Article
Engineering, Electrical & Electronic
Wenjie Liu, Shibo Chen, Yunhe Hou, Zaiyue Yang
Summary: This paper studies a trilevel profit maximization problem for electric vehicle aggregators in the day-ahead reserve market with uncertain EV connectivity. The problem is transformed into a single-level mixed integer nonlinear program using total unimodularity property and other methods, and a sample-based algorithm is developed for solving it, with the effectiveness validated through case studies.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Management
Veronika Grimm, Galina Orlinskaya, Lars Schewe, Martin Schmidt, Gregor Zoettl
Summary: The study compares various flexible tariffs for prosumers' electricity management, finding that real-time pricing tariff increases retailer profits but leads to the largest price volatility for prosumers, while time-of-use and critical-peak-pricing tariffs only yield mild additional profits for retailers and uncertain revenues due to the multiplicity of optimal plans from prosumers.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Energy & Fuels
Smita Lokhande, Yogesh Bichpuriya, Ankur A. Kulkarni, Venkatesh Sarangan
Summary: With the increasing use of intermittent renewable energy sources in the electric power system, the system operator faces the challenge of maintaining the dynamic and uncertain demand-supply balance. To address this challenge, the operator procures services from balancing service providers, including energy storage system (ESS) aggregators. This study proposes a model for an ESS aggregator that can trade multiple services in ancillary service markets, contributing to maintaining the real-time demand-supply balance.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Marija Miletic, Mirna Grzanic, Ivan Pavic, Hrvoje Pandzic, Tomislav Capuder
Summary: Empowering end-users to change their behavior and providing flexibility is an important aspect of the EU Clean Energy legislative package. This paper investigates the benefits of automation and different electricity pricing options for households, as well as the impact on suppliers. The results show that automated households can reduce electricity bills through time-of-use pricing, and suppliers' revenue is mostly affected by households' local production.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Green & Sustainable Science & Technology
Xiangchu Xu, Zewei Zhan, Zengqiang Mi, Ling Ji
Summary: With the popularity of charging pile infrastructure and the development of smart devices and 5G technology, electric vehicle aggregators (EVA) can aggregate electric vehicle resources to participate in the electricity market. This paper establishes a bilevel optimization model for EVA participation in the day-ahead and intra-day electricity markets, aiming to analyze the impact on market clearing results. Based on the proposed model, simulations show that EVA's participation can improve the benefits of both EVA and ISO.
Article
Engineering, Electrical & Electronic
I. Pavic, H. Pandzic, T. Capuder
Summary: The shift from fossil fuels to renewable energy sources in the power system has led to the search for new reserve providers to ensure flexibility. Smart charging for electric vehicles has emerged as a promising solution, but there are uncertainties regarding reserve activation and EV availability. This study introduces a new method for modeling reserve activation uncertainty in European markets and demonstrates the improvement of proposed stochastic and robust models compared to deterministic approaches.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Barbara Rodrigues, Miguel F. Anjos, Valerie Provost
Summary: The article introduces an innovative business model that aggregates residential storage systems and compensates participants for using their energy storage. A realistic case study in Texas confirms the profitability of the model, highlighting the importance of setting appropriate compensation for successful implementation.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Mathematics, Applied
Teodora Dan, Andrea Lodi, Patrice Marcotte
Summary: The researchers designed an algorithmic framework based on branch-and-bound algorithm to handle mathematical programs with equilibrium constraints (MPECs) involving both integer and continuous variables. The framework was applied to a specific instance of MPEC, a competitive facility location problem taking into account the queueing process that determines the equilibrium assignment of users to open facilities, and was computationally evaluated.
SIAM JOURNAL ON OPTIMIZATION
(2021)
Article
Green & Sustainable Science & Technology
Dapeng Chen, Zhaoxia Jing, Zhigang Li, Hedong Xu, Tianyao Ji
Summary: This paper focuses on the optimal bidding strategy of a plug-in electric vehicle aggregator in the day-ahead energy market using indirect load control. By proposing relaxation methods to remove complementary constraints and Karush-Kuhn-Tucker conditions, the complexity of the model is effectively reduced, resulting in improved computational performance. Case study results demonstrate the accuracy and efficiency of the proposed relaxation methods, showing significant constraint removal and reduced computational time in various scenarios.
IET RENEWABLE POWER GENERATION
(2022)
Article
Energy & Fuels
Seong-Hyeon Cha, Sun-Hyeok Kwak, Woong Ko
Summary: With the increasing share of distributed generation, aggregators have opportunities to participate in the electricity market, contributing to the reliability of the power system through participation in the day-ahead and real-time markets. However, the uncertainty in reserve provision limits the availability of aggregated resources. Therefore, a robust optimization model is proposed for aggregators to formulate participation strategies and deploy energy control in real-time operation.
