Article
Energy & Fuels
Rafael S. Pinto, Clodomiro Unsihuay-Vila, Fabricio H. Tabarro
Summary: This paper proposes a robust model to solve the coordinated operation and expansion planning of active distribution networks with multiple microgrids, DERs, demand response, and generation contingency. By using a contingency-constrained approach, it aims to determine the best expansion planning proposals and optimal daily operation for DERs under uncertainties. The results show a decrease in total cost and improved reliability index with coordinated operation and inclusion of contingencies.
Review
Green & Sustainable Science & Technology
Abdollah Rastgou
Summary: This study provides a comprehensive investigation of the distribution network expansion planning (DNEP) problem, examining various aspects such as objective functions, constraints, design variables, and addressing issues like uncertainty, distributed generation, and storage. Future research directions, including conflict resolution and solving approaches, are also suggested.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2024)
Article
Engineering, Electrical & Electronic
Tao Ding, Ming Qu, Can Huang, Zekai Wang, Pengwei Du, Mohammad Shahidehpour
Summary: This paper introduces a multi-period active distribution network planning (ADNP) method with distributed generation (DG) to minimize total planning cost while considering DG uncertainties. It utilizes a multi-stage stochastic optimization model and a nested decomposition method to address computational challenges, and its effectiveness is verified on practical distribution systems.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Sarah Allahmoradi, Mohsen Parsa Moghaddam, Salah Bahramara, Pouria Sheikhahmadi
Summary: This study proposes a solution to the flexibility-constrained operation problem in distribution networks by reducing the ramp-rate of purchased power from the market by distribution companies, which enhances system stability and reliability. The effectiveness of the proposed model is demonstrated in a test network with three microgrids, showing a successful decrease in the ramp-rate of purchased power.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Ali Rajaei, Sajjad Fattaheian-Dehkordi, Mahmud Fotuhi-Firuzabad, Moein Moeini-Aghtaie, Matti Lehtonen
Summary: The paper proposes a distributed operational management model for multi-agent distribution systems, considering uncertainties of each agent, using ADMM to coordinate operational scheduling and robust optimization technique for worst-case realization. The framework is implemented on the IEEE 37-bus network and analyzed for its efficacy in distributed robust operational management of distribution systems with multi-agent structures.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Thermodynamics
Arian Khaledi, Amirali Saifoddin
Summary: Increasing energy demand and industrialization are the main causes of climate change, leading to more natural disasters and power outages. Climate change mitigation should be a global goal, and rapid system restoration after natural disasters is essential. Energy resilience is a multi-dimensional solution to this problem.
Article
Chemistry, Multidisciplinary
Dimitra G. Kyriakou, Fotios D. Kanellos
Summary: In this paper, an optimization method was developed to facilitate the sustainable operation of active distribution networks by integrating smart residential building prosumers, plug-in electric vehicle aggregators, and renewable energy sources. The method effectively reduced the operational cost by 17% while ensuring all operational limitations were met.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Multidisciplinary
Wei Jin, Shuo Zhang, Jian Li
Summary: The development of active distribution networks (ADN) with a high proportion of renewable energy, driven by the energy crisis and environmental concerns, poses challenges to power system operation. Network reconfiguration is used in the planning stage to enhance the adjustable capacity of the power system and promote the consumption of renewable energy. A robust optimization model considering network reconstruction and distributed power generation in ADN is proposed, incorporating a wind-light-load uncertain scenario set to address uncertainty. The influence of network reconfiguration on DG planning, economy, and reliability of ADN is analyzed through simulation, validating the model.
APPLIED SCIENCES-BASEL
(2023)
Article
Thermodynamics
Yang Li, Bo Feng, Bin Wang, Shuchao Sun
Summary: This paper proposes a joint planning model for distributed generations (DGs) and energy storage in an active distribution network. The model utilizes a bi-level programming approach to optimize the location, capacity, and operation of DGs and energy storage. By using an improved binary particle swarm optimization algorithm, the optimal joint planning is achieved, reducing planning deviation and improving the performance of distribution systems.
Article
Engineering, Electrical & Electronic
Mariana Simoes Noel da Silva, Delberis A. Lima
Summary: The paper proposes an optimization model for a day-ahead operation of an unbalanced distribution system with photovoltaic distributed generation penetration, considering the application of Conservation Voltage Reduction technique in different approaches to minimize energy consumption at the substation. The results suggest that the robust approach is better for utilities to save energy and reduce power demand due to its conservative nature towards voltage violations and lower computational burden.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Computer Science, Information Systems
Zhichun Yang, Ji Han, Li Li, Yuting Deng, Fan Yang, Yang Lei, Huaidong Min, Wei Hu, Lei Su
Summary: This paper proposes an islanding operation and fault recovery strategy for distribution networks, considering the uncertainty of new energy sources. The proposed method involves the establishment of islanding division and operation models, as well as a fault recovery model. It also addresses the issue of uncertainty by combining scenario generation reduction methods and second-order cone programming theory. Experimental results demonstrate the feasibility and effectiveness of the proposed method in both the islanding division and fault recovery stages.
