Article
Economics
Carlos Cruz, Tarek Alskaif, Esther Palomar, Ignacio Bravo
Summary: In recent years, there has been a growing movement towards more sustainable communities driven by the increasing popularity of renewable energy and energy-efficient technologies. This paper proposes a cooperative framework for planning sustainable smart communities by integrating electricity consumers into aggregators, which redistribute consumers' demand based on available renewable energy supply. The study also investigates the different types of demand preferences and their validation through a reputation factor. Additionally, the research analyzes the current energy policy and regulations in Spain regarding demand flexibility, demand aggregation, and microgeneration capacity.
Article
Green & Sustainable Science & Technology
Yan Ding, Xiaoting Wei
Summary: A bi-level optimization model was proposed to determine a planning program for regional energy systems, with an evaluation index system established to assess operation performance. The model was verified in a real-world case study, showing the effectiveness of maximizing ground source heat pump capacity and utilizing a precooling/preheating + temperature reset strategy.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Energy & Fuels
Reza Lotfi, Nooshin Mardani, Gerhard-Wilhelm Weber
Summary: This study utilizes robust bi-level programming technique and game theory to locate renewable energy sites, demonstrating that the incorporation of uncertainties can enhance energy generation and supplier's profit. Sensitivity analysis shows that increasing uncertainty decreases generated energy but increases supplier's profit; raising the discounting rate gradually diminishes supplier's profit; as the scale of problems increases, both generated energy and supplier's profit are boosted.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
W. N. Silva, L. F. Henrique, A. F. P. da C. Silva, B. H. Dias, T. A. Soares
Summary: This paper discusses the evaluation of opportunities for producer-consumer decision-making in demand response programs with the help of optimization tools, and introduces the application of main market models and optimization techniques.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Energy & Fuels
Xin Zhao, Zhenqi Bai, Wanlei Xue, Nan Xu, Chenhui Li, Huiru Zhao
Summary: This study establishes a bi-level cooperative robust planning model considering the impact of distributed renewable energy and demand response on the distribution grid. Model verification and analysis show that considering demand response can delay investment costs, enhance load flexibility for power users, and effectively avoid issues such as load cutting.
Article
Energy & Fuels
Yu Wang, Ke Li, Shuzhen Li, Xin Ma, Chenghui Zhang
Summary: In this study, an upper-layer capacity configuration model was constructed to optimize the operating costs of compressed air energy storage systems. The heterogeneous energy network operation and China's emission reduction constraints were subsequently integrated. The KKT condition and the Big M method were used to solve the two-tier optimization problem. The comparative analysis showed that the method effectively reduced the capacity of the energy storage system and significantly improved its reliable, economic, and low-carbon operation.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Green & Sustainable Science & Technology
Vitor A. C. C. Almeida, Ricardo de A. L. Rabelo, Arthur Carvalho, Joel J. P. C. Rodrigues, Petar Solic
Summary: The study introduces a two-step approach to address the issue from both the ESP and customer's perspectives, optimizing customer load scheduling and systemwide demand profile to reduce costs and discomfort, achieving a reduction in the peak-to-average ratio of aggregate demand profile.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Green & Sustainable Science & Technology
Edstan Fernandez, M. J. Hossain, Khizir Mahmud, Mohammad Sohrab Hasan Nizami, Muhammad Kashif
Summary: This paper proposes an energy management system for a smart locality that facilitates local energy trading, and develops two optimization frameworks for optimal resource allocation and revenue maximization. The study finds that energy sharing can maximize overall revenue, and grid pricing scheme is a major factor in determining revenue sharing between entities.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Engineering, Electrical & Electronic
Hanyu Yang, Canbing Li, Ruanming Huang, Feng Wang, Lili Hao, Qiuwei Wu, Long Zhou
Summary: This paper proposes an energy trading model that incorporates a large-scale biogas plant and biogas energy storage, aiming to address the imbalance caused by increasing renewable energy sources in rural areas. The model utilizes the temperature-sensitive characteristic of anaerobic digestion and cooperates with a demand response aggregator to improve the accommodation capacity of photovoltaic generation and enhance economic performance.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Energy & Fuels
Nima Nasiri, Amin Mansour Saatloo, Mohammad Amin Mirzaei, Sajad Najafi Ravadanegh, Kazem Zare, Behnam Mohammadi-ivatloo, Mousa Marzband
Summary: This paper proposes a bi-level scheduling model for a new energy system, where multi-energy service providers (MESPs) participate in the integrated power and natural gas market. The lower level of the model considers unit commitment constraints and gas network line pack constraints, while the upper level minimizes the cost of purchasing power and natural gas through the operation of energy storage systems and demand response programs. An iterative-based two-step algorithm is developed to solve the bi-level problem, and a robust optimization method is used to capture the uncertainty of the power price determined by the market. The model is tested on a 6-bus power system integrated with a 6-node natural gas network and extended to a 118-bus power system with a 10-node gas network, demonstrating cost reduction by employing flexible energy sources.
