Article
Energy & Fuels
Hamed Asgarian Honarmand, Ahmad Ghaderi Shamim, Hassan Meyar-Naimi
Summary: A robust optimization framework is proposed in this paper to solve the energy hub operation problem with renewable energy resources and multiple systems. The study uses a real case of a hospital building and solves the mixed-integer non-linear programming problem through multiple case studies. Results show that storage systems increase flexibility and reduce operation costs.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Energy & Fuels
Jiangyang Liu, Xu Yang, Zhongbing Liu, Juan Zou, Yaling Wu, Ling Zhang, Yelin Zhang, Hui Xiao
Summary: This paper proposes an energy utilization system for buildings in hot summer and cold winter zones, which includes cold and thermal energy storage to improve building energy flexibility. The system capacity and load demand are analyzed, and the characteristics of energy-flexibility with and without energy storage are presented.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Engineering, Electrical & Electronic
Shuning Wu, Huaqiang Li, Yang Liu, Yang Lu, Ziyao Wang, Yamei Liu
Summary: This paper presents a two-stage rolling dispatch strategy and establishes a multi-energy flow and virtual energy storage model to improve the operational economy and accuracy of scheduling results in integrated energy systems.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Elham Mokaramian, Hossein Shayeghi, Farzad Sedaghati, Amin Safari, Hassan Haes Alhelou
Summary: In this study, an energy hub system is proposed to address the economic and emission problem in power systems. Uncertainties in wind turbine, photovoltaic, load, and electricity market price are modeled with a Mont-Carlo method. A new method is introduced to model the uncertainties of electric vehicles, simplifying the uncertainty modeling process to increase system reliability. Two objective functions, economic cost, and environmental cost, are considered, and a three-step strategy is introduced to solve the multi-objective problem.
Article
Thermodynamics
Maryam Azimi, Abolfazl Salami
Summary: A novel robust-based flexibility evaluation method is proposed for multi-carrier energy systems (MCESs) to quantify the maximum potentiality of the energy hub to compensate for the maximum uncertainty. The method is implemented through a two-level optimization framework to achieve optimal and deterministic scheduling of MCESs.
Article
Energy & Fuels
Alireza Tavakoli, Ali Karimi, Miadreza Shafie-khah
Summary: This article proposes a stochastic framework for optimizing the operation of a new energy hub structure, utilizing various energy converters and electric storage. The framework models uncertainties through generating random scenarios using methods such as Monte Carlo and ARIMA. The paper compares different uncertainty modeling methods and demonstrates the effectiveness of the proposed strategy and methods through simulation results.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Thermodynamics
Xinhui Lu, Haobin Li, Kaile Zhou, Shanlin Yang
Summary: This paper proposes an optimal load dispatch model for EH system by considering the coupling relationship of electric and thermal energy, and adopts robust optimization method to deal with the uncertainty of renewable energies (REs) and demand response (DR) programs. Simulation experiments demonstrate that the total cost of EH system can be effectively reduced by installing energy storage systems and implementing DR programs.
Article
Chemistry, Multidisciplinary
Pavel Ilyushin, Dmitry Gerasimov, Konstantin Suslov
Summary: The concept of multi-energy systems (MES) is widely used in different areas of energy supply to analyze energy flows and their mutual influence. New and innovative methods, such as mathematical modeling, are employed in analyzing, forecasting, and controlling the behavior of energy facilities. This paper proposes a methodological approach based on the concept of an energy hub, which has been successfully tested on a simulation model for two energy supply channels in a real-world energy facility. This simulation-based approach offers great potential for expanding the capabilities in designing and operating integrated multi-energy systems.
APPLIED SCIENCES-BASEL
(2023)
Article
Energy & Fuels
Angela Flores-Quiroz, Kai Strunz
Summary: An integrated generation, transmission, and energy storage planning model is proposed to account for short-term constraints and long-term uncertainty, using scenario tree to represent the latter. A distributed computing framework based on Column Generation and Sharing algorithm is introduced to overcome computational burden, resulting in improved performance on the NREL 118-bus power system.
