Article
Energy & Fuels
Jianing Luo, Hangxin Li, Shengwei Wang
Summary: This study proposes a novel uncertainty-based reliability assessment approach and risk quantification method for islanded microgrids, using a hotel microgrid in Hong Kong as an example. The results show that the proposed approach provides more robust reliability assessment results and identifies the highest monthly and hourly power inadequacy risks.
Article
Energy & Fuels
Ivo Horstkoetter, Philipp Gesner, Kerstin Hadler, Bernard Baeker
Summary: Understanding the degradation processes of lithium-ion cells is a current and pressing challenge, influenced by various operating conditions. Experimentation has shown that the discharge dynamics of a load profile significantly impact battery degradation, with higher current gradients resulting in larger degradation rates. This linear relationship between current gradient and degradation rate highlights the importance of considering dynamic influences in battery aging studies.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Marcos Tostado-Veliz, Hany M. Hasanien, Rania A. Turky, Yasser O. Assolami, David Vera, Francisco Jurado
Summary: Energy storage is crucial for decarbonizing the electricity sector, especially in residential installations. Home energy management applications play a vital role in enabling active control of appliances and storage systems to achieve efficient energy utilization. However, the emergence of renewable generators and electric vehicles poses challenges due to uncertainties in residential asset operation. This paper introduces a novel home energy management tool that addresses these uncertainties by using a Lexicographic-Interval formulation and prioritizing the impact of random parameters. A benchmark case study validates the proposed tool and demonstrates its ability to handle different tariffs.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Green & Sustainable Science & Technology
Bo Wang, Cuo Zhang, Chaojie Li, Peishuai Li, Zhao Yang Dong, Jason Lu
Summary: This paper proposes an adaptive BESS dispatch method with SoC interval management for unbalanced three-phase microgrids. The method dispatches BESS within the SoC interval using a rolling horizon procedure and utilizes a hybrid interval-robust optimization method to solve the scheduling problem. Simulation results demonstrate the high efficiency and solution robustness of the proposed method.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Engineering, Multidisciplinary
Seyed Amir Hosseini, Seyed Hossein Hesamedin Sadeghi, Adel Nasiri
Summary: This article proposes a decentralized adaptive scheme for protection coordination in microgrids with topological and operational uncertainties, which is carried out in two stages. The first stage involves deploying traditional fault protection, while the second stage utilizes a federation structure for negotiation among agents to determine the best protection coordination strategy in the event of single or multiple faults. The efficiency of the scheme is demonstrated through simulations and comparisons with conventional centralized and decentralized methods.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2021)
Article
Energy & Fuels
Gayan Lankeshwara, Rahul Sharma, Ruifeng Yan, Tapan K. Saha
Summary: The paper proposes a novel two-stage control algorithm for robust management of aggregate residential loads, ensuring precise load set-point tracking while preserving end-user thermal comfort. By utilizing air conditioners and water heaters as controllable loads, the study demonstrates the effectiveness of the approach in load management and mitigation of unknown uncertainties. Comparisons with existing industry approaches show that the proposed control scheme is resilient to uncertainties, maintains thermal comfort, and is practical under current demand response standards.
Article
Computer Science, Information Systems
Ibrahim M. Ibrahim, Almoataz Y. Abdelaziz, Hassan Haes Alhelou, Walid A. Omran
Summary: Battery storage units are utilized for multi-function operation in microgrids, including supply/demand matching and energy arbitrage, to maximize benefits. The optimization of the microgrid system, considering wind turbines, photovoltaic systems, diesel units, aims at minimizing costs, harmful gas emissions, and the power difference between renewable energy generation and demand. The problem is formulated as a constrained nonlinear optimization problem and solved using Moth-Flame Optimization (MFO) and Hybrid Firefly and Particle Swarm Optimization (HFPSO) algorithms. Uncertainties in parameters such as wind speed and solar irradiance are considered using Latin Hypercube Sampling (LHS) method. Different case studies are presented to validate the proposed methodology and compare the effectiveness of MFO and HFPSO algorithms in achieving the optimal solution. The optimization problem is implemented and solved using MATLAB software.
Article
Engineering, Electrical & Electronic
Yuzhou Zhou, Qiaozhu Zhai, Lei Wu
Summary: This paper proposes a new multistage generation scheduling method for regional microgrids with renewables and energy storage that can ensure robustness and nonanticipativity of scheduling solutions. A feasibility proposition and a scenario-based multistage robust scheduling model are established to address uncertainties and guarantee economic performance of scheduling results. Numerical tests demonstrate the efficacy of the proposed method.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Green & Sustainable Science & Technology
Houssem R. E. H. Bouchekara, Yusuf A. Sha'aban, Mohammad S. Shahriar, Saad M. Abdullah, Makbul A. Ramli
Summary: This paper presents an optimal design for a small-scale PV/Wind/Diesel Hybrid Microgrid System (HMS) in Yanbu, Saudi Arabia, taking into account the uncertainties of renewable energy resources and battery degradation. An Improved Decomposition Multi-Objective Evolutionary Algorithm (IMOEAD) is proposed to solve the optimization problem. The results show that the suggested approach can generate a set of solutions forming a Pareto front (PF), from which the designer can select the optimal compromise option.