Article
Thermodynamics
Pavlos Nikolaidis, Andreas Poullikkas
Summary: The increasing share of low-carbon energy is creating reliability disturbances in modern power systems. Renewable resources are categorized into firm, variable, and uncertain based on their origin. System operators need to plan ahead for spinning reserves to cope with the impact of variable and uncertain renewables on residual load.
Article
Engineering, Multidisciplinary
Fateme Fattahi Ardakani, Seyed Babak Mozafari, Soodabeh Soleymani
Summary: This paper presents a new approach to dispatch energy and reserve in a day-ahead electricity market. A stochastic model and chance constrained optimization method are used to allocate reserve power and ensure the security of the operating point in the presence of renewable resources. The proposed model achieves lower cost for energy and reserve provision in the electricity market, as demonstrated by testing on a 24 bus IEEE test system.
AIN SHAMS ENGINEERING JOURNAL
(2022)
Article
Energy & Fuels
F. Palmiotto, Y. Zhou, G. Forte, M. Dicorato, M. Trovato, L. M. Cipcigan
Summary: This paper proposes two procedures for optimizing electric vehicle charging strategies, aiming at load profile levelling and total cost minimization, taking into account the realistic diffusion of photovoltaic systems and electric vehicles. The best compromise between the two objectives is evaluated by determining techno-economic merit indicators.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Computer Science, Software Engineering
Suresh Bolusani, Ted K. Ralphs
Summary: This paper presents a framework for reformulating and solving optimization problems, which extends the well-known framework introduced by Benders. The detailed application of this framework to multilevel/multistage mixed integer linear optimization problems provides new insights and a broader interpretation of the core ideas related to duality and value functions.
MATHEMATICAL PROGRAMMING
(2022)
Article
Management
Concepcion Dominguez, Martine Labbe, Alfredo Marin
Summary: This paper addresses the Rank Pricing Problem with Ties (RPPT) and introduces a new three-indexed integer formulation as well as two resolution approaches. Computational experiments are carried out to assess the performance of the resolution methods.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Civil
Canqi Yao, Shibo Chen, Zaiyue Yang
Summary: With the increasing popularity of electric vehicles (EV) in the transportation sector, optimizing the charging and routing process of EVs has become a popular research topic. This paper proposes a Benders decomposition based method to solve this problem, effectively decomposing it into a master problem and sub-problems for distributed implementation. The computation speed is further improved by relaxing the master problem and adding a novel kind of valid cut. The study also introduces a rolling-horizon framework to handle the uncertainty of future information. Numerical results demonstrate the algorithm's superior computation speed and capability to handle large-scale instances.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Computer Science, Information Systems
Boda Li, Ying Chen, Wei Wei, Shengwei Mei, Yunhe Hou, Shanshan Shi
Summary: Severe hurricanes in recent years have posed a significant challenge to the operation of distribution networks. This article introduces a preallocation method for electric buses (EBs) before hurricanes to enhance the resilience of fragile distribution networks. By applying a two-stage data-driven robust stochastic programming technique, the optimal preallocation strategy of EBs with minimum load losses under worst-case scenarios is explored. The results show that preallocating EBs to charging stations effectively improves the resilience of distribution networks post-hurricane.
IEEE SYSTEMS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Zhijun Qin, Xinwei Chen, Yunhe Hou, Hui Liu, Yude Yang
Summary: This study proposes a method to coordinate preventive dispatch, emergency dispatch, and restorative dispatch in transmission systems under extreme weather conditions, aiming to reduce overall loss and enhance power system resilience.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Jiazuo Hou, Shunbo Lei, Wenqian Yin, Wei Sun, Yunhe Hou
Summary: This paper investigates the cybersecurity issues in a multi-infeed high-voltage direct current (MIDC) system and proposes an event-triggered cyber-defense strategy to mitigate multiple non-simultaneous cyber-attacks.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Engineering, Electrical & Electronic
Yujia Lauren Li, Wei Sun, Wenqian Yin, Shunbo Lei, Yunhe Hou
Summary: This paper investigates the influence of cold load pickup phenomenon on load pickup decisions under the installation of distributed energy resources. A novel modeling technique is proposed to capture the decision-dependent uncertainty in the cold load pickup process. A two-stage stochastic decision-dependent service restoration model is constructed, and the efficiency of this model is verified through numerical tests. The research provides fresh insights into the monetary and secure values of uncertainty quantification.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Energy & Fuels
Yixuan Chen, Yunhe Hou
Summary: This paper proposes a novel multi-timescale multi-objective economic-environmental dispatch (MTMO-EED) method to solve the fast computation or good balancedilemma. The method includes a new framework with intra-day offline-online coordination and a new multi-objective algorithm to improve computational efficiency. Case studies on a modified IEEE 39-bus system validate the effectiveness of the proposed method.