Article
Energy & Fuels
Praveen Agrawal, Neeraj Kanwar, Nikhil Gupta, K. R. Niazi, Anil Swarnkar
Summary: This paper proposes a three-stage Self-healing Algorithm (SHA) to enhance the resiliency of distribution systems, efficiently restoring maximum priority loads during blackout with multiple line faults while maintaining system efficiency and reliability. The algorithm transforms faulty distribution network into an augmented FDN (AFDN) for load flow and mesh checks, maximizing prioritized loads while considering power balance and operational constraints. Experimental results demonstrate the effectiveness of the proposed method in handling various line faults.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Engineering, Electrical & Electronic
Pushpendra Singh, S. K. Bishnoi
Summary: This article proposes a novel bi-layer optimization model to maximize the renewable power hosting potential of an active distribution network, using a modified version of the MFO algorithm to address multiple objectives and ancillary service challenges effectively.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
Yanhong Luo, Qiubo Nie, Dongsheng Yang, Bowen Zhou
Summary: With the increasing penetration of distributed energy, a new robust optimal operation method based on the minimum confidence interval of distributed energy Beta distribution is proposed in this paper to address the challenges faced by traditional distribution network optimization models in ensuring stable and efficient operation. The method includes establishing an ADN model with second-order cone, analyzing historical data of distributed energy, obtaining the minimum confidence interval, and solving a two-stage robust optimization model for ADN, resulting in more stable and efficient operation compared to traditional methods.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2021)
Article
Computer Science, Information Systems
Guodong Liu, Thomas B. Ollis, Maximiliano F. Ferrari, Aditya Sundararajan, Yang Chen
Summary: This paper proposes a distributed energy management method for modern distribution systems, which can coordinate the operation of various active participants to achieve better economics and/or preferred performances. Through iterative solving of a multi-objective optimization model using ADMM algorithm, the method adjust participants' schedules and update price signals in a distributed way, ultimately achieving power balance.
Article
Chemistry, Physical
Gang Wu, Ting Li, Weiting Xu, Yue Xiang, Yunche Su, Jiawei Liu, Fang Liu
Summary: This paper presents an optimal energy-reserve scheduling model for wind-photovoltaic-hydrogen integrated energy systems with multi-type energy storage devices. The model considers the impact of renewable and load uncertainties on reserve constraints using chance-constrained programming theory. An improved discretized step transformation method is proposed to convert the non-convex CCP problem into a solvable mixed integer linear programming formulation. Additionally, a critical threshold value selection approach is developed to reduce constraints and improve solution efficiency. Case studies show that the proposed model reduces operating costs while ensuring system safety. The combined method of improved discretized step transformation and critical threshold value selection reduces computational burden and improves scheduling accuracy.
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
(2023)
Article
Energy & Fuels
Xiangyu Wei, Yue Xiang, Junlong Li, Junyong Liu
Summary: This paper proposes a coordinated bidding/operation model for wind farms to improve their benefits in the electricity market. The maximum entropy based deep reinforcement learning algorithm is used to construct the model, and the learned strategy effectively enhances the wind farm benefits while ensuring robustness.
Article
Energy & Fuels
Jianping Yang, Yue Xiang, Wei Sun, Junyong Liu
Summary: This paper analyzes the investment benefit mechanism directly from the perspective of investment input-output relationship, designs an interactive auxiliary investment decision-making system based on correlation rule mining, and provides decision makers with assistance in formulating investment alternatives.
Article
Energy & Fuels
Yongtao Guo, Yue Xiang
Summary: This study proposes an optimal planning model for a wind-photovoltaic-hydrogen storage-integrated energy system, aiming to minimize both economic and environmental costs. Case studies and sensitivity analysis are conducted to demonstrate the potential benefits of hydrogen investment in reducing carbon emissions.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Computer Science, Information Systems
Shijie Chen, Yue Xiang, Wei Sun, Junyong Liu
Summary: The study proposes a scenario-based bilevel mathematical model using a Bayesian integrated optimization method to evaluate and quantify the connectable capacity of distributed wind generation. The innovative constraint on the generation curtailment ratio (CR) and integration with network security constraints effectively combine the characteristics of wind power and local policies. Practical cases verify the effectiveness of the method, showing that it is more efficient than traditional optimization algorithms while ensuring compliance with local renewable energy development policies.