Article
Thermodynamics
Junjie Zhong, Yijia Cao, Yong Li, Yi Tan, Yanjian Peng, Lihua Cao, Zilong Zeng
Summary: A distributed synergistic model with min max-min robust optimization is proposed for a 3-block integrated energy system, which effectively handles multiple uncertainties and accelerates the solution process with the developed C&CG-AOP algorithm. The simulation results show that the constructed uncertainty set considering spatial-temporal correlation and symmetry can reduce operating costs.
Article
Thermodynamics
Mohammad H. Shams, Majid Shahabi, Mohammad MansourLakouraj, Miadreza Shafie-khah, Joao P. S. Catalao
Summary: This paper explores the short-term operation of microgrids with natural gas network using a min max min robust framework to address the challenges posed by the uncertainty of renewable resources and electrical/thermal loads. The effectiveness of the proposed model is assessed through a 21-node energy hub-based microgrid, demonstrating improved system robustness with increased budget of uncertainty and forecast error. Converting dual variables of the subproblem to primary variables allows for evaluation of unit commitment and energy dispatch results.
Article
Mathematics
Luyu Wang, Houbo Xiong, Yunhui Shi, Chuangxin Guo
Summary: This paper proposes a multi-stage robust real-time economic dispatch model (MRRTD) for power systems. The MRRTD uses the dynamic form of multi-stage robust optimization as the framework to simulate the operation of temporally coupled equipment, such as utility-level energy storage systems. The effectiveness of the proposed model and solution algorithm is demonstrated through simulation results from benchmark test cases.
Article
Computer Science, Information Systems
Xin Shen, Zhao Luo, Jun Xiong, Hongzhi Liu, Xin Lv, Taiyang Tan, Jianwei Zhang, Yuting Wang, Yinghao Dai
Summary: This study focuses on the optimal planning problem of the hybrid energy storage system (HESS) in the community multi-energy system (CMES). A two-stage stochastic planning model is proposed, leveraging thermal inertia to reduce costs, and simulation results confirm the effectiveness of the proposed method.
Article
Green & Sustainable Science & Technology
Zhongjie Guo, Wei Wei, Laijun Chen, Zhao Yang Dong, Shengwei Mei
Summary: This paper proposes two parametric optimization models to quantify the impact of power and energy capacity of energy storage units (ESUs) on renewable energy utilization. By using a severity ranking algorithm to select critical fluctuation scenarios, the proposed models can be solved by multi-parametric mixed-integer linear programs (mp-MILPs). Such a method provides analytical expressions of the impact of ESU capacity parameters and serves as a powerful tool for storage sizing.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2021)
Article
Energy & Fuels
Pieter Valkering, Andrea Moglianesi, Louis Godon, Jan Duerinck, Dominik Huber, Daniele Costa
Summary: This study presents a national-scale energy system optimization model that takes into consideration the interaction between local energy use flexibility from electric vehicle charging, battery storage, rooftop photovoltaic systems, and distribution grids. The results show that flexibility significantly reduces total system costs and enables a significant uptake of rooftop PV. However, this is dependent on a high prosumer potential.
Article
Energy & Fuels
Hedayat Saboori, Shahram Jadid
Summary: This study proposes a solution to high electricity costs and renewable energy waste by utilizing mobile charging stations, with a novel model for spatio-temporal status and battery power-energy scheduling.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Ali Azizi, Hamid Karimi, Shahram Jadid
Summary: A mixed-integer linear programming model is proposed for minimizing the total daily cost of a local multi-energy system, using neural network prediction and stochastic optimization. The model reduces the total cost of the multi-energy system by 12% in the worst-case scenario. Sensitivity analysis of loads, electricity prices, and gas prices are conducted to investigate the variables' impact on energy hub operating costs.
