guidelines for V2G system designers in smart city scenarios to plan a cost-effective strategy for large-scale EVs distributed energy management

    Multiagent-based transactive energy framework for distribution systems with smart microgrids

    No full text

    Ethereum blockchain-based peer-to-peer energy trading platform

    No full text
    Blockchain is one of the emerging security technologies that have enormous potential in diverse sectors such as financial organization, academic institutions, national government, business sphere. In this paper, we focus on the application of blockchain systems in the energy industry addressing potential challenges and limitations in this area. The deployment of the proliferation of distributed energy resources requires an efficient and reliable transactive energy (TE) management system in terms of peer-to-peer energy trading. Independence of the energy management system from financial transactions can cause an insecure and vulnerable energy exchange environment. The proposed system design focuses on eliminating gaps in the security by the integration of decentralized application technology with the TE management and Multi-Agent System. The paper discusses the Ethereum blockchain-based peer-to-peer energy trading platform based on the enforced smart contract that controls both financial transactions and energy interchange operations for power trading systems

    State-of-the-Art Reviews and Analyses of Emerging Research Findings and Achievements of Thermoelectric Materials over the Past Years

    No full text

    Review of current high-ZT thermoelectric materials

    No full text
    corecore