IEEE SYSTEMS JOURNAL
(2022)
Article
Green & Sustainable Science & Technology
Xiangyu Wei, Yue Xiang, Junlong Li, Xin Zhang
Summary: This paper presents a self-dispatch model based on deep reinforcement learning for wind-storage integrated system (WSS) in real-time market (RTM). The model is able to learn the bidding and charging policy of WSS from historical data and uses the Ape-X framework to improve efficiency and performance. With the maximum entropy framework, the model can explore optimal possibilities considering the uncertainty of wind power and electricity price, bringing more benefits to wind farms.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Energy & Fuels
Yongtao Guo, Yue Xiang
Summary: With the promotion of renewable energy utilization and the trend of a low-carbon society, the real-life application of photovoltaic (PV) combined with battery energy storage systems (BESS) has thrived recently. An optimization model is proposed for evaluating sizing, operation simulation, and cost-benefit of the PV-BESS integrated energy systems. The simulation results demonstrate the feasibility and effectiveness of the proposed model in an industrial area. Furthermore, the cost-benefit analysis reveals the cost superiority of PV-BESS investment compared with the pure utility grid supply.
Article
Energy & Fuels
Huawei Chao, Gang Wu, Ting Li, Weiting Xu, Jiakun Dai, Yue Xiang
Summary: This study proposes a method of combining Grey relational analysis (GRA), artificial neural network (ANN), and XGBoost algorithm for the potential assessment of clean energy stations. The method involves analyzing the relationship between the output of clean energy stations and meteorological factors using GRA and ANN. It also uses historical data and high correlated meteorological factors to predict the future outputs of new clean energy stations via XGBoost. The proposed method includes an assessment method based on predicted output and evaluation indicators such as available capacity coefficient (AOC).
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Haotian Yao, Yue Xiang, Junyong Liu
Summary: This paper addresses the planning framework of non-utility-owned distributed generators (DGs), considering multiple investment strategies from the perspective of risk and profit. The autonomous planning and operation strategy and leasing planning and operation strategy are proposed to deal with the different ownership and pricing mechanism of DG investment/operation rights. The conditional value at risk is adopted to manage the risk in profit, and the decentralized optimization approach is used to solve the planning problem.
Article
Engineering, Multidisciplinary
Mengqiu Fang, Yue Xiang, Bohan Xu, Tianhao Wang, Li Pan, Youbo Liu, Junyong Liu
Summary: This article proposes a complete framework for load pattern identification, which consists of clustering and classification modules, to mine and analyze massive residential power consumption information. By introducing multi-dimensional scaling and an innovative mixture model, better clustering and classification performance are achieved.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Multidisciplinary
Bohan Xu, Yue Xiang, Junyong Liu, Youbo Liu, Li Pan, Mengqiu Fang, Tianhao Wang
Summary: This article introduces an agent-based var-voltage control capability to improve the economic scheduling efficiency of integrated energy systems and proposes a deep learning-enabled surrogate model to solve the scheduling problem. The results demonstrate that the proposed method can effectively and accurately meet safety constraints and reduce the operational costs of the system.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Engineering, Electrical & Electronic
Junlong Li, Chenghong Gu, Xiangyu Wei, Ignacio Hernando Gil, Yue Xiang
Summary: This paper proposes a dark-grey box method for dwelling thermal modelling, based on an edge computing system. The method achieves high accuracy by integrating time-varying features and utilizing both physical and machine-learning models.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Engineering, Electrical & Electronic
Wenxule Chen, Yue Xiang, Junyong Liu
Summary: The shared energy storage mode provides a solution to promote renewable energy utilization, and enables mutually beneficial cooperation among multiple virtual power plants.
Review
Engineering, Electrical & Electronic
Junlong Li, Chenghong Gu, Yue Xiang, Furong Li
Summary: This paper extensively reviews the application of edge computing-cloud computing system in the smart grid, providing theoretical basis, architecture, and discussing its application in the entire supply chain. Furthermore, future research opportunities and challenges are outlined for applying this technology to the smart grid.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2022)
Article
Energy & Fuels
Shuai Zhang, Yue Xiang, Junyong Liu, Jichun Liu, Jingxian Yang, Xu Zhao, Shafqat Jawad, Jing Wang
Summary: This study focuses on the cascaded hydro-PV-PSH joint power system and proposes a rule-based method for determining the regulating capacity. Through the use of statistical techniques and a continuous cyclic revision method, the study achieves the constraint and configuration of PV system's fast fluctuations. The experimental results verify the feasibility and effectiveness of the proposed method, and provide a PV and PSH regulating capacity configuration that meets real-time application requirements.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2022)
