Article
Engineering, Electrical & Electronic
L. Phani Raghav, R. Seshu Kumar, D. Koteswara Raju, Arvind R. Singh
Summary: The article introduces a stochastic framework utilizing the Quantum Teaching Learning-based optimization (QTLBO) algorithm to optimize energy flow in microgrids, assessing four scenarios of seasonal variations. Results show the superiority of QTLBO in terms of convergence and achieving global optimum solutions for microgrid optimization.
IEEE TRANSACTIONS ON SMART GRID
(2021)
Article
Chemistry, Multidisciplinary
Shuang Rong, Yanlei Zhao, Yanxin Wang, Jiajia Chen, Wanlin Guan, Jiapeng Cui, Yanlong Liu
Summary: Multi-microgrid collaborative scheduling can promote the local consumption of renewable energy in the smart grid and reduce operating costs. The uncertainty of PV power generation and load demand seriously affects the profit maximization of microgrids. To address this challenge, this paper proposes a stochastic optimal scheduling strategy for industrial park smart microgrids with multiple transformers based on IGDT.
APPLIED SCIENCES-BASEL
(2023)
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
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
Irina Picioroaga, Madalina Luca, Andrei Tudose, Dorian Sidea, Mircea Eremia, Constantin Bulac
Summary: As climate changes intensify, the resilience of electricity supply systems becomes a major concern. To address this issue, a combination of renewable energy sources and energy storage systems is proposed to improve reliability and reduce the impact of outages on critical loads in remote microgrids.
Article
Construction & Building Technology
Faezeh Jalilian, Mohammad Amin Mirzaei, Kazem Zare, Behnam Mohammadi-Ivatloo, Mousa Marzband, Amjad Anvari-Moghaddam
Summary: This paper proposes an integrated scheduling model for optimal despatch of cooling, heating, power, gas, and water sources in an energy-water microgrid. The model considers the role of water and energy storage systems (WESSs) and demand response programs (DRPs) in the optimal scheduling process. A multi-objective two-stage stochastic optimization model is adopted to minimize total cost, with simulation results confirming the advantages of considering WESSs and DRPs on the total cost of the proposed energy-water microgrid.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Green & Sustainable Science & Technology
Musa Terkes, Zafer Ozturk, Alpaslan Demirci, Said Mirza Tercan
Summary: The rapid development of distributed renewable energy has created a need for energy storage to ensure efficient operation. However, the high investment costs and long payback periods make energy storage challenging for prosumers. This study explores the feasibility of using second-use batteries as shared storage for prosumers and determines the financial and technical break-even points. The results suggest that governments should develop realistic incentive mechanisms to effectively implement second-life batteries.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Energy & Fuels
R. Seshu Kumar, L. Phani Raghav, D. Koteswara Raju, Arvind R. Singh
Summary: This paper proposes a three-stage stochastic EMS framework to address operational cost optimization in MG, creating solar and wind power generation profiles under uncertainties, establishing MG system configuration and operational constraints, and using quantum particle swarm optimization to achieve optimal power dispatch configuration.
Article
Energy & Fuels
Hui Hwang Goh, Shuaiwei Shi, Xue Liang, Dongdong Zhang, Wei Dai, Hui Liu, Shen Yuong Wong, Tonni Agustiono Kurniawan, Kai Chen Goh, Chin Leei Cham
Summary: This paper proposes a multi-stage methodology to optimize the energy management problem of microgrids considering the uncertainty of carbon trading market and demand side response. The scenario analysis method is used to tackle the uncertainty of renewable energy, and the characteristics of different load types are analyzed. The quantum particle swarm optimization algorithm is utilized to obtain the optimal solution. The results show that carbon trading market policy contributes to the reduction of carbon emissions and fossil fuel consumption, and a high load participation rate in demand side response can improve the operational economics of microgrids.
Article
Energy & Fuels
Ghada Abdulnasser, Abdelfatah Ali, Mostafa F. Shaaban, Essam E. M. Mohamed
Summary: This paper proposes a stochastic-based multi-objectives optimization model for optimal day-ahead scheduling of microgrids based on energy hubs (EHs). The model simultaneously manages non-dispatchable distributed generator units and energy storage systems, considering uncertainties of wind speed, solar radiation, and residential loads. By introducing a demand response program, significant reductions in cost, emissions, imported power, and CAES operation costs are achieved.
