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Electronics
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Optimization and Modeling of Complex Energy Systems
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Optimization and Modeling of Complex Energy Systems

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Power Electronics".

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 9525

Special Issue Editors

Prof. Luca Giaccone

E-Mail Website
Guest Editor
Dipartimento Energia, Politecnico di Torino, 10129 Torino, Italy
Interests: optimization and modeling of complex energy systems; computation of electromagnetic and thermal fields; magnetic field mitigation; EMF dosimetry; compliance of LF pulsed magnetic field sources
Dr. Paolo Lazzeroni

E-Mail Website
Guest Editor
Department of Energy, Politecnico di Torino, Turin, Italy
Interests: optimization and modeling of complex energy systems; smart grids; renewable energy technologies and environment protection; energy conversion; energy efficiency in building; sustainable energy systems; energy communities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Hybrid energy systems, combining two or more energy vectors into a single system, are a promising way of increasing the efficiency of energy production and demand but the complexity of their management increases when several types of energy sources are combined on the same site. Mixed energy demands such as electricity, heating, and cooling require several generators integrating their production in order to fulfill user requirements. In addition, the introduction of energy storage solutions increases the complexity of the system, ensuring the maximum exploitation of the renewable sources and the flexibility of the system.

The operator of a hybrid energy hub requires accurate modeling and the optimal management of the whole system to provide efficient strategies capable of operating a complex polygeneration plant. The best scheduling and/or size of generators must be found to enhance energy optimization by considering operational and technical constraints capable to harvest generation from renewable sources and increase energy saving by minimizing energy wastes at low efficiency working points.

In this context, the Special Issue focuses on the research, development, and practical application of optimization methods applied to the optimal management and/or design of complex energy systems.

Prof. Luca Giaccone
Dr. Paolo Lazzeroni
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Energy analysis and optimization
  • Process integration, analysis, and optimization
  • Refrigeration, air-conditioning, and heat pumps
  • Power generation and CHP
  • Renewable energy (solar, wind, hydro, etc.)
  • Energy storage (batteries, thermal, hydrogen, etc.)
  • Distributed generation and smart grids
  • District energy supply and networks
  • Biomass and biofuels
  • Energy use (building, transportation, desalination, etc.)
  • Industrial energy use
  • Energy conservation and management
  • Environmental impacts of energy conversion
  • Energy policy and planning
  • Techniques addressing uncertainties in optimization of energy systems.

Published Papers (4 papers)

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Research

18 pages, 6688 KiB  
Article
Co-Simulation and Data-Driven Based Procedure for Estimation of Nodal Voltage Phasors in Power Distribution Networks Using a Limited Number of Measured Data
by Marinko Barukčić, Toni Varga, Vedrana Jerković Štil and Tin Benšić
Electronics 2021, 10(4), 522; https://doi.org/10.3390/electronics10040522 - 23 Feb 2021
Cited by 1 | Viewed by 1996
Abstract
The paper studies the framework for the application of computational intelligence methods used for estimations in the distribution power system when a decreased number of measured data is present. Due to the lack of all measured data, the estimation of the distribution power [...] Read more.
The paper studies the framework for the application of computational intelligence methods used for estimations in the distribution power system when a decreased number of measured data is present. Due to the lack of all measured data, the estimation of the distribution power system state is very challenging. The paper studies the application of the artificial neural network and metaheuristic optimization in synergy to solve the voltage phasors estimation problem. The proposed method uses a metaheuristic optimization technique to find virtual input data for the physical model of the network. The presented framework is based on the usage of different computational tools in co-simulation configuration. The research output is the proposed co-simulation setup for the estimation in the distribution power system using a decreased and limited number of available measured data. The estimation procedure was applied on four test distribution networks to validate the presented approach. The maximal estimation errors in voltage magnitudes and angles, using the proposed setup, are below 1.75% and 1∘, respectively, without considering the measurement errors. When the measurement errors are taken into account, the proposed procedure estimates voltage magnitudes and angles with errors below 2.5% and 1.4∘, respectively. In the scenario considering the consumers’ load shape, including the uncertainty range of 20%, the maximal estimation errors are below 1% for magnitude and 0.45∘ for the angle taking the measurement errors in the range of 2% into account. Full article
(This article belongs to the Special Issue Optimization and Modeling of Complex Energy Systems)
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49 pages, 3800 KiB  
Article
Economic, Energy, and Environmental Analysis of PV with Battery Storage for Italian Households
by Paolo Lazzeroni, Ivan Mariuzzo, Michele Quercio and Maurizio Repetto
Electronics 2021, 10(2), 146; https://doi.org/10.3390/electronics10020146 - 11 Jan 2021
Cited by 10 | Viewed by 2332
Abstract
The use of renewable energy sources is one way to decarbonize current energy consumption. In this context, photovoltaic (PV) technology plays a direct fundamental role since it can convert sun irradiance into electricity to be used for supplying electric loads for households. Despite [...] Read more.
The use of renewable energy sources is one way to decarbonize current energy consumption. In this context, photovoltaic (PV) technology plays a direct fundamental role since it can convert sun irradiance into electricity to be used for supplying electric loads for households. Despite the huge availability of the solar resource, the intermittence of PV production may reduce its exploitation. This problem can be solved by the introduction of storage systems, such as batteries, storing electricity when PV overproduction occurs and acting as a source when PV generation is absent. Consequently, increase in self-sufficiency and self-consumption can be expected in residential end users, paving the way for more sustainable energy systems. In this paper, an economic, energy, and environmental analysis of PV systems (without and with batteries) for the household is performed for the whole of Italy, by means of a Geographical Information Systems (GIS) approach. A model to simulate energy balance and to manage batteries is defined for households to assess the profitability of such systems under an Italian regulation framework. Concerning results, indicators are provided at a national scale using GIS tools to highlight areas where investments are more profitable, boosting the CO2 emission reduction. Full article
(This article belongs to the Special Issue Optimization and Modeling of Complex Energy Systems)
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17 pages, 704 KiB  
Article
Hybrid Energy Network Management: Simulation and Optimisation of Large Scale PV Coupled with Hydrogen Generation
by Marco Cerchio, Francesco Gullí, Maurizio Repetto and Antonino Sanfilippo
Electronics 2020, 9(10), 1734; https://doi.org/10.3390/electronics9101734 - 20 Oct 2020
Cited by 4 | Viewed by 2309
Abstract
The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply [...] Read more.
The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply and demand. Hybrid Energy Networks (HEN