Article
Engineering, Electrical & Electronic
Lun Yang, Yinliang Xu, Hongbin Sun, Wenchuan Wu
Summary: This paper proposes a new chance-constrained OPF model that satisfies operational constraints with a given probability without assuming specific probability distributions. The joint chance constraint is decomposed into individual chance constraints using an optimized Bonferroni approximation. Different convex approximations are proposed to formulate the model as tractable forms. The proposed convex approximations can also be extended to incorporate structural information and correlation among reserve chance constraints.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Green & Sustainable Science & Technology
Yuqi Zhou, Hao Zhu, Grani A. A. Hanasusanto
Summary: This work aims to develop a robust optimal transmission switching (OTS) framework to alleviate grid congestion and reduce renewable curtailment. A two-stage distributionally robust chance-constrained (DRCC) problem is formulated to ensure limited constraint violations under any uncertainty distribution within an ambiguity set. Moment-based and distance-based ambiguity sets are utilized to obtain scalable mixed-integer linear program (MILP) formulations. Numerical experiments on test systems have demonstrated the performance improvements of the proposed DRCC-OTS approaches in terms of constraint violations and renewable curtailment reduction. The moment-based MILP approach is computationally efficient and suitable for real-time grid operations.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Automation & Control Systems
Chao Han, Yi Gu, Guohua Wu, Xinwei Wang
Summary: Agile satellites, with stronger attitude maneuvering capability, are the new generation of Earth observation satellites. Cloud coverage has a significant impact on satellite observation missions, making scheduling of multiple agile satellites complicated. Introducing cloud coverage uncertainty further increases the scheduling complexity, motivating the development of an improved heuristic algorithm for the problem.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Engineering, Chemical
Wanke Han, Tijun Fan, Shuxia Li, Liping Liu
Summary: This study proposes a new multimodal network model that considers a detour strategy and uncertainty in hazmat transportation. The study demonstrates through a case study using simulated data that changes in demand uncertainty and transit discount factor affect the total cost and risk of the multimodal hub network, thus influencing carrier's location and route decisions. The new model can effectively control and mitigate risk, making it more suitable for hazmat transportation.
JOURNAL OF LOSS PREVENTION IN THE PROCESS INDUSTRIES
(2023)
Article
Computer Science, Software Engineering
Weijun Xie, Shabbir Ahmed, Ruiwei Jiang
Summary: This paper investigates the Bonferroni approximation of distributionally robust joint chance constraints and proposes an optimized version of the Bonferroni approximation. It is shown that the optimized Bonferroni approximation is exact when the uncertainties are separable across the individual inequalities but leads to NP-hard optimization problems in certain cases. Sufficient conditions for the optimized Bonferroni approximation to be convex and tractable are derived. The paper also demonstrates how the results can be used to derive a convex reformulation of a distributionally robust joint chance constraint with a specific nonseparable distribution family.
MATHEMATICAL PROGRAMMING
(2022)
Article
Energy & Fuels
Shida Zhang, Shaoyun Ge, Hong Liu, Junkai Li, Chengshan Wang
Summary: This paper proposes a novel method to depict the feasible region for photovoltaic hosting capability in high-dimensional space, which provides explicit boundaries for feasible PV integration capacity at different integration locations. A multi-objective optimization model based on information gap decision theory is used to observe the feasible region, and active distribution network management schemes are deployed with a limited budget to improve PV hosting capability. The impact of PV output uncertainty on security constraints is addressed using data-driven Wasserstein-distance-based distributionally robust chance constraints.
Article
Computer Science, Interdisciplinary Applications
Huiran Liu, Zhiming Fang, Renjie Li
Summary: This study addresses a multimode resource-constrained project scheduling problem under hybrid uncertain environment, utilizing credibility distribution function and a hybrid algorithm for minimizing project duration and cost.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Shu-Bo Yang, Zukui Li
Summary: A kernel distributionally robust chance-constrained optimization (DRCCP) method is proposed based on the kernel ambiguity set, which is established using the kernel mean embedding (KME) and the maximum mean discrepancy (MMD) between distributions. The method formulates two different models to handle the chance constraint and is compared with the popular Wasserstein ambiguity set based approach. Numerical examples and a nonlinear process optimization problem demonstrate the efficacy of the proposed method.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Energy & Fuels
Jiaxin Cao, Bo Yang, Shanying Zhu, Chao Ning, Xinping Guan
Summary: This study proposes an energy management scheme based on distributionally robust optimization approach, which can be applied to energy hubs without accurate probability distributions and complete information, providing them with a robust optimal solution for the day-ahead market.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Eduardo S. Schultz, Simon Olofsson, Adel Mhamdi, Alexander Mitsos
Summary: This paper proposes an algorithm to calculate heuristically optimal solutions for dynamic optimization problems with path chance constraints. The uncertainty in parameters and initial conditions is modeled using Gaussian distributions, and the algorithm solves nonlinear programs generated by replacing the probability constraint with a set of approximated deterministic pointwise constraints. The algorithm demonstrates improved performance in terms of CPU time and iterations compared to using a fixed set of pointwise constraints.
