Article
Operations Research & Management Science
Muer Yang, Sameer Kumar, Xinfang Wang, Michael J. Fry
Summary: This article presents an optimization model for stocking disaster relief items at strategic locations to enhance the effectiveness of humanitarian supply chain distribution networks in responding to disasters. The model provides robust solutions by addressing uncertain parameters using distribution-free uncertainty ranges, which are illustrated through a case study of hurricane preparedness in the Southeastern United States. Simulation studies further demonstrate the effectiveness of the approach in situations where conditions deviate from model assumptions.
ANNALS OF OPERATIONS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Xinyue Chang, Yinliang Xu, Hongbin Sun
Summary: This paper investigates a peer-to-peer transactive energy trading framework among prosumers in the active distribution network and proposes a vertex scenario-based robust optimization method to handle uncertainties of renewable energy. The developed model aims to minimize the overall cost of multi-energy resource owners considering power loss and incorporates various network constraints to ensure reliable and safe operation. Adoption of Nash bargaining theory in payment allocations encourages mutually beneficial and fair solutions to encourage prosumers' participation.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Xi Xiang, Tao Fang, Changchun Liu, Zhi Pei
Summary: This study proposed an optimization method for a robust service network design problem, balancing objective value and penalty violation with penalty limit constraint and robustness index. A decomposition method was introduced to solve the problem, with numerical results demonstrating the efficiency of the algorithm. The robust optimization approach was validated using real data, resulting in a robust parcel delivery network design with satisfactory out-of-sample performances.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Energy & Fuels
Xihai Zhang, Shaoyun Ge, Hong Liu, Yue Zhou, Xingtang He, Zhengyang Xu
Summary: Peer-to-peer (P2P) energy trading has economic benefits for prosumers, but the intermittency of photovoltaic (PV) poses challenges. This paper proposes a data-driven distributionally robust optimization (DRO) approach for P2P energy trading to minimize the operation cost and handle the randomness of PV generation.
Article
Engineering, Multidisciplinary
Morteza Vahid-Ghavidel, Mohammad S. Javadi, Sergio F. Santos, Matthew Gough, Behnam Mohammadi-Ivatloo, Miadreza Shafie-Khah, Joao P. S. Catalao
Summary: This study proposes a model that addresses uncertainties in the electricity market through a hybrid stochastic-robust optimization approach, and is thoroughly simulated in a real case study to demonstrate its effectiveness. The research focuses on the responsibilities of demand response aggregators and model improvements to effectively manage end-users' demand response programs.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2021)
Article
Mathematics, Applied
Zhe Zhang, Shabbir Ahmed, Guanghui Lan
Summary: This paper investigates distributionally robust two-stage stochastic optimization problems with discrete scenario support and fills the gap in existing research by reformulating the problem and developing new algorithms. The developed algorithms have low iteration complexity, can be performed in parallel if necessary, and also propose modifications for solving problems with Kantorovich ball ambiguity sets.
SIAM JOURNAL ON OPTIMIZATION
(2021)
Article
Computer Science, Artificial Intelligence
Qi Wang, Xiang He, Xu Jiang, Xuelong Li
Summary: Data clustering has attracted much attention, with various effective algorithms developed to handle the task. Non-negative matrix factorization (NMF) is considered powerful, but it has limitations in terms of sensitivity to noise and outliers. Existing graph-based NMF methods highly depend on the initial similarity graph and perform graph construction and matrix factorization separately, leading to suboptimal graph structures.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Interdisciplinary Applications
Charles Dapogny, Franck Iutzeler, Andrea Meda, Boris Thibert
Summary: This study introduces the recent paradigm of distributional robustness in shape and topology optimization. It considers the case where the probability law of uncertain physical data is approximated from observed samples, and optimizes the worst-case value of the expected cost of a design. The proximity between probability laws is quantified by the Wasserstein distance. The proposed formulation combines classical entropic regularization with convex duality theory, making the optimization problem tractable for computations. Two numerical examples demonstrate the relevance and applicability of the formulation in different design frameworks.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Engineering, Electrical & Electronic
Jiarui Zhang, Bo Wang, Junzo Watada
Summary: With the increasing penetration of intermittent renewable generation in power systems, more historical data is available. However, traditional distributionally robust optimization struggles to capture the difference and heterogeneity in historical samples, resulting in highly conservative solutions. To comprehensively characterize uncertainty, a data-driven stochastic distributionally robust optimization model for unit commitment is proposed using deep representation clustering method. Simulation results demonstrate the proposed approach's ability to strike a balance between stochastic optimization and distributionally robust optimization, reducing operation costs and hedging against perturbations.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Energy & Fuels
R. Seshu Kumar, L. Phani Raghav, D. Koteswara Raju, Arvind R. Singh
Summary: This paper proposes a three-stage stochastic EMS framework to address operational cost optimization in MG, creating solar and wind power generation profiles under uncertainties, establishing MG system configuration and operational constraints, and using quantum particle swarm optimization to achieve optimal power dispatch configuration.