IET RENEWABLE POWER GENERATION
(2022)
Article
Engineering, Electrical & Electronic
Mohadese Movahednia, Hamid Karimi, Shahram Jadid
Summary: This paper proposes a cooperative game model for scheduling the day-ahead operation of multi-microgrid systems. By integrating transactions between microgrids, the model aims to achieve a global optimum for system cost. Price-based demand response is implemented to provide cost-reducing opportunities for consumers. The model incorporates data uncertainties to enhance result reliability. The study shows that implementing the cooperative model can reduce overall system cost and improve performance of individual microgrids.
ELECTRIC POWER SYSTEMS RESEARCH
(2022)
Article
Engineering, Electrical & Electronic
Kimia Parandeh, Abed Bagheri, Shahram Jadid
Summary: Nowadays, grid-connected renewable energy resources are widely used in the electricity market. To provide household consumers with photovoltaic (PV) systems, bilateral interfaces are required for energy and data exchange. Day-ahead dynamic pricing is an effective method for integrating renewable energy resources with smart grids and ensuring social welfare. Different metering mechanisms such as feed-in tariffs, net metering, and net purchase and sale play important roles in power grid operation planning. In this paper, optimal condition decomposition method is used to analyze the day-ahead dynamic pricing of grid-connected residential renewable energy resources under different metering mechanisms and carbon emission taxes. The results show that net metering and net purchase and sale mechanisms can significantly reduce total load while feed-in tariff mechanism increases social welfare without load reduction.
JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY
(2023)
Article
Energy & Fuels
Abed Bagheri, Shahram Jadid
Summary: This paper proposes a new decentralized framework for clearing both wholesale and retail electricity markets, and explores its pros and cons compared to centralized management and other schemes. The framework is based on optimality condition decomposition and complies with the liberalization rules of the EU.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Mahsa Babagheibi, Shahram Jadid, Ahad Kazemi
Summary: This study proposes a distributed locational marginal pricing strategy for congestion management in a radial distribution system with renewable-based microgrids. The results show that considering accurate load models can improve problem-solving accuracy and reduce estimation errors in energy trading and locational marginal prices.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Energy & Fuels
Ali Jani, Shahram Jadid
Summary: This paper focuses on the day-ahead and real-time transactive energy markets in the multi-microgrid system. The main purpose is to obtain an optimal schedule for the energy management of microgrids in energy markets. The proposed approach is modeled in a time frame including offline and online classes using a bi-level optimization structure. The first stage considers the day-ahead scheduling of the multi-microgrid system using game theory, where a retail market is established for transactive energy exchange between the microgrids and the microgrid community on an hourly time scale. The second stage focuses on managing the fluctuations of renewables and electricity demand on a shorter time scale and forming a real-time market in the multi-microgrid. The purpose of the second stage implementation is real-time dispatch to minimize the imbalance cost of the microgrids and the microgrid community. The simulation results show that in a cooperative space between neighboring microgrids, the total operating cost is reduced by $61.26. Moreover, this cost reduction reaches $44.05 by moving the battery energy storage systems to the level of microgrids.
Article
Energy & Fuels
Mahsa Babagheibi, Shahram Jadid, Ahad Kazemi
Summary: This paper proposes a robust model of a local flexibility market to incentivize microgrids (MGs) to provide flexibility services to relieve line congestion. The proposed market model is based on a request and response structure, adopting a modified ADMM method for negotiations. It is considered a complementary market for bilateral energy trading of MGs and a distribution system for a fairer environment. The distributed market frameworks ensure data privacy and a low computational burden.
Article
Energy & Fuels
Hamid Karimi, Shahram Jadid
Summary: This paper proposes a stochastic framework for the operation scheduling of integrated renewable-based energy microgrid systems. The proposed model presents comprehensive scheduling that simultaneously considers total generation costs, generation flexibility, and demand-side flexibility. The framework consists of three layers, with each layer targeting specific aspects of the operation management. The application of the proposed framework to a general energy system structure shows significant improvements in electrical and thermal generating flexibility.
