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Research On Energy Management Strategy In Distributed Energy Resource Systems

Posted on:2020-06-24Degree:DoctorType:Dissertation
Country:ChinaCandidate:W F ZhongFull Text:PDF
GTID:1362330572479192Subject:Control Science and Engineering
Abstract/Summary:PDF Full Text Request
At present,the problems of environmental pollution,low energy efficiency,and poor development quality brought about by the fossil fuel-dominated energy structure are still serious in China.Promoting the revolution in energy production,transportation and consumption,and creating environmentally friendly,low-carbon,reliable and efficient energy industrial systems have become the primary mission of China's energy development reform.Traditional centralized energy supply systems have been unable to meettoday's goals of energy structure optimization and cleanliness.In contrast,distributed energy resources are increasingly used in many countries around the world due to their advantages such as high energy efficiency,low energy transmission loss,and low environmental pollution.This dissertation studies energy management strategies in distributed energy resource systems,aiming at improving the systems' operational efficiency,reliability,fault tolerance,and scalability,which has practical significance for the development of distributed energy resources.Focus on energy management issues in three typical distributed energy resource systems,namely,electric vehicle charging and discharging energy trading,real-time power control in distributed energy storage device sharing systems,and energy scheduling in multi-energy systems.The existing related research works are reviewed and their shortcomings are pointed out.Corresponding solutions are proposed.Simulation results based on real data such as electricity price,load,and solar power are given to verify the effectiveness of the proposed energy management schemes.Electric vehicles are mobile energy storage units.They can participate in demand response programs during charging,and also can provide voltage regulation and peak shaving services,which is beneficial to improve the flexibility and stability of power systems.In order to make full use of the potential dispatchable resources in electric vehicles,it is necessary to design effective energy trading mechanisms encouraging more electric vehicles to participate in electricity trading and achieving well-organized charging and discharging schedule.Chapters 2 and 3 focus on energy trading of electric vehicles.Chapter 2 proposes a two-layer electric vehicle energy trading mechanism.The VCG(Vickrey-Clarke-Groves)auction theory is used to design the upper-layer energy trading mechanism between the grid and aggregators,and the randomized auction theory is used to design the lower-layer energy trading mechanism between an aggregator and electric vehicles.This ensures the truthfulness,voluntary participation,and efficiency in the energy trading.Chapter 3 proposes an electric vehicle energy trading mechanism for active power distribution systems,which uses vehicle charging/discharging energy to regulate the grid voltage.Two types of charging/discharging energy auctions are designed for distribution networks and microgrids,respectively,which are further embedded in the ATC(Analytical target cascading)distributed framework.This guarantees the truthfulness,voluntary participation,and efficiency in the trading mechanism no matter the microgrids are in grid-connected or island mode.Electric energy storage devices are highly flexible distributed energy resources,which can be used as backup power generation or surplus electricity consumption,can be beneficial to the integration of renewable energy,and can improve energy utilization and system reliability.In order to give full play to the flexibility of energy storage devices and reduce electricity consumer cost,chapters 4 and 5 propose two new energy storage device sharing system models,respectively.Chapter 4 proposes a system model for sharing energy storage devices among households.Households without energy storage can purchase storage capacity from other households to create virtual energy storage devices.Chapter 5 proposes a new system model of distributed energy storage device sharing,in which the capacities of energy storage devices are virtualized and reallocated to users.The users only need to manage their own virtual energy storage devices without knowing the detailed control on the real storage device side.For these two scenarios,the Lyapunov optimization framework was used to design two online algorithms for real-time energy management of energy storage sharing systems,respectively.The proposed online algorithms make decisions based only on the current system states,without the need to forecast home load,solar power,and grid price.Multi-energy systems utilize various energy conversion devices and energy storage devices in the form of electricity,heating energy,and gas,which can realize the transfer of energy supply/demand among multiple energy carrier networks,thereby improving the overall energy utilization efficiency and reducing the overall operating cost.In order to improve the scalability of multi-energy systems to adapt to scenarios with a large number of plug-and-play devices,chapters 6 and 7 study distributed multi-energy scheduling.Chapter 6 proposes a distributed multi-energy trading mechanism for energy hub optimized scheduling.Using VCG auction theory and ADMM(Alternating direction method of multipliers)distributed framework,the computing tasks in energy trading are offloaded to users.At the same time,users are prevented from tampering with the trading results,and the truthfulness of the trading mechanism is ensured.Chapter 7 proposes distributed multi-energy scheduling methods that can be implemented in a non-ideal peer-to-peer communication network.A distributed Steiner tree algorithm is used to find relatively reliable communication paths in the network.The randomized ADMM distributed framework is used to enable the proposed scheduling methods to tolerate random failure of network nodes and links.
Keywords/Search Tags:Distributed energy resource, electric vehicle, energy storage device, multi-energy system, energy trading, energy scheduling
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