Article
Thermodynamics
Taiheng Zhang, Hongbin Zhao, Huicheng Du, Heng Wang
Summary: This paper proposes a new cogeneration system using a combination of various technologies to address the imbalance of grid supply and demand, optimizing system efficiency. Simulation results show that the combined system has excellent performance and improved electrical efficiency.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Engineering, Electrical & Electronic
Amirhossein Benyaghoob-Sani, Mostafa Sedighizadeh, Davoud Sedighizadeh, Rezvan Abbasi
Summary: The study focuses on a model for Energy Hub (EH) in Microgrid (MG) to optimize the operation. The goal is to minimize operational and environmental costs with various dispatchable and non-dispatchable generations of energy, along with different energy storage systems considered.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Energy & Fuels
Sepideh Sarmast, Roydon A. Fraser, Maurice B. Dusseault
Summary: This study investigates a novel small-scale, site-flexible cased-wellbore compressed air energy storage (CW-CAES) system that can store both heat and mechanical energy, improving system efficiency. Analysis using numerical and semi-analytical models shows that the modeled partial adiabatic CW-CAES has a round-trip efficiency of around 40%, which increases with more charge/discharge cycles.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Thermodynamics
Fuqiong Lei, David Korba, Wei Huang, Kelvin Randhir, Like Li, Nick AuYeung
Summary: The study explores the potential of combining thermochemical and sensible energy storage for Compressed Air Energy Storage (CAES) applications. By developing a mathematical model and analyzing the performance of TCES-rock-filled PBTES systems, it is found that similar round-trip efficiency can be achieved with different materials and design modifications, leading to improved stability. Furthermore, the concept could potentially improve the roundtrip efficiency, have longer storage duration, and stable turbine air inlet temperature under suitable operating conditions, especially with future advanced materials.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Morteza Saleh Kandezi, Seyed Mojtaba Mousavi Naeenian
Summary: By combining compressed air energy storage with concentrated solar power and absorption chiller, this novel concept not only addresses environmental issues, but also generates power, cooling capacity, and hot water, reducing peak energy demand.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Jacek S. Leszczynski, Dominik Grybos, Jan Markowski
Summary: This paper presents the unique design and processing conditions of a micro-CAES device that generates, stores and delivers electrical energy with highly efficient total energy conversion. The focus is on the control and efficiency of the post-preparation section and the expansion section of the device. The use of multiple reciprocating engines and thermal energy storage enhances the controllability and performance of the expansion process. Mathematical modeling and experimental data are used to validate the performance and reliability of the device, and sensitivity analysis is performed to determine the optimal operating conditions.
Article
Energy & Fuels
Mehdi Jalili, Mostafa Sedighizadeh, Alireza Sheikhi Fini
Summary: This paper investigates the optimization model for energy hub in a microgrid, aiming to minimize operational and environmental costs, manage dispatchable and nondispatchable generations, as well as energy storage systems under various technical constraints. The study shows that using a novel solar-powered compressed air energy storage system can improve the efficiency of energy hub operation and reduce environmental costs.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Engineering, Electrical & Electronic
Seyyed Aliasghar Ghappani, Ali Karimi
Summary: This paper aims to ensure the optimal operation of an energy hub (EH) to meet electrical, thermal, and hydrogen demands, considering the issues of pollutant emission and operating costs. In the proposed structure for the EH, a solid oxide fuel cell (SOFC) converter with ammonia fuel is used, and thus a combined hydrogen, heat, and power (CHHP) system is formed. The proposed economic-environmental framework for the operation of the EH is multi-objective as a stochastic mixed-integer linear programming (MILP).
IET GENERATION TRANSMISSION & DISTRIBUTION
(2023)
Review
Green & Sustainable Science & Technology
Zheming Tong, Zhewu Cheng, Shuiguang Tong
Summary: China has become a leader in renewable energy production to reduce greenhouse gas emissions, utilizing Compressed Air Energy Storage (CAES) to tackle the intermittency of renewable sources. Promoting electricity trading markets could enhance CAES arbitrage in high-consumption areas, while integrating CAES with renewable energy generation reveals significant economic and environmental benefits.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Danman Wu, Wei Wei, Jiayu Bai, Shengwei Mei
Summary: This paper studies the strategic behavior of an AA-CAES based energy hub in deregulated electricity and heat markets, and proposes a special decomposition method to compute the market equilibrium. Case studies verify the proposed model and method.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Thermodynamics
Mohamad Cheayb, Dean Chalmers, Ward De Paepe, Ahmad Hajjar, Sebastien Poncet
Summary: Decarbonization objectives in industrial processes require changes in industrial energy supply. A new method combining steady state and dynamic approaches is developed to solve the optimal conceptual design problem of cogeneration plants. By breaking down the electricity and thermal cost, energy prices of different decarbonization solutions are mapped.
