Article
Energy & Fuels
Seyed Masoud Mohseni-Bonab, Innocent Kamwa, Abbas Rabiee, C. Y. Chung
Summary: This research presents a stochastic optimal transmission switching (SOTS) model that considers uncertainty to minimize grid vulnerability and risk. By using scenario reduction technique, the computational burden is alleviated in the developed model. The proposed VO-SOTS model reduces generation costs, effectively minimizes system vulnerability and risk by considering the set of critical transmission lines.
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
Energy & Fuels
Yang Yuan, Haozhong Cheng, Heng Zhang, Zheng Wang, Wei Zhou
Summary: This paper presents a novel model for transmission expansion planning with optimal transmission switching considering uncertain N-k contingency, renewables, and loads. The proposed approach utilizes ambiguity set and budget uncertainty set to simultaneously characterize the uncertainties in wind power output, load demands, and the status of generation and transmission N-k contingency. Through a three-level model, the optimal expansion plan and transmission switching can be obtained to ensure the safety and economy of the power system in worst-case scenarios. A decomposition algorithm based on benders decomposition is developed to efficiently solve the model. Case studies on the revised IEEE 30-bus test system demonstrate the effectiveness of the proposed approach in determining the optimal expansion plan and reducing total costs.
Article
Computer Science, Information Systems
S. Pinzon, D. Carrion, E. Inga
Summary: Optimal transmission switching allows for various analyses to improve electrical power system functionality, including contingency analysis to increase system flexibility through changes in network topology and power flow redirection. The research in this article focuses on the impact of transmission line switching on loadability and voltage angles, using optimal DC power flows as a mixed-integer linear program problem. Results show a small number of unviable solutions prior to implementation of switching actions, indicating the potential of applying line switching post-contingency while maintaining load and minimizing costs.
IEEE LATIN AMERICA TRANSACTIONS
(2021)
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)
Review
Computer Science, Information Systems
Muhammad Numan, Muhammad Farasat Abbas, Muhammad Yousif, Sherif S. M. Ghoneim, Alsharef Mohammad, Abdulfattah Noorwali
Summary: The integration of variable renewable energy sources into power grids has led to a more complex operating environment, requiring increased grid flexibility. Optimal transmission switching is a cost-effective technology that can alleviate network congestion and improve system reliability. However, there is currently no extensive review paper on this topic in the literature.
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
Construction & Building Technology
Marcos Tostado-Veliz, Salah Kamel, Hany M. Hasanien, Rania A. Turky, Francisco Jurado
Summary: This paper addresses the energy management issue in smart cities by developing a framework that considers energy exchanging and proposes a novel stochastic-interval model to handle uncertainties. The study validates the effectiveness of the new tool and analyzes the importance of smart devices, while also discussing other relevant aspects.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Energy & Fuels
Benxin Li, Xuan Zhang, Yumin Zhang, Yixiao Yu, Ying Zang, Xueqing Zhang
Summary: This article proposes an optimal transmission switching model based on the bus tearing method to enhance the capacity of interconnection and coordination among different areas of power systems. The model aims to improve the accommodation level of renewable energy sources and low-carbon efficiency, and achieve the coordinated operation and optimal allocation of network resources in the interconnected power grid.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Multidisciplinary Sciences
Fahad Saleh Alismail
Summary: This paper proposes a robust optimal planning strategy for addressing the challenges of optimal site selection and network expansion in modern power systems, utilizing a mixed-integer linear programming approach. The simulation results demonstrate the effectiveness of the strategy in finding the optimal size and location of ESS, as well as determining the optimal candidates and transfer capacity for tie-lines expansion planning.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2021)
Article
Energy & Fuels
Rong Li, Pingfeng Ye, Donghai Jiang, Liwei Ma, Chenhao Sun
Summary: This study proposes a multi-regional interconnected transmission network optimization method based on analytical target cascading to address the challenges brought by the increasing penetration rate of intermittent renewable energy in power systems. By investigating the reactive power regulation characteristics of renewable energy and establishing models for wind turbine and photovoltaic generation, the power system is decomposed into multiple sub-systems and an optimal transmission switching model with renewable energies is established. The analytical target cascading approach is employed to achieve coordinated optimization of the complex transmission network by decomposing the model into main and sub-problems for parallel computation. The proposed model is verified using the IEEE 14-bus and IEEE 118-bus systems, showing its effectiveness in dealing with coupling nonlinear problems and promoting renewable energy consumption.
FRONTIERS IN ENERGY RESEARCH
(2023)
Article
Energy & Fuels
Amal Nammouchi, Phil Aupke, Fabio D'Andreagiovanni, Hakim Ghazzai, Andreas Theocharis, Andreas Kassler
Summary: This paper investigates the complexity of energy management within microgrids with a large number of renewable energy sources, such as photovoltaics, and proposes a data-driven system called AIROBE that utilizes machine learning and robust optimization to address uncertainties. The impact of uncertainties on the optimality of different robust energy exchange strategies is evaluated.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Engineering, Electrical & Electronic
Saeed Akbari, Hamed Hashemi-Dezaki, Seyed Saeed Fazel
Summary: This paper presents a probabilistic clustering-based framework for the optimal operation of smart railway stations (SRSs). By using Monte Carlo Simulations (MCS) and the k-means algorithm, multiple scenarios are clustered and applied to an actual SRS. Test results show that the scenario-based method achieves a related error of less than 4.4% under real-time pricing, with significantly reduced computation time. Sensitivity analysis is also conducted to determine the impact of exchanging power constraints and ESS capacity on SRS operation.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Energy & Fuels
Mohammad Ali Taghikhani
Summary: The increasing use of electricity in households and industries, along with the environmental pollution caused by fossil fuels, emphasizes the need for renewable energy sources. This study evaluates optimal scheduling and load management of renewable resources in micro-grids, using mixed-integer linear programming and stochastic programming to address uncertainties. Results are compared with genetic algorithm, validating the effectiveness of the proposed technique.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Environmental Studies
Tuyet Thi Anh Nguyen, Shuo-Yan Chou
Summary: This paper proposes a novel approach to analyze quantitative and qualitative factors of renewable energy by integrating financial and fuzzy models. Different groups prioritize environmental, economic, and technological criteria differently, with small-scale onshore wind energy, large-scale onshore wind energy, and solar energy identified as the best options for Government, Investor, and User, respectively.
ENERGY & ENVIRONMENT
(2022)