arXiv subjects

Dongxiang Yan

Publications and source records attributed to Dongxiang Yan.

7 recordsLinked to original sources

arXiv2024

A Two-Stage Online Algorithm for EV Charging Station Energy Management and Carbon Trading

The increasing electric vehicle (EV) adoption challenges the energy management of charging stations (CSs) due to the large number of EVs and the underlying uncertainties. Moreover, the carbon footprint of CSs is growing significantly due to the rising charging power demand. This makes it important for CSs to properly manage their energy usage and ensure their carbon footprint stay within their carbon emission quotas. This paper proposes a two-stage online algorithm for this purpose, considering the different time scales of energy management and carbon trading. In the first stage, the CS characterizes the real-time aggregate EV power flexibility, in terms of upper and lower bounds on the total charging power, by a Lyapunov optimization-based online algorithm. In the second stage, the CS co-optimizes energy management and carbon trading, with EV charging power chosen within the aggregate flexibility region provided by the first stage. A generalized battery model is proposed to capture the dynamic carbon footprint changes and carbon trading. A virtual carbon queue is designed to develop an online algorithm for the second stage, which can ensure the carbon footprint of CS be within its carbon emission quota and its total operation cost is nearly offline optimal. Case studies validate the effectiveness and advantages of the proposed algorithm.

math.OC↗

arXiv2024

Hierarchical Game for Coupled Power System with Energy Sharing and Transportation System

The wide deployment of distributed renewable energy sources and electric vehicles can help mitigate climate crisis. This necessitates new business models in the power sector to hedge against uncertainties while imposing a strong coupling between the connected power and transportation networks. To address these challenges, this paper first proposes an energy sharing mechanism considering AC power network constraints to encourage local energy exchange in the power system. Under the proposed mechanism, all prosumers play a generalized Nash game. We prove that the energy sharing equilibrium exists and is socially optimal. Furthermore, a hierarchical game is built to characterize the interactions both inside and between the power and transportation systems. Externally, the two systems are engaged in a generalized Nash game because traffic flows serve as electric demands by charging behaviors, and each driver pays the energy sharing price for charging. The hierarchical game is then converted into a mixed-integer linear program (MILP) with the help of optimality conditions and linearization techniques. Numerical experiments validate the theoretical results and show the mutual impact between the two systems.

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arXiv2023

Real-time Feedback Based Online Aggregate EV Power Flexibility Characterization

As an essential measure to combat global warming, electric vehicles (EVs) have witnessed rapid growth. Flexible EVs can enhance power systems' ability to handle renewable generation uncertainties. How EV flexibility can be utilized in power grid operation has captured great attention. However, the direct control of individual EVs is challenging due to their small capacity and large number. Hence, it is the aggregator that interacts with the grid on behalf of the EVs by characterizing their aggregate flexibility. In this paper, we focus on the aggregate EV power flexibility characterization problem. First, an offline model is built to obtain the lower and upper bounds of the aggregate EV power flexibility region. It ensures that any trajectory within the region is feasible. Then, considering that parameters such as real-time electricity prices and EV arrival/departure times are not known in advance, an online algorithm is developed based on Lyapunov optimization techniques. We provide a theoretical bound for the maximum charging delay under the proposed online algorithm. Furthermore, real-time feedback is designed and integrated into the proposed online algorithm to better unlock EV power flexibility. Comprehensive performance comparisons are carried out to demonstrate the advantages of the proposed method.

math.OC↗

arXiv2023

An Online Algorithm for Combined Computing Workload and Energy Coordination Within A Regional Data Center Cluster

Regional data center clusters have flourished in recent years to serve customers in a major city with low latency. The optimal coordination of data centers in a regional cluster has become a pressing issue because of its rising energy consumption. In this paper, a Lyapunov optimization-based online algorithm is developed for the combined computing workload and energy coordination of data centers in a regional cluster. The proposed online algorithm is prediction-free and easy to implement. We prove that the workload queues and battery energy level will be within their physical limits, though their related time-coupling constraints are not considered explicitly in the proposed algorithm. The previous online algorithms do not have such a guarantee. A theoretical upper bound on the optimality gap between the online and offline results is derived to provide a performance guarantee for the proposed algorithm. To enable distributed implementation, an accelerated ADMM algorithm is developed with iteration truncation and follow-up well-designed adjustments, whereby a nearly optimal solution is attained with much enhanced computational efficiency. Case studies show the effectiveness of the proposed method and its advantages over the existing methods.

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arXiv2023

Distributed Coordination of Charging Stations with Shared Energy Storage in a Distribution Network

Electric vehicle (EV) charging stations have experienced rapid growth, whose impacts on the power grid have become non-negligible. Though charging stations can install energy storage to reduce their impacts on the grid, the conventional "one charging station, one energy storage" method may be uneconomical due to the high upfront cost of energy storage. Shared energy storage can be a potential solution. However, effective management of charging stations with shared energy storage in a distribution network is challenging due to the complex coupling, competing interests, and information asymmetry between different agents. To address the aforementioned challenges, this paper first proposes an equilibrium model to characterize the interaction among charging stations, shared energy storage, and the distribution network. We prove that the equilibrium coincides with the centralized optimization result with trading prices equaling the value of dual variables at optimum. Then, to achieve the efficient equilibrium, a distributed coordination mechanism with a prediction and a correction step is developed to guide the behaviors of different agents with proof of convergence. Numerical experiments and comprehensive performance comparisons are conducted to validate the theoretical results and show the advantages of the proposed mechanism.

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arXiv2022

Distributed Coordination of Charging Stations Considering Aggregate EV Power Flexibility

In recent years, electric vehicle (EV) charging stations have witnessed a rapid growth. However, effective management of charging stations is challenging due to individual EV owners' privacy concerns, competing interests of different stations, and the coupling distribution network constraints. To cope with this challenge, this paper proposes a two-stage scheme. In the first stage, the aggregate EV power flexibility region is derived by solving an optimization problem. We prove that any trajectory within the obtained region corresponds to at least one feasible EV dispatch strategy. By submitting this flexibility region instead of the detailed EV data to the charging station operator, EV owners' privacy can be preserved and the computational burden can be reduced. In the second stage, a distributed coordination mechanism with a clear physical interpretation is developed with consideration of AC power flow constraints. We prove that the proposed mechanism is guaranteed to converge to the centralized optimum. Case studies validate the theoretical results. Comprehensive performance comparisons are carried out to demonstrate the advantages of the proposed scheme.

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arXiv2022

A Distributed Online Algorithm for Promoting Energy Sharing Between EV Charging Stations

In recent years, electric vehicle (EV) charging station has experienced an increasing supply-demand mismatch due to its fluctuating renewables and unpredictable charging demand. To reduce its operating cost, this paper proposes a distributed online algorithm to promote the energy sharing between charging stations. We begin with the offline and centralized version of the EV charging stations operation problem, whose objective is to minimize the long-term time-average total cost. Then, we develop an online implementation approach based on the Lyapunov optimization framework. Although the proposed online algorithm runs in a prediction-free manner, we prove that by properly choosing the parameters, the time-coupling constraints remain to be satisfied. We also provide a theoretical bound for the optimality gap between the offline and online optimums. Furthermore, an improved alternating direction method of multipliers (ADMM) algorithm with iteration truncation is proposed to enable distributed computation. The proposed algorithm can protect privacy while being suitable for online implementation. Case studies validate the effectiveness of the theoretical results. Comprehensive performance comparisons are carried out to demonstrate the advantages of the proposed method.

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