ENERGY CONVERSION AND MANAGEMENT
(2023)
Article
Thermodynamics
Amir Reza Razmi, M. Soltani, Armin Ardehali, Kobra Gharali, M. B. Dusseault, Jatin Nathwani
Summary: A CAES facility proposed for wind farms in Iran helps stabilize power generation by storing wind energy during peak demand hours, with higher wind speeds recorded in July. The facility contributes stored power to the grid with round trip efficiencies of 52%, 47%, and 43% in July, August, and September.
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
Energy & Fuels
Amir Ghazvini, Mostafa Sedighizadeh, Javad Olamaei
Summary: This paper introduces a mathematical optimization approach based on semidefinite programming for optimal operation of a microgrid equipped with renewable energy resources and energy storage systems. It formulates an optimization problem to minimize costs related to operation and environmental effects, while overcoming the deviation between predicted and actual uncertainty variables. By incorporating risk averse strategy, the presented model shows a 3.8% reduction in total costs compared to not considering energy storage systems in the day-ahead optimal operation.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Thermodynamics
Shadi Bashiri Mousavi, Mahdieh Adib, M. Soltani, Amir Reza Razmi, Jatin Nathwani
Summary: This article presents a novel, efficient, and green adiabatic compressed air energy storage system based on a cascade packed bed thermal energy storage to address the challenges of renewable energy generation variability, aiming at improving system performance and efficiency.
ENERGY CONVERSION AND MANAGEMENT
(2021)
Article
Energy & Fuels
Seyed Amir Mansouri, Ahmad Rezaee Jordehi, Mousa Marzband, Marcos Tostado-Veliz, Francisco Jurado, Jose A. Aguado
Summary: This study proposes a hierarchical decentralized framework for the simultaneous management of electricity, heat and hydrogen markets, integrating smart prosumers and multi-energy microgrids. By utilizing deep learning forecasting and a risk-averse information gap decision theory, the model reduces the clearing prices of electricity and heat during peak hours. Furthermore, the introduced structure for hydrogen exchange through the transportation system has the potential to be implemented in competitive markets.
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
Flavio Trojan, Pablo Isaias Rojas Fernandez, Marcio Guerreiro, Lucas Biuk, Mohamed A. Mohamed, Pierluigi Siano, Roberto F. Dias Filho, Manoel H. N. Marinho, Hugo Valadares Siqueira
Summary: This paper compares the multi-criteria method ELECTRE TRI with clustering algorithms to define initial thresholds for the ELECTRE TRI method. The results show that the Fuzzy C-Means algorithm is more suitable for achieving the desired response. This study provides a relevant procedure for defining initial boundaries in multi-criteria sorting methods based on datasets from specific applications, and it is a new development in pre-defining the initial limits of classes for the sorting problem in multi-criteria approaches.
Article
Computer Science, Information Systems
Amin Mansour Saatloo, Mohammad Amin Mirzaei, Behnam Mohammadi-Ivatloo
Summary: This article proposes a novel platform for MG prosumers to actively trade energy with each other directly. P2P energy trading is introduced to achieve a win-win outcome and facilitate energy balance locally. The numerical results show that prosumers can actively trade with each other and achieve economic benefits.
IEEE SYSTEMS JOURNAL
(2023)
Article
Energy & Fuels
Mansour Selseleh Jonban, Luis Romeral, Elyas Rakhshani, Mousa Marzband
Summary: This study proposes a novel smart multi-agent-based framework under a tendering process framework with a bottom-up approach to control and manage the flow of energy into a grid-connected microgrid. The first-price sealed-bid algorithm is implemented to optimize the electricity cost and decrease the use of grid power. The proposed approach optimally allocates energy among generators and guarantees the system from blackouts.
Article
Automation & Control Systems
Olatunji M. Adeyanju, Pierluigi Siano, Luciane N. Canha
Summary: This article presents a dedicated microgrid planning and operation approach that considers pumped-hydro storage (PHS) to support distribution network (DN). The approach allows dedicated microgrids to solely serve the distribution system, reducing the overall operation cost and increasing revenue. By incorporating a short-term operation capacity index, power purchase agreement, and levelized energy cost, the microgrid's sensitivity to operation penalty is minimized, enabling it to maximize profit.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Amirhossein Ahmadi, Saman Taheri, Reza Ghorbani, Vahid Vahidinasab, Behnam Mohammadi-Ivatloo
Summary: This study proposes a new ensemble model for dynamic line rating forecasting of overhead transmission lines. By utilizing multivariate empirical mode decomposition, the proposed ensemble model overcomes the limitations of single models and improves the forecasting performance. The results show that the ensemble model can accurately predict the dynamic line rating and is robust to noisy data.