Article
Engineering, Electrical & Electronic
Jiazuo Hou, Jun Wang, Yue Song, Wei Sun, Yunhe Hou
Summary: This paper proposes and investigates a stealthy false data injection cyber-attack targeting the small-signal angle stability (SSAS) of a power system. The attack misleads the optimal power flow (OPF) and compromises operation points, leading to damages to the SSAS margin. The paper establishes a novel bi-level model and formulates closed-form expressions to analyze the effects of the attack on the SSAS margin and operation cost. Simulation results demonstrate the significant damaging effects of the proposed attack and the conflict between the two attacking purposes.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Computer Science, Information Systems
Wenqian Yin, Shuanglei Feng, Jiazuo Hou, Chengchen Qian, Yunhe Hou
Summary: This article proposes a decision-dependent stochastic approach for the joint operation and maintenance of overhead transmission lines (OTLs) in order to determine the optimal maintenance sequence. By modeling the multi-period maintenance process of OTLs as a stochastic process with decision-dependent uncertainty, a two-stage stochastic model is formulated. A unique modeling transformation technique is adopted to tackle the coupling relation between decisions and uncertainty. Case studies verify the effectiveness of the proposed method for postsandstorm maintenance scheduling.
IEEE SYSTEMS JOURNAL
(2023)
Article
Computer Science, Information Systems
Wenqian Yin, Yujia Li, Jiazuo Hou, Miao Miao, Yunhe Hou
Summary: The global experience in wind farm development shows that the prediction error of wind power is related to the scale of wind farms due to spatial correlation. This article proposes a coordinated planning model for large-scale wind farms and energy storage that considers decision-dependent uncertainties. The model includes a DDU model and an affine function-based solution method for capturing and handling the uncertainties in wind power predictions and decisions.
IEEE SYSTEMS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Wenqian Yin, Shuanglei Feng, Yunhe Hou
Summary: This study proposes a stochastic expansion planning model for large-scale wind farms considering decision-dependent uncertainty (DDU) and investigates the coupling relationship between expansion decisions and DDU. The model is established based on the Point Estimate Method (PEM) and an iterative solution method is proposed to handle DDU. The effects of DDU on wind farm expansion schemes are analyzed and case studies validate the proposed model and solution method.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Computer Science, Information Systems
Jun Sun, Shibo Chen, Pengcheng You, Qinmin Yang, Zaiyue Yang
Summary: This article investigates the online operation of distributed data centers equipped with energy battery. We aim to minimize their long-term operational cost by optimally distributing workload among data centers and operating energy battery. However, future spatio-temporally variant uncertainties in both workload and electricity prices have been the main impediment for a performance-guaranteed online data center operation strategy. To address this issue, we develop a fully distributed online algorithm that decouples workload distribution and battery operation across the network and time by introducing well-designed virtual queues for workload and batteries into the framework of Lyapunov optimization. Theoretically, an analytical gap between the long-term operational cost achieved by our algorithm and the theoretical optimum is provided to corroborate the desirable operation strategy. Extensive simulations using the real-world workload and electricity price data demonstrate the cost-delay tradeoff that our algorithm strikes and validate the theoretical results that we obtained.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2023)
Article
Engineering, Civil
Canqi Yao, Shibo Chen, Mauro Salazar, Zaiyue Yang
Summary: This paper investigates the scheduling problem of a fleet of electric vehicles, providing mobility as a service to a set of time-specified customers. We consider incentive-aware customers and propose that the operator offers monetary incentives in exchange for time flexibility. The proposed mathematical model can reduce the delivery fees for the customers and the cost of operation incurred by the fleet operator.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Wenjie Liu, Yunjian Xu, Junhong Liu, Wenqian Yin, Yunhe Hou, Zaiyue Yang
Summary: In this article, we propose a data-driven distributionally robust energy and reserve sharing model considering renewable generation uncertainty and limited communication resources among different agents in electricity markets. We use data-driven distributionally robust chance constraints to determine the reserve capacity and employ an inner approximation approach to convert them into tractable linear constraints. We also develop a communication-censored consensus alternating direction method of multipliers to solve the sharing problem in a fully decentralized manner while considering the limited communication resources in the Internet of Things. Extensive simulations are conducted to verify the effectiveness of the proposed model and theoretical results.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Qinfei Long, Junhong Liu, Feng Liu, Yunhe Hou
Summary: To mitigate failure risk, a dynamic thermal rating (DTR) sensor can be placed in transmission lines. This paper proposes a submodular optimization-based DTR placement model that considers Braess paradox. A model based on Markov probability and important sampling weight techniques is utilized to quantify failure risk efficiently. The risk model is then applied to analyze the conditions for Braess paradox and reformulate the risk mitigation model with estimation error. A computationally efficient algorithm is designed to solve this nonmonotone submodular optimization, providing a provable approximation guarantee.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Proceedings Paper
Automation & Control Systems
Mengfan Cao, Shibo Chen, Haoyu Miao, Zaiyue Yang
Summary: This paper studies the online optimal energy management problem for building heating systems and proposes an online algorithm based on the Lyapunov optimization method to minimize long-term time average costs while meeting building temperature and TES energy level constraints.
2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC)
(2022)