Article
Engineering, Electrical & Electronic
Ali Sahebi, Shahram Jadid
Summary: Local energy market formation and the design of new market structures are essential due to changes in power absorption and injection caused by Multi-Energy Micro-Grids (MEMG) and combined heat and power units (CHP). Improving energy trading models can enhance the accuracy of trading schedules and system operating conditions. Robust optimization considers upstream market uncertainty and helps Distribution System Operators (DSO) trade energy with MEMGs, leading to improved energy trading in the local market. Simulation results show that real-time market uncertainty increases DSO operating costs by 16.34%, while strengthening the local energy market increases MEMGs' income by up to 44.4%. The IEEE 33-bus test system with four connected MEMGs is used for simulation.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Hamid Karimi, Shahram Jadid, Saeed Hasanzadeh
Summary: This paper proposes a techno-economic-environmental energy scheduling framework for a multi-energy microgrid system, which couples the electrical, heating, cooling, and water sections to enhance flexibility and reliability. The framework consists of three layers that focus on cost-effective operation management, environmental issues, and independence optimization. Through optimization, the independence of the multi-energy microgrid system and power losses have been significantly improved.
SUSTAINABLE PRODUCTION AND CONSUMPTION
(2023)
Article
Engineering, Electrical & Electronic
Hamid Karimi, Mahdieh Monemi Bidgoli, Shahram Jadid
Summary: This paper proposes an economic-environmental scheme for integrating the electrical, water, thermal, and cooling sections of a multi-energy system, aiming to increase efficiency and synergy in modern distribution grids. The use of industrial desalination units to provide potable water is considered, with a preference for groundwater resources due to high energy consumption. However, overuse of groundwater resources leads to various problems, such as climate changes and a lack of adequate water and food supply. Therefore, a multi-objective decision-making scheme is proposed to minimize operating costs and groundwater usage. Furthermore, thermal and electrical demand-side management, along with dispatchable and energy storage systems, are employed to address the intermittent behavior of renewable generation. The optimization results demonstrate that the proposed model reduces groundwater extraction by 26.8% with only a 1.12% increase in operating cost.
ELECTRIC POWER SYSTEMS RESEARCH
(2023)
Article
Automation & Control Systems
Mahdi Shademan, Hamid Karimi, Shahram Jadid
Summary: This paper presents a method to solve an optimization problem in the electricity distribution system using reinforcement learning and deep neural networks to protect the privacy of microgrids and improve the efficiency of the solution.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Construction & Building Technology
Mahsa Babagheibi, Ali Sahebi, Shahram Jadid, Ahad Kazemi
Summary: According to the development of CHP and HP, energy scheduling of thermal and electrical systems became more dependent on each other. New designs of Integrated Heat and Power Markets (IHPM) are proposed to use the complementary capabilities of multi-energy systems such as Energy Hubs. The proposed market structure based on the ADMM improves social welfare value and reduces operating costs.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Energy & Fuels
Hamid Karimi, Shahram Jadid
Summary: This paper proposes a day-ahead stochastic operation planning method for hybrid renewable/non-renewable multi-microgrid systems. A multi-objective tri-stage decision-making framework is utilized to optimize the operating cost, generation flexibility, and demand-side flexibility simultaneously. The proposed model considers uncertainty, cooperation, and flexibility to enhance the efficiency and capability of the multi-microgrid system.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2023)
Article
Energy & Fuels
M. Ahmadifar, K. Benfriha, M. Shirinbayan, A. Aoussat, J. Fitoussi
Summary: This study investigates the impact of innovative polymer-metal interface treatment on the reliability and robustness of hydrogen storage technology. A scaled-down demonstrator was fabricated using rotomolding to examine the mechanical characteristics, damage, and fatigue behaviors of the metal-polymer interface. The findings reveal that sandblasting treatment enhances the resilience of the interface.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
A. A. Kandil, Mohamed M. Awad, Gamal I. Sultan, Mohamed S. Salem
Summary: This paper proposes a novel hybrid system that splits solar radiation into visible and thermal components using a beam splitter and integrates a phase change material (PCM) packed bed with a PV cell. Experimental and theoretical analyses show that the hybrid configuration significantly increases the net power output of the system compared to using a PV system alone.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Jinchao Li, Ya Xiao, Shiqiang Lu
Summary: The combination of energy storage and microgrids is crucial in addressing the uncertainty of distributed wind and solar resources. This article proposes a multi microgrid interaction system with electric-hydrogen hybrid energy storage, which optimizes the system's capacity configuration to improve its economy and reliability.