JOURNAL OF ENERGY STORAGE
(2022)
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
Energy & Fuels
Simon Sandler, Eric Williams, Eric Hittinger, Alejandro Elenes
Summary: Future cost reductions in renewable generation and storage technologies have the potential to drastically alter the design, cost, and carbon emissions of microgrids. The design of microgrids is nonlinearly dependent on technology costs, and can be analyzed using a phase transition analogy. Results demonstrate clearly defined phases in the incorporation of solar, batteries, and diesel into the system design.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Engineering, Electrical & Electronic
N. Covic, F. Braeuer, R. McKenna, H. Pandzic
Summary: This paper explores the investment issues of battery storage and photovoltaics for industrial consumers, and discusses ways to enhance their flexibility by utilizing different markets and revenue streams. The study demonstrates that by closely considering scenarios of local load, market prices, and photovoltaic generation, as well as using robust optimization models, uncertainty in the market can be effectively managed.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Computer Science, Information Systems
Michele Roccotelli, Agostino Marcello Mangini, Maria Pia Fanti
Summary: This paper addresses the energy management problem of cooperative microgrids in a smart energy district and proposes an innovative optimization model taking into account uncertainties of key parameters. Two approaches, linear programming and stochastic linear programming, are proposed to solve the DEMS problem and provide optimal strategies for scheduling the charging and discharging operations of storage systems and electric vehicle batteries.
Article
Automation & Control Systems
Hong Liang, Haochen Hua, Yuchao Qin, Maojiao Ye, Shuqing Zhang, Junwei Cao
Summary: The functionality of energy routing among microgrids is crucial in the deployment of smart power systems worldwide. To improve energy routing performance and enhance renewable energy integration, a new electrical device called energy router (ER) is being developed as part of the future energy Internet infrastructure. This article adopts compressive sensing as a solution to the nonlinear energy storage management problem in ERs, considering the randomness of power generation and usage in the energy Internet scenario. The compressive sensing method used in this article is proven to be more efficient than conventional methods, and its performance is evaluated through numerical examples.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Energy & Fuels
Javier Tobajas, Felix Garcia-Torres, Pedro Roncero-Sanchez, Javier Vazquez, Ladjel Bellatreche, Emilio Nieto
Summary: This study focuses on the development of a resilience-oriented optimization for microgrids with hybrid Energy Storage System (ESS), validated through numerical simulations. The research aims to improve the autonomy of the microgrid and achieve a rapid transition response.
Article
Thermodynamics
Diogo Ortiz Machado, Gustavo Artur Andrade, Julio Elias Normey-Rico, Carlos Bordons
Summary: This study develops an exergy-based hierarchical control for the ACUREX solar collector field. The control can track references, reject disturbances, and optimize production considering operational constraints and intermittent processes. The findings suggest that the proposed exergy-based controller design provides improved thermodynamic performance and is a suitable strategy for the ACUREX solar field.
Article
Chemistry, Multidisciplinary
Isabel Santiago, Javier Garcia-Quintero, Gonzalo Mengibar-Ariza, David Trillo-Montero, Rafael J. Real-Calvo, Miguel Gonzalez-Redondo
Summary: This study analyzes the impact of small photovoltaic installations on low-voltage distribution networks and finds that their production and injection of electricity can cause a slight rise in grid voltage values, but not close to the limits set by regulations. The study also assesses the hosting capacity of the grid for these installations and analyzes the possible influence on voltage imbalance and grid frequency.
APPLIED SCIENCES-BASEL
(2022)
Article
Engineering, Multidisciplinary
Joaquin Garrido-Zafra, Aurora R. Gil-de-Castro, Rafael Savariego-Fernandez, Matias Linan-Reyes, Felix Garcia-Torres, Antonio Moreno-Munoz
Summary: This paper introduces a cloud-based extended functionality for power quality monitoring and smart appliance response. The system utilizes the FIWARE Internet of Things platform to identify and predict various electrical disturbances, and allows for customization of alarms. It can operate autonomously or under the coordination of the GEB Energy Management System.
IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Diogo Ortiz Machado, Adolfo J. Sanchez, Antonio J. Gallego, Gustavo A. de Andrade, Julio E. Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve the production of an absorption plant. Control techniques are simulated and compared in an absorption plant in Spain. The results demonstrate that the proposed controllers significantly reduce the effort of control actuators and improve energy and exergy production.
Article
Energy & Fuels
Stavros-Andreas Logothetis, Vasileios Salamalikis, Bijan Nouri, Jan Remund, Luis F. Zarzalejo, Yu Xie, Stefan Wilbert, Evangelos Ntavelis, Julien Nou, Niels Hendrikx, Lennard Visser, Manajit Sengupta, Mario Po, Remi Chauvin, Stephane Grieu, Niklas Blum, Wilfried van Sark, Andreas Kazantzidis
Summary: Solar forecasting is crucial for solar farms' operation, production, and storage of generated power. This study investigates the feasibility of using all-sky imagers (ASIs) for forecasting ramp events in solar irradiance. The results show that ASIs have high accuracy in predicting ramp events, and combining physical and deep learning-based methods could further improve the forecasts.