Article
Energy & Fuels
Bo Gu, Chengxiong Mao, Dan Wang, Bin Liu, Hua Fan, Rengcun Fang, Zixia Sang
Summary: This paper proposes a two-stage stochastic energy sharing model considering photovoltaic power uncertainties, aiming to minimize the social cost of PV prosumers and community energy storage (CES) in the community. The optimization model derives the optimal schedule of the community under the worst-case scenario in the first stage, and formulates a regulation model for PV prosumers in the second stage to address PV uncertainties using demand response, charging/discharging schedule, and transactive energy schedule. Experimental results demonstrate the effectiveness of the proposed energy sharing optimization model in decreasing energy costs and validate the feasibility of multi-ports energy hub in energy sharing communities.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
Marcos Tostado-Veliz, Ahmad Rezaee Jordehi, Lazuli Fernandez-Lobato, Francisco Jurado
Summary: This paper proposes a robust energy management methodology for isolated microgrids considering hydrogen storage and demand response. The problem is solved using a nested max-min optimization framework and a master-slave scheme. The approach is applied to a benchmark microgrid, and the results show that flexible demand has a greater impact on monetary savings than hydrogen storage, reducing the total cost by 6%.
Article
Thermodynamics
Gabriele Volpato, Gianluca Carraro, Marco Cont, Piero Danieli, Sergio Rech, Andrea Lazzaretto
Summary: In this paper, the authors use Mixed-Integer Linear Programming to analyze the economic operation of energy communities and propose optimization strategies. The study finds that complementarity, cost allocation criteria, and demand-response programs have significant impacts on the economic operation of energy communities.
Article
Energy & Fuels
Meryeme Azaroual, Djeudjo Temene Hermann, Mohammed Ouassaid, Mohit Bajaj, Mohamed Maaroufi, Faisal Alsaif, Sager Alsulamy
Summary: This paper proposes an energy management strategy for power sharing between prosumers with grid-connected renewable energy systems. The optimal results are obtained using the Fmincon solver. The study considers both residential and commercial sectors and demonstrates significant cost savings and greenhouse gas emissions reductions.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2023)
Article
Chemistry, Analytical
Catia Silva, Pedro Faria, Bruno Ribeiro, Luis Gomes, Zita Vale
Summary: This paper proposes a methodology for optimally managing a community and focuses on the fairness of remuneration for community members providing flexibility. The study found that a single fair remuneration approach was more beneficial for the community manager, while considering a clustering method was more advantageous for prosumers.
Article
Green & Sustainable Science & Technology
Bo Zhou, Jiakun Fang, Xiaomeng Ai, Shichang Cui, Wei Yao, Zhe Chen, Jinyu Wen
Summary: This paper proposes a novel storage right-based hybrid discrete-time and continuous-time (HT) flexibility trading between energy storage station (ESS) and renewable power plants (RPP). The proposed method allows ESS to sell flexibility for profits and RPPs to buy flexibility to hedge power supply shortage risks. Case studies validate the effectiveness of the proposed method in achieving higher profits for ESS and lower power supply shortage risks for RPPs.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Energy & Fuels
Yunyun Wu, Jiakun Fang, Xiaomeng Ai, Xizhen Xue, Shichang Cui, Xia Chen, Jinyu Wen
Summary: This paper proposes a robust co-planning model for hybrid AC/DC transmission network and energy storage, aiming to accommodate renewable energy and avoid investment redundancy. The energy storage in the power grid improves power flow distribution and alleviates transmission congestion, postponing investment in new devices. A deterministic co-planning model is developed, and second-order cone programming (SOCP) is applied to handle the non-convexity of the model. To deal with the uncertainty of renewable energy, a robust co-planning formulation is established with the use of data-adaptive uncertainty set and the extreme scenario method. The effectiveness and superiority of the proposed model are verified through case studies on two power systems.
Article
Automation & Control Systems
Yan Lei, Yan-Wu Wang, Irinel-Constantin Morarescu, Romain Postoyan
Summary: This article investigates the fixed-time stabilization of uncertain linear time-invariant systems exhibiting two time scales using a state-feedback event-triggered controller. The authors propose an event-triggered strategy with two independent sampling mechanisms to ensure the fixed-time stability property. The effectiveness of the results is illustrated through a numerical example.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Engineering, Electrical & Electronic
Wu Yang, Shu-Ming Liang, Yan-Wu Wang, Zhi-Wei Liu
Summary: This brief study focuses on the distributed control of battery energy storage systems (BESSs) in microgrids. It proposes a control strategy based on distributed prespecified-time observers to achieve state-of-charge (SoC) balancing and power tracking for BESSs with multiple distributed heterogeneous battery units. The proposed strategy accurately estimates the average battery units' state and average desired power within a prespecified time, reducing communication costs and avoiding single-point failures.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Guan-Nan Yu, Jiang-Wen Xiao, Xiao-Kang Liu, Ze-Hong Zeng, Yan-Wu Wang
Summary: This paper investigates the consensus problem for a class of interconnected systems with different cyber-physical topologies. A two-layer control framework is proposed where two different connections exist among the systems in physical and cyber layers, respectively. Theoretical sufficient conditions for consensus are derived, and a novel expandable construction scheme is proposed for switching topologies in the cyber layer. Numerical simulation and comparison demonstrate the effectiveness of the proposed control method and its advantage in saving communication network constructions.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Construction & Building Technology
Jiang-Wen Xiao, Minghui Cao, Hongliang Fang, Jinsong Wang, Yan-Wu Wang
Summary: This paper proposes a novel multi-task learning model with a selected-shared-private mechanism to tackle the problem of short-term load forecasting for residential buildings. The model considers the spatial correlation between different buildings and achieves joint prediction for multiple buildings.