JOURNAL OF ENERGY STORAGE
(2024)
Review
Energy & Fuels
Shri Hari S. Pai, Sarvesh Kumar Pandey, E. James Jebaseelan Samuel, Jin Uk Jang, Arpan Kumar Nayak, HyukSu Han
Summary: This review discusses the structure-property relationship of nickel oxide nanostructures as excellent supercapacitive materials and provides an overview of various preparation methods and strategies to enhance specific capacitance. It comprehensively analyzes the current status, challenges, and future prospects of nickel oxide electrode materials for energy storage devices.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Xiaowei Wu, Xin Dong, Ziqin Liu, Xinyi Wang, Pu Hu, Chaoqun Shang
Summary: The growth of Li dendrites in lithium metal batteries is effectively controlled by constructing a three-dimensional framework on the surface of Li using Ni(OH)2 nanosheets modified Prussian blue tubes. This method provides a homogenous Li+ flux and sufficient space to accommodate the volume change of Li, resulting in suppressed dendrite growth and improved cycling performance.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Yan-Jie Liao, Yi-Yen Hsieh, Yi-Chun Yang, Hsing-Yu Tuan
Summary: We present two-dimensional AgInP2Se6 (AIPSe) bimetallic phosphorus trichalcogenides nanosheets as anodes for advanced alkali metal ion batteries (AMIBs). The introduction of bimetallic components enhances the electronic/ionic conductivity and optimizes the redox dynamics, resulting in superior electrochemical performance. The AIPSe@G anodes achieve high specific capacity, excellent cycle stability, and rate capability in both lithium-ion (LIBs) and potassium-ion batteries (PIBs). The comprehensive full cell tests further demonstrate the stability of AIPSe@G anodes under diverse current regimes.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Chenghu Wu, Weiwei Li, Tong Qian, Xuehua Xie, Jian Wang, Wenhu Tang, Xianfu Gong
Summary: In the context of increasing global environmental pollution and constant increase of carbon emission, hydrogen production from surplus renewable energy and hydrogen transportation using existing natural gas pipelines are effective means to mitigate renewable energy fluctuation, build a decarbonized gas network, and achieve the goal of carbon peak and carbon neutral in China. This paper proposes a quasi-steady-state modeling method of a hydrogen blended integrated electricity-gas system (HBIEGS) considering gas linepack and a sequential second-order cone programming (S-SOCP) method to solve the developed model. The results show that the proposed method improves computational efficiency by 91% compared with a general nonlinear solver.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Jingcen Zhang, Zhi Guo, Yazheng Zhu, Haifeng Zhang, Mengjie Yan, Dong Liu, Junjie Hao
Summary: In this study, a new type of sensible heat storage material was prepared using low-cost steel slag as the main component, providing an effective way of recycling steel slag. By analyzing the effects of different pretreatment steel slag content and sintering temperatures on the organization and properties of heat storage materials, the study found that the steel slag heat storage material exhibited excellent performance and stability under certain conditions.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
D. Carrillo-Pena, G. Pelaz, R. Mateos, A. Escapa
Summary: Methanogenic biocathodes have the potential to convert CO2 and electricity into methane, making them suitable for long-term electrical energy storage. They can also function as biological supercapacitors for short-term energy storage, although this aspect has received less attention. In this study, carbon-felt-based MB modified with graphene oxide were investigated for their electrical charge storage capabilities. Results showed that the potential of the electrode during discharging plays a significant role in determining the charge storage capacity.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Marco Gambini, Federica Guarnaccia, Michele Manno, Michela Vellini