Review
Energy & Fuels
Romain Mannini, Julien Eynard, Stephane Grieu
Summary: Microgrids and networked microgrids are efficient ways to integrate distributed energy resources into power distribution systems, enhancing grid resilience and maintaining power quality. However, challenges exist in managing these resources effectively. This paper surveys recent advances in smart management of microgrids and networked microgrids, highlighting the emerging alternatives of model-based predictive control, data-driven strategies, game theory, and artificial intelligence.
Article
Green & Sustainable Science & Technology
Stavros-Andreas Logothetis, Vasileios Salamalikis, Stefan Wilbert, Jan Remund, Luis F. Zarzalejo, Yu Xie, Bijan Nouri, Evangelos Ntavelis, Julien Nou, Niels Hendrikx, Lennard Visser, Manajit Sengupta, Mario Po, Remi Chauvin, Stephane Grieu, Niklas Blum, Wilfried van Sark, Andreas Kazantzidis
Summary: Accurate solar short-term forecasts are crucial for optimal utilization of solar energy systems. This study evaluated the performance of four all-sky imagers in forecasting global horizontal irradiance (GHI), and found that these imagers were able to accurately forecast GHI under different sky conditions, outperforming persistence models.
Article
Automation & Control Systems
A. Zafra-Cabeza, J. J. Marquez, Carlos Bordons, Miguel A. Ridao
Summary: Due to the current energy dependence of society, the availability and correct functioning of microgrids are strategic issues to be dealt with. This paper presents a novel Control Reconfiguration framework based on Model Predictive Control (MPC) to manage faults in microgrids. The proposal includes fault detection, isolation, and reconfiguration, using different model predictive controllers. Experiments on a real microgrid have shown the benefits of this method.
CONTROL ENGINEERING PRACTICE
(2023)
Article
Energy & Fuels
Youssef Karout, Stephane Thil, Julien Eynard, Emmanuel Guillot, Stephane Grieu
Summary: This paper introduces a hybrid model for short-term forecasting of Direct Normal Irradiance (DNI), which combines a knowledge-based model with a machine learning model. The hybrid model evaluates the impact of atmospheric disturbances on solar resource by processing high dynamic range sky images and forecasts DNI by utilizing DNI measurements. The results demonstrate the significance of combining knowledge-based models with data-driven models and integrating sky-imaging data into the DNI forecasting process, as the proposed hybrid model successfully handles clear-sky, overcast, and mixed weather situations.
Proceedings Paper
Automation & Control Systems
J. J. Marquez, A. Zafra-Cabeza, C. Bordons
Summary: The current energy situation and the possibility of depleting fossil fuels have spurred the investment in renewable energy sources for power generation. Microgrids are proposed as a configuration that integrates renewable energy sources into the power system, with the use of control systems to maintain reliability and minimize costs. Fault-tolerant control is introduced as a tool to maintain control objectives even in the presence of faults, requiring fault detection, quantification, and adaptive control. This article presents a fault quantification method based on parity equations and structured residuals to mitigate the consequences of faults in microgrid systems.
Proceedings Paper
Automation & Control Systems
Manuel Sivianes, Ascension Zafra-Cabeza, Carlos Bordons
Summary: The energy network is decentralizing due to the inclusion of distributed energy resources. This paper proposes a distributed energy management platform that utilizes blockchain technology to enable safe peer-to-peer transactions. The performance of the distributed model predictive control scheme is compared with the centralized approach.
2022 EUROPEAN CONTROL CONFERENCE (ECC)
(2022)
Proceedings Paper
Automation & Control Systems
Diogo O. Machado, Adolfo J. Sanchez, Gustavo A. de Andrade, Julio Normey-Rico, Carlos Bordons, Eduardo F. Camacho
Summary: This article introduces a control method for line focus concentrating solar collectors that tracks the desired outlet temperature by manipulating the flow and uses a solar tracking device for defocusing. The article proposes a new approach to use defocusing as a standard manipulated variable combined with the flow and employs a multi-variable non-linear model predictive control technique for simulation.
2022 EUROPEAN CONTROL CONFERENCE (ECC)
(2022)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Manuel Sivianes, Carlos Bordons
Summary: A distributed energy management algorithm utilizing blockchain technology for safe power trades in microgrids is proposed. The blockchain acts as a global aggregator, verifying and evaluating convergence of power trades.
BLOCKCHAIN AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Juan Aguilar, C. Bordons, A. Arce, R. Galan
Summary: This paper develops a reconfigurable hierarchical multi-time scale framework that combines dynamic storage virtualization and intent profiling to enable domestic consumers to participate in energy markets with weighted strategies. The intelligent management of individual storage virtualization improves the forecasted economic profit of participating in demand-response programs.