ENERGY AND BUILDINGS
(2023)
Article
Automation & Control Systems
Hongliang Fang, Jiang-Wen Xiao, Yan-Wu Wang
Summary: This paper proposes a self-training convolutional autoencoder (STCAE) framework for consumer characteristics identification with imbalance datasets. STCAE addresses the label scarcity and class imbalance problems, showing superior performance in consumer characteristics identification.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Yan Lei, Yan-Wu Wang, Xiao-Kang Liu, Irinel-Constantin Morarescu
Summary: In this work, a state feedback output regulation method is proposed based on a classical stabilizing composite state feedback controller. The method of asymptotic power series expansion is applied to provide an approximate solution to the regulator equation. A time-continuous state feedback controller is designed by combining the Chang transformation approach and the low-gain feedback technique, resulting in a semi-global bounded output regulation. Additionally, dynamic and observer-based event-triggered control schemes are proposed to reduce control updates and cater to the practical scenario of unavailable system state information.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Automation & Control Systems
Yu Zhang, Yan-Wu Wang, Xiao-Kang Liu, Wu Yang, Shu-Ming Liang
Summary: Due to the popularity of distributed generators and diversity of loads, hybrid microgrid, mixing AC/DC subgrids, has become a popular research topic. This article proposes a distributed predefined-time controller (DPTC) to achieve precise AC/DC bus voltage/frequency restoration and global power sharing among DGs in hybrid microgrid within a predefined time. The convergence time of bus voltage and output power of converters can be adjusted by a predefined parameter. Experimental tests prove the effectiveness of the DPTC in scenarios of load change and plug-and-play.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Electrical & Electronic
Hongliang Fang, Jiang-Wen Xiao, Yan-Wu Wang
Summary: The paper discusses the convenience and risks of AMI, presents a new intermittent electricity theft attack behavior, and proposes a machine learning-based detection framework. Case studies show that the presented attack can evade existing detectors and the proposed detector outperforms state-of-the-art detectors.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Jiang -Wen Xiao, Yutao Xie, Hongliang Fang, Yan-Wu Wang
Summary: Demand response is considered a promising solution for integrating renewable energy, but targeting the right customers with high potential for peak reduction remains a key challenge. This paper proposes a new deep learning-based clustering method to overcome scalability and performance issues in analyzing daily load curves. Based on the clustering results, a customer selection framework is developed that considers consumption behavior stability and peak hour characteristics. Case studies show the superiority of the proposed method and simulations demonstrate significant peak reduction from the selected customers.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Engineering, Electrical & Electronic
Lingling Le, Jiakun Fang, Xiaomeng Ai, Shichang Cui, Jinyu Wen
Summary: This paper focuses on the aggregation and scheduling of multi-chiller HVAC systems in continuous-time stochastic unit commitment to enhance the intra-hour flexibility for system operation. The continuous-time modeling method is utilized to handle the sub-hourly variability of wind power and the intra-hour flexibility of the HVAC systems. Simulation results validate the effectiveness of the modeling and aggregation for multi-chiller HVAC systems, and demonstrate the benefits of applying the continuous-time HVAC reserve provision model to enhance the flexibility for the power system operation.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Green & Sustainable Science & Technology
Xiao-Kang Liu, Jiong Cai, Lantao Xing, Yan-Wu Wang
Summary: In this paper, a distributed secondary control strategy based on quantized signals is proposed to eliminate voltage deviation of DC microgrids induced by droop control. By using quantized signals and an event-triggered mechanism, current sharing and voltage restoration can be achieved, and the communication burden and controller updating rate can be reduced.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2023)
Article
Automation & Control Systems
Yu Chen, Zhi-Wei Liu, Guanghui Wen, Yan-Wu Wang
Summary: This article addresses the real-time detection problem of multiple line outages in power systems. The proposed algorithm utilizes a distributed finite-time observer and only utilizes local measurements and information from neighboring buses for rapid detection.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Thermodynamics
Jiang-Wen Xiao, Yan-Bing Yang, Shichang Cui, Yan-Wu Wang
Summary: This paper proposes a cooperative online schedule framework to reduce the high operation costs and carbon emissions of data centers. An online algorithm based on Lyapunov optimization theory is proposed to achieve good service coordination and efficient energy coordination.