COMPUTERS & CHEMICAL ENGINEERING
(2022)
Article
Automation & Control Systems
Jeremy Coulson, John Lygeros, Florian Dorfler
Summary: This article addresses the problem of finite-time constrained optimal control of unknown stochastic linear time-invariant (LTI) systems, proposing a novel data-enabled predictive control algorithm that shows strong out-of-sample performance while respecting constraints with high probability.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Operations Research & Management Science
Jia Liu, Abdel Lisser, Zhiping Chen
Summary: This paper discusses distributionally robust geometric programs with individual or joint chance constraints, considering several groups of uncertainty sets. Deterministic reformulations of the programs are found under each group of uncertainty sets. Convexity, solution methods, and relationships of the reformulation programs are discussed. Numerical tests are carried out on a shape optimization problem.
MATHEMATICS OF OPERATIONS RESEARCH
(2022)
Article
Economics
Yue Zhao, Zhi Chen, Andrew Lim, Zhenzhen Zhang
Summary: This paper studies the vessel deployment problem in the liner shipping industry and proposes a distributionally robust optimization method to address the challenge of fluctuating shipping demands. It provides high-quality solutions and extends to a data-driven model based on the Wasserstein distance.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2022)
Article
Green & Sustainable Science & Technology
Qiang Fan, Dong Liu
Summary: This paper proposes a novel Wasserstein-distance based two-stage distributionally robust chance constrained (DRCC) bidding model for virtual power plant (VPP) participating in the electricity-carbon coupled market. The uncertainties are modeled as an ambiguity set based on Wasserstein distance, in which the two-sided chance constraints are guaranteed satisfied. A reformulation approach based on strong duality theory and conditional value-at-risk (CVaR) approximation is proposed to transform the DRCC problem into a tractable mixed-integer linear programming (MILP) framework. Case studies are carried out to verify the effectiveness and efficiency of the proposed approach on the IEEE 30-bus system.
IET RENEWABLE POWER GENERATION
(2023)
Article
Engineering, Chemical
Shu-Bo Yang, Zukui Li
Summary: This work proposes a novel distributionally robust chance-constrained optimization method based on the Sinkhorn ambiguity set. The proposed method can handle more general families of uncertainty distributions than the Wasserstein-based methods. It formulates the problem as a tractable conic model using the CVaR approximation and the discretized kernel distribution relaxation. Compared to the Wasserstein-based approaches, the presented Sinkhorn DRCCP is a more practical method that can handle a wider range of uncertainty constraints.
Article
Economics
Ningwen Tu, Dimas Adiputranto, Xiaowen Fu, Zhi-Chun Li
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2018)
Article
Engineering, Civil
Zhi-Chun Li, Qian Liu
Article
Economics
Ya-Ting Peng, Zhi-Chun Li, Paul Schonfeld
TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE
(2019)
Article
Economics
Dian Sheng, Zhi-Chun Li, Xiaowen Fu
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2019)
Article
Economics
Zhi-Chun Li, Qiao-Yu Wu, Hai Yang
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2019)
Article
Transportation Science & Technology
Dian Sheng, Qiang Meng, Zhi-Chun Li
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2019)
Article
Economics
Jinyan Sang, Zhi-Chun Li, William H. K. Lam, S. C. Wong
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2019)
Article
Economics
Zhi-Chun Li, Liping Zhang
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2020)
Article
Operations Research & Management Science
Tingsong Wang, Yuquan Du, Debin Fang, Zhi-Chun Li
TRANSPORTATION SCIENCE
(2020)
Review
Economics
Zhi-Chun Li, Hai-Jun Huang, Hai Yang
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2020)
Article
Transportation Science & Technology
Zhijia Tan, Min Xu, Qiang Meng, Zhi-Chun Li
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2020)
Article
Economics
Baoli Liu, Zhi-Chun Li, Dian Sheng, Yadong Wang
Summary: This paper proposes a mixed-integer linear programming model for integrated planning of berth allocation and vessel sequencing in a one-way navigation channel seaport. Numerical experiments show that the integrated planning model can significantly reduce vessels' dwelling time, and the proposed adaptive large neighborhood search algorithm outperforms existing methods in solving all problem instances.
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2021)
Article
Transportation Science & Technology
Khoa D. Vo, William H. K. Lam, Zhi-Chun Li
Summary: This paper presents a novel household-oriented activity-based mixed-equilibrium model for estimating individual and household activity-travel choices in multimodal transportation networks with interactions between private car and public transit modes. The model utilizes a logit-based stochastic choice model to capture mixed equilibrium, converting the time-dependent activity-travel scheduling problem into an equivalent static traffic assignment problem. The conditions for the existence and uniqueness of a solution to the equivalent variational inequality problem for joint activity-travel paths are also identified.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Transportation Science & Technology
Zhi-Chun Li, Wen-Jing Liu, Xiao-Yan Wang
Summary: This paper investigates the effects of introducing women-only parking spaces on drivers' parking behavior and operator's investment behavior. The study finds that gender, driving age, vehicle length, and parking environment significantly impact the time taken to complete the parking process. Women-only parking spaces can help reduce this time. However, investing in women-only parking spaces may lead to a loss in net profit for operators, so careful decision-making is necessary.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Economics
Ningwen Tu, Zhi-Chun Li, Xiaowen Fu, Zheng Lei
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2020)