Article
Computer Science, Artificial Intelligence
Yang Wang, Tao Zhou, Guanci Yang, Chenglong Zhang, Shaobo Li
Summary: This article introduces a new regularized SCN model (RSCN-INFO) based on the weighted mean of vectors to optimize the parameter selection and network structure. The proposed model utilizes a regularization term and an automatic parameter search algorithm (INFO) to dynamically adjust the training parameters. Simulation results demonstrate that RSCN-INFO outperforms other contrast algorithms in terms of parameter setting, fast convergence, and network compactness.
PEERJ COMPUTER SCIENCE
(2023)
Article
Operations Research & Management Science
Haodong Yu, Jie Sun, Yanjun Wang
Summary: A computational method is developed to solve time consistent distributionally robust multistage stochastic linear programs with discrete distribution using nested Benders decomposition. The method approximates the cost-to-go function at each node through backward steps solving conic programming problems, and generates additional trial points through forward steps. A new convergence analysis framework is established to ensure global convergence, independent of the assumption of polyhedral structure.
COMPUTATIONAL OPTIMIZATION AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Pengfei Wang, Hongyu Wang, Nenggan Zheng
Summary: This paper proposes a policy gradient method that converges to second-order stationary point policies for any differentiable policy classes. The method is computationally efficient and uses cubic-regularized subroutines to escape saddle points while minimizing Hessian-based computations. Experimental results demonstrate the effectiveness of the method.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Management
Pengyu Wei, Charles Yang, Yi Zhuang
Summary: This paper examines the optimal consumption and portfolio choice problem for ambiguity-averse investors with recursive preferences. The findings suggest that the optimal consumption strategy is more sensitive to ambiguity aversion towards diffusion risks than jump risks. Participating in the derivatives market and considering the ambiguity aversion towards diffusion risks are essential in reducing potential welfare loss, while the impact of jump misspecification is marginal.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Yi Zhang, Tian Lan, Wei Hu
Summary: This paper presents a robust optimization microgrid model based on carbon-trading mechanisms and demand-response mechanisms, aiming to enhance the low-carbon level and economic performance of microgrid systems. The findings indicate that the model can effectively reduce carbon emissions of the microgrid but also increase the operating costs. Additionally, sensitivity analysis and comparisons with other models demonstrate the advantages of the proposed model in coordinating the economy, stability, and low-carbon level of microgrid operations.
Article
Engineering, Electrical & Electronic
Wandry R. Faria, Gregorio Munoz-Delgado, Javier Contreras, Benvindo R. Pereira Jr
Summary: This paper proposes a new bilevel mathematical model for competitive electricity markets, taking into account the participation of distribution systems operators. A new pricing method is introduced as an alternative to the inaccessible dual variables of the transmission system.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Chao Zhang, Liwei Zhang, Dong Wang, Kaiyuan Lu
Summary: The load disturbance rejection ability of electrical machine systems is crucial in many applications. Existing studies mainly focus on improving disturbance observers, but the speed response control during the transient also plays a significant role. This paper proposes a sliding mode disturbance observer-based load disturbance rejection control with an adaptive filter and a Smith predictor-based speed filter delay compensator to enhance the transient speed response.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Arif Hussain, Arif Mehdi, Chul-Hwan Kim
Summary: The proposed scheme in this research paper is a communication-less islanding detection system based on recurrent neural network (RNN) for hybrid distributed generator (DG) systems. The scheme demonstrates good performance in feature extraction, feature selection, and islanding detection, and it also performs effectively in noisy environments.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Zonghui Sun, Xizheng Guo, Shinan Wang, Xiaojie You
Summary: This paper presents a status pre-matching method (SPM) that eliminates the iterative calculations for resistance switch model, and simulates all operation modes of PECs through a more convenient approach. Furthermore, a FPGA implementation scheme is proposed to fully utilize the multiplier units of FPGA.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Rui Zhou, Shuheng Chen, Yang Han, Qunying Liu, Zhe Chen, Weihao Hu
Summary: In power system scheduling with variable renewable energy sources, considering both spatial and temporal correlations is a challenging task due to the complex intertwining of spatiotemporal characteristics and computational complexity caused by high dimensionality. This paper proposes a novel probabilistic spatiotemporal scenario generation (PSTSG) method that generates probabilistic scenarios accounting for spatial and temporal correlations simultaneously. The method incorporates Latin hypercube sampling, copula-importance sampling theory, and probability-based scenario reduction technique to efficiently capture the spatial and temporal correlation in the dynamic optimal power flow problem. Numerical simulations demonstrate the superiority of the proposed approach in terms of computational efficiency and accuracy compared to existing methods.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Juan Manuel Mauricio, J. Carlos Olives-Camps, Jose Maria Maza-Ortega, Antonio Gomez-Exposito