IEEE TRANSACTIONS ON POWER DELIVERY
(2023)
Article
Engineering, Electrical & Electronic
Farzam Monfaredi, Hossein Shayeghi, Pierluigi Siano
Summary: This paper introduces a novel optimal energy management method based on the multi-agent deep reinforcement learning (MA-DRL) approach. The method utilizes deep neural networks and stacked denoising auto-encoders to learn strategies, and employs multi-agent deep deterministic policy gradient learning capability. The MA-DRL method is utilized to find the optimal strategy for managing energy resources under the Markov decision process framework, taking into account the distinct properties of electric and thermal energies.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2023)
Article
Construction & Building Technology
Fernando Cerna, John K. Coelho, Mauricio P. Fantesia, Ehsan Naderi, Mousa Marzband, Javier Contreras
Summary: In urban areas, the increasing population has made services more dependent on electricity, leading to operational stress in the electricity network. To address this issue, efficient energy management strategies are needed to improve the load factor of the network. This study proposes a mixed-integer linear programming model that optimizes the scheduling of electrical appliances and the use of distributed energy resources to increase the load factor and mitigate voltage fluctuations and technical losses. The model considers operational constraints and uncertainties in demand profiles and solar irradiance. The results demonstrate the applicability of the proposed model in reducing electricity waste and ensuring an efficient network operation.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Construction & Building Technology
Shahab Eslami, Younes Noorollahi, Mousa Marzband, Amjad Anvari-Moghaddam
Summary: This study utilizes a geographic information system (GIS) to analyze different layers and identify the most suitable locations for district heating in Gaziantep, Turkey. The study employs a mixed integer linear programming (MILP) approach to model proposed energy systems and achieve optimal operation and planning. Results show that a hybrid energy system with a renewable energy penetration rate of 78% achieves the best levelized cost of energy (LCOE) of 0.0442.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Automation & Control Systems
Gerasimos Rigatos, Pierluigi Siano, Bilal Sari, Masoud Abbaszadeh, Mohamed Assaad Hamida
Summary: In this study, a nonlinear optimal control method (H-infinity) is developed for a wind power unit with twin turbines, permanent magnet synchronous generators (PMSGs), and AC/DC converters. The control algorithm solves the setpoints definition problem based on proving the differential flatness properties of the system. The dynamic model of the wind power unit is linearized around a temporary operating point using Taylor series expansion and Jacobian matrices. A stabilizing optimal (H-infinity) feedback controller is then designed for the linearized model to address the nonlinear optimal control problem under model uncertainty and external perturbations. The global stability properties of the control method are proven through Lyapunov analysis, and a H-infinity Kalman Filter is used as a robust state estimator for state estimation-based control of the wind power unit.
JOURNAL OF CONTROL AND DECISION
(2023)
Article
Engineering, Electrical & Electronic
Sattar Shojaeiyan, Moslem Dehghani, Pierluigi Siano
Summary: This paper aims to address the resilience framework in microgrids (MGs) after natural catastrophes by considering energy hub (EH) systems. The study focuses on the restoration of critical loads using water and EHs (WEHs) and the assessment of system resiliency against unpredictable events. The introduced scenario-based method improves the resiliency of MGs in uncertain environments. The efficiency of the model was evaluated using a modified IEEE test system.
Article
Engineering, Electrical & Electronic
Yingqi Liang, Junbo Zhao, Pierluigi Siano, Dipti Srinivasan
Summary: This paper proposes a new data-driven approach for estimating sparse voltage sensitivity in large-scale distribution systems with PVs. The approach effectively mitigates the impact of PV stochasticity and unknown measurement noise under different system operating conditions. The proposed method includes adaptively-weighted l(1) sparsity-promoting regularization, l(2) regularization, Huber loss function, and concomitant scale estimate, implemented in a fast recursive parallel computing framework. Simulation results demonstrate the robustness and efficiency of the proposed estimator compared to existing alternatives.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Energy & Fuels
Hossein Khorramdel, Mohsen Gitizadeh, Pierluigi Siano, Sara Bakhtiari
Summary: Demand response offers consumers the opportunity to play a crucial role in the development of smart grids. It provides a potential solution to address the uncertainties associated with renewable energies. Additionally, the personality types of consumers can influence their tariff choices and electricity costs.
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS
(2023)
Article
Computer Science, Information Systems
Poras Khetarpal, Neelu Nagpal, Mohammed S. Al-Numay, Pierluigi Siano, Yogendra Arya, Neelam Kassarwani
Summary: Power quality issues need to be properly addressed in the forthcoming era of smart meters, smart grids, and increased integration of renewable energy. This paper proposes the use of Deep Auto-encoder (DAE) networks for power quality disturbance (PQD) classification and location detection, without the need for complex signal processing techniques and classifiers. The proposed method shows excellent classification accuracy for PQD, compared to other methods, and requires smaller data sets and less computation time.