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Reseaches On Optimal Scheduling And Control Methods For Distributed Energy Resources In Smart Grid

Posted on:2018-07-14Degree:DoctorType:Dissertation
Country:ChinaCandidate:W H ZhouFull Text:PDF
GTID:1312330518452638Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
Smart grid is a modernized power supply and demand network system, which optimally manages the power system in a real-time basis by using advanced information and communications technologies, and also enables the interactions between bidirectional power and information flows to improve efficiency and security. Compared with the centralized power generations in conventional power systems, distributed energy resources, especially renewable distributed energy resources, have advantages of environment protecting and flexibly power generating, so they will be one of the important energy sources in smart grid.However, a large number of distributed energy resources operating online will impose huge challenges on stability of the power system. How to efficiently schedule distributed energy resources and at the same time maintain dynamic stability of the power system is the context of smart grid is an essential topic in smart grid technology research. In smart grid, microgrid is a type of autonomous power system, which is able to efficiently match the local distributed energy resource supply and load demand. It is an effective solution to distributed energy resource online operation problems. Electric vehicles, as a special type of distributed energy resource, has characteristics of mobility, randomness, and low service cost. Therefore,optimal energy management for microgrids and electric vehicles is essential for improving the efficiency and flexibility of smart grid.This dissertation focuses on optimal energy management problems for microgrids and electric vehicles in the research on distributed energy resources in smart grid. The major contributions are as follows:The study on microgrid energy management consists of three main parts. (1) Firstly, a non-cooperative game based distributed power scheduling scheme is proposed for the users in a microgird. In this scheme, household users compete with each other and control loads to ensure their comfort and preference degrees and meanwhile reduce electricity costs. (2)Secondly, an adaptive dynamic programming scheme with system cost optimization for centralized energy scheduling is proposed for energy scheduling between microgrid users and distributed energy resources. In this scheme, scheduling center collects all information from user loads and renewable distributed energy resources in a microgrid, and then schedules the user load consumptions based on real-time electricity price information to reduce the microgrid power consumption costs. (3) Thirdly, considering that a microgrid has both inner power scheduling and outer power trading, a two-layer game mechanism is devised to achieve optimal and flexible microgrid energy trading. A non-cooperative game mechanism is built up among multiple households in a single microgrid. A multi-leader multi-follower Stacklberg game is adopted for energy trading among microgrids. This two-layer energy trading mechanism can greatly improve microgrid renewable utilization and decrease energy consumption cost.The electric vehicle power management study includes static and dynamic charging scenarios. (1) Firstly, an adaptive dynamic programming based centralized price control strategy is proposed for the static electric vehicle charging scenario. In this strategy,aggregator manages electric vehicles' batteries, considers power transmission constraints of the power grid, and regulates the charging demand to an expected level via price control,guaranteeing security and stability of the power grid. (2) Secondly, considering the electric vehicle dynamic charging scenario, an adaptive energy storage system control method is proposed to regulate dynamic wireless charging loads. This method jointly considers grid-side power damp rate and impact of charging/discharging on battery life in the system cost function, ensuring the two performances in the control process. (3) Thirdly, an iterative double auction algorithm is used to match power supply and demand in a wireless charging market, in which distributed energy resources act as energy sellers, and aggregators aggregating electric vehicles' charging demands act as energy buyers. Sellers and buyers offer prices according to the principle of self-utility maximization. This method can maximize total benefit while protecting private information of the sellers and buyers.Finally, the studies on the distributed energy resource scheduling and control in smart grid are summarized. Future work is also provided.
Keywords/Search Tags:Smart grid, distributed energy resource, microgrid, electric vehicle, adaptive dynamic programming, game theory
PDF Full Text Request
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