Summary: This paper proposes a simplified thermal model of VSC, which can produce accurate results at a low computational cost. The model consists of a simple first-order thermal dynamics system and two quadratic equations to model power losses. A methodology is also provided to derive the model parameters from manufacturer data.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Jae-Kyeong Kim, Kyeon Hur
Summary: This paper investigates the relationship between the accuracy of finite difference-based trajectory sensitivity (FDTS) analysis and the perturbation size in non-smooth systems. The study reveals that the approximation accuracy is significantly influenced by the perturbation size, and linear approximation is the most suitable method for practical applications.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yuan Si, Amjad Anvari-Moghaddam
Summary: This paper investigates the impact of geomagnetic disturbances on small signal stability in power systems and proposes the installation of blocking devices to mitigate the negative effects. Quantitative evaluation reveals that intense geomagnetic disturbances significantly increase the risk of small signal instability. Optimal placement of blocking devices based on sensitivity scenarios results in a significant reduction in the risk index compared to constant and varying induced geoelectric fields scenarios.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xuejian Zhang, Wenxin Kong, Nian Yu, Huang Chen, Tianyang Li, Enci Wang
Summary: The intensity estimation of geomagnetically induced currents (GICs) varies depending on the method used. The estimation using field magnetotelluric (MT) data provides the highest accuracy, followed by the estimation using 3D conductivity models and the estimation using a 1D conductivity model. The GICs in the North China 1000-kV power grid have reached a very high-risk level, with C3 and C4 having a significant impact on the geoelectric field and GICs.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Yue Pan, Shunjiang Lin, Weikun Liang, Xiangyong Feng, Xuan Sheng, Mingbo Liu
Summary: This paper introduces the concept and model of offshore-onshore regional integrated energy system, and proposes a stochastic optimal dispatch model and an improved state-space approximate dynamic programming algorithm to solve the model. The case study demonstrates the effectiveness and high efficiency of the proposed method in improving economic and environmental benefits.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Mohammad Eydi, Reza Ghazi, Majid Oloomi Buygi
Summary: Proportional current sharing, voltage restoration, and SOCs balancing in DC microgrid control algorithms are the leading challenges. This paper proposes a novel communication-less control method using a capacitor and a DC/DC converter to stabilize the system and restore the DC bus voltage. The method includes injecting an AC signal into the DC bus, setting the current of energy storage units based on frequency and SOC, and incorporating droop control for system stability. Stability analysis and simulation results validate the effectiveness of the proposed method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Xiangjian Meng, Xinyu Shi, Weiqi Wang, Yumin Zhang, Feng Gao
Summary: With the increasing penetration of photovoltaic power generation, regional power forecasting becomes critical for stable and economical operation of power systems. This paper proposes a minute-level regional PV power forecasting scheme using selected reference PV plants. The challenges include the lack of complete historical power data and the heavy computation burden. The proposed method incorporates a novel reference PV plant selection method and a flexible approach to decrease the accumulated error of rolling forecasting.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Huabo Shi, Yuhong Wang, Xinwei Sun, Gang Chen, Lijie Ding, Pengyu Pan, Qi Zeng
Summary: This article investigates the dynamic stability characteristics of the full size converter variable speed pumped storage unit and proposes improvements for the control strategy. The research is important for ensuring the safe and efficient operation of the unit.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Firmansyah Nur Budiman, Makbul A. M. Ramli, Houssem R. E. H. Bouchekara, Ahmad H. Milyani
Summary: This paper proposes an optimal harmonic power flow framework for the daily scheduling of a grid-connected microgrid, which addresses power quality issues and ensures effective control through demand side management.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)
Article
Engineering, Electrical & Electronic
Cong Zeng, Ziyu Chen, Jizhong Zhu, Fellew Ieee
Summary: This paper introduces a distributed solution method for the multi-objective OPF problem, using a coevolutionary multi-objective evolutionary algorithm and the idea of decomposition. The problem is alleviated by decomposing decision variables and objective functions, and a new distributed fitness evaluation method is proposed. The experimental results demonstrate the effectiveness of the method and its excellence in large-scale systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2024)