Article
Energy & Fuels
Neelam Mughees, Mujtaba Hussain Jaffery, Anam Mughees, Ejaz Ahmad Ansari, Abdullah Mughees
Summary: The fourth industrial revolution is driven by the Energy Internet, which promotes the integration of industrial multi-energy microgrids and renewable energy sources. Conventional demand response schemes limit the usage of industrial users and their communication capabilities. However, smart industrial multi-energy microgrids provide additional options for meeting energy needs through the integration of diverse energy sources. This research proposes a smart Integrated Demand Response program for a novel grid-connected industrial microgrid framework.
Article
Engineering, Electrical & Electronic
Mao Yang, Yu Cui, Jinxin Wang
Summary: The grid connection of wind power and photovoltaics adds uncertainty to power system operation and scheduling, which can lead to increased operating costs and microgrid frequency fluctuations. This paper studies the effects of renewable energy uncertainty on microgrid dispatching and proposes a multi-objective optimal dispatching model and a two-step optimal scheduling method.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Pei Yong, Ning Zhang, Qingchun Hou, Yuxiao Liu, Fei Teng, Song Ci, Chongqing Kang
Summary: This paper evaluates the dispatchable capacity of backup batteries in 5G base stations and illustrates how they can be utilized to optimize the operation of power systems. The study analyzes the effects of backup batteries under different load levels and showcases the potential application of daily operation optimization.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Energy & Fuels
Saeid Ahmadi, Marcos Tostado-Veliz, Ali Asghar Ghadimi, Mohammad Reza Miveh, Francisco Jurado
Summary: Microgrids serve as an important framework for integrating renewable energy sources and demand response programs. The deployment of energy storage facilities and the use of hybrid storage systems can lead to more efficient management. Coping with uncertainties and properly modeling them is crucial for the operation of microgrids.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
S. Gupta, A. Maulik, D. Das, A. Singh
Summary: This study focuses on the optimal coordinated operation of a grid-connected AC microgrid consisting of controllable and uncontrollable power sources, battery storage units, considering plug-in hybrid electric vehicles and demand response programs. Through a nested stochastic optimization algorithm, a coordinated optimal operating strategy is proposed, which effectively reduces operating costs and system losses.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Thermodynamics
Kaile Zhou, Zhineng Fei, Rong Hu
Summary: This study proposes a hybrid robust decentralized energy management framework for the optimal day ahead scheduling of interconnected MEMGs. It utilizes a decomposition strategy based on ADMM for privacy protection and incorporates DRO and RO to effectively deal with multiple uncertainties. Experimental results show that the coordination of multiple energy carriers can significantly lower the total cost and carbon emission cost. The used ADMM owns excellent performance and comparative analysis further demonstrates the predictability and superiority of the proposed HyRO.
Article
Engineering, Electrical & Electronic
Hossein Saberi, Turaj Amraee, Cuo Zhang, Zhao Yang Dong
Summary: The paper introduces a TSCUC model using Benders Decomposition technique to ensure transient stability in power systems. The model determines committed units through a master problem and two subproblems, while also developing a method to assess system transient stability. The effectiveness of the algorithm is validated through multiple case studies.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Daichen Liu, Cuo Zhang, Guo Chen, Yan Xu, Zhao Yang Dong
Summary: The paper proposes a stochastic security-constrained optimal power flow method to address the uncertainty issue in microgrids, considering both main grid resilience and microgrid security. By reducing computing burdens, considering tie-line switching, problem decomposition, and probabilistic modeling, the method ensures robust microgrid security after tie-line switching.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Bo Wang, Cuo Zhang, Chaojie Li, Guangya Yang, Zhao Yang Dong
Summary: This paper proposes a transactive energy sharing (TES) approach for minimizing the total social cost in microgrids, considering network operating constraints. The approach utilizes an alternating direction method of multipliers (ADMM) and an adaptive robust optimization (ARO) method to address the uncertainties in the system. The simulation results confirm the efficiency and robustness of the proposed TES method.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Green & Sustainable Science & Technology
Bo Wang, Cuo Zhang, Chaojie Li, Peishuai Li, Zhao Yang Dong, Jason Lu
Summary: This paper proposes an adaptive BESS dispatch method with SoC interval management for unbalanced three-phase microgrids. The method dispatches BESS within the SoC interval using a rolling horizon procedure and utilizes a hybrid interval-robust optimization method to solve the scheduling problem. Simulation results demonstrate the high efficiency and solution robustness of the proposed method.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Engineering, Electrical & Electronic
Heling Yuan, Yan Xu, Cuo Zhang
Summary: This paper proposes a robust optimization method to address the impact of wind power generators on transient stability of a power system. By considering uncertain wind power output, coordinating generation dispatch and emergency load shedding, this method offers an effective solution.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2022)
Article
Engineering, Electrical & Electronic
Ruipeng Xu, Cuo Zhang, Yan Xu, Zhaoyang Dong, Rui Zhang
Summary: This paper proposes a multi-objective hierarchically-coordinated VVC method to maximize the benefits of inverter-based VVC. By simultaneously optimizing reactive power setpoints for central control and droop control functions for local control, the method aims to minimize average bus voltage deviation and network power loss.