Summary: This paper presents an analytical assessment of the energy-power relationship for different material-based hydrogen storage systems. It explores the impact of power demand on the amount of discharged hydrogen and the utilization factor. The results show that metal hydrides have higher specific power compared to liquid organic hydrogen carriers. The study provides insights into the discharge duration and energy utilization of hydrogen storage systems.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Shujahadeen B. Aziz, Rebar T. Abdulwahid, Pshko A. Mohammed, Srood O. Rashid, Ari A. Abdalrahman, Wrya O. Karim, Bandar A. Al-Asbahi, Abdullah A. A. Ahmed, M. F. Z. Kadir
Summary: This study investigates a novel biodegradable green polymer electrolyte for energy storage. Results show that the sample with added glycerol has the highest conductivity. The primary conduction species in the electrolyte are ions. Testing confirms that the sample can withstand a voltage suitable for practical applications.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Binit Kumar, Abhishek Awasthi, C. Suresh, Yongseok Jeon
Summary: This study presents a new numerical model for effective thermal conductivity that overcomes the limitations of previous models. The model can be applied to various shapes and phase change materials, using the same constants. By incorporating the natural convection effect, the model accurately calculates the thermal conductivity. The results of the study demonstrate the effectiveness of the model for different shapes and a wide range of alkanes.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Supak Pattaweepaiboon, Wisit Hirunpinyopas, Pawin Iamprasertkun, Katechanok Pimphor, Supacharee Roddecha, Dirayanti Dirayanti, Adisak Boonchun, Weekit Sirisaksoontorn
Summary: In this study, electrode powder from spent zinc-carbon/alkaline batteries was upcycled into LiMn2O4 cathode and carbon anode for rechargeable lithium-ion batteries. The results show that the upcycled LiMn2O4 exhibits improved electrochemical performance, with higher discharge capacity compared to pristine LiMn2O4. Additionally, the recovered carbon materials show superior cycling performance. This research provides great potential for upcycling waste battery electrodes to high-value cathode and anode materials for lithium-ion battery applications.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
Pan Yang, H. D. Yang, X. B. Meng, C. R. Song, T. L. He, J. Y. Cai, Y. Y. Xie, K. K. Xu
Summary: This paper introduces a novel multi-task learning data-driven model called GBLS Booster for accurately assessing the state of health (SOH) and remaining useful life (RUL) of lithium batteries. The model combines the strengths of GBLS and the CNN-Transformers algorithm-based Booster, and the Tree-structured Parzen Estimator (TPE) algorithm is used for optimization. The study devises 10 healthy indicators (HIs) derived from readily available sensor data to capture variations in battery SOH. The random forest method (RF) is employed for feature refinement and data dimension reduction, while the complete empirical mode decomposition (CEEMDAN) method and the Pearson correlation coefficient are used for noise reduction and data point elimination in RUL prediction. The proposed model demonstrates exceptional accuracy, robustness, and generalization capabilities.
JOURNAL OF ENERGY STORAGE
(2024)
Article
Energy & Fuels
M. Arrinda, M. Oyarbide, L. Lizaso, U. Osa, H. Macicior, H. J. Grande
Summary: This paper proposes a robust aging model generation methodology for lithium-ion batteries with any kind of lab-level aging data availability. The methodology involves four phases and ensures the robustness of the aging model through a verification process.
JOURNAL OF ENERGY STORAGE
(2024)