IEEE TRANSACTIONS ON SMART GRID
(2022)
Article
Green & Sustainable Science & Technology
Cuo Zhang, Yan Xu, Yu Wang, Zhao Yang Dong, Rui Zhang
Summary: This paper proposes a three-stage hierarchically-coordinated VVC method considering network voltage stability to address voltage fluctuation and stability issues brought by intermittent photovoltaic power generation. The method optimizes control gains to reduce network power losses and bus voltage deviations while maintaining network voltage stability.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Engineering, Electrical & Electronic
Sara Ashfaq, Daming Zhang, Cuo Zhang, Zhao Yang Dong
Summary: To balance the operation of renewable and conventional generation, a regionalized microgrid approach is proposed. The distribution system is divided into conventional generation-based regions (CGRs) and renewable generation-based regions (RGRs), with back-to-back converters enabling bi-directional power exchange. A novel load flow algorithm is developed to solve the power flow problem considering the uncertainty of renewable distributed generators (RDGs) and loads, with a focus on frequency regulation in both types of regions. Case studies on IEEE 15, 33, and 69-bus distribution systems demonstrate the effectiveness of the proposed approach with fast convergence speed.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Automation & Control Systems
Qingmian Chai, Cuo Zhang, Ziyuan Tong, Shuai Lu, Wen Chen, Zhao Yang Dong
Summary: This article proposes a PV inverter reliability-constrained VVC method that minimizes power losses and enhances PV inverter reliability by considering uncertainties and using a power smoothing scheme.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Peishuai Li, Zaijun Wu, Cuo Zhang, Yan Xu, Zhaoyang Dong, Minqiang Hu
Summary: This paper proposes a multi-timescale affinely adjustable robust reactive power dispatch method to reduce network power losses and alleviate voltage deviations and fluctuations caused by uncertain and intermittent power outputs of PV systems. The method coordinates OLTCs, CBs, and PV inverters through a three-stage structure covering multiple timescales. The proposed method is verified through theoretical analysis and numerical simulations.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Engineering, Electrical & Electronic
Hossein Saberi, Cuo Zhang, Zhao Yang Dong
Summary: Smart buildings have potential for developing virtual energy storage systems (VESS) due to their thermal inertia and interruptible loads. However, current literature lacks advanced models to optimize VESS capacity for power system ancillary services, specifically frequency regulation services (FRS). This paper proposes a probabilistic model to quantify and optimize the VESS capacity, and develops a data-driven distributionally robust optimization (DRO) method to optimize the capacity against uncertainties. Numerical simulations validate the efficiency and performance of the proposed VESS capacity optimization method.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Thermodynamics
Lei Gan, Tianyu Yang, Bo Wang, Xingying Chen, Haochen Hua, Zhao Yang Dong
Summary: This paper proposes a three-stage coordinated operation method for steel plant-based MEMGs, aiming to minimize the total operating cost. The method considers the production demand for carbon emission reduction, and optimizes the CHP commitment and day-ahead energy transaction. A scenario-based stochastic optimization method is utilized to tackle the uncertainty of renewable generation. The results show that the proposed method can decrease the operating cost compared with the other two conventional methods.
Article
Energy & Fuels
Qingmian Chai, Cuo Zhang, Yan Xu, Zhao Yang Dong, Rui Zhang
Summary: This paper proposes a new PV inverter-based VVC optimization method and uses a Pareto front analysis to improve the inverter's lifetime. By analyzing the reliability of the vulnerable DC-link capacitor in the PV inverter, the long-term impact of VVC on inverter reliability is identified. Then, a multi-objective PV inverter-based VVC optimization model is proposed to minimize both inverter apparent power output and network power loss with a weighting factor.
Lastly, a Pareto front analysis method is developed to determine the effective weighting factor for reducing network power loss and improving inverter lifetime. The effectiveness of the proposed VVC optimization model and Pareto front analysis method is verified in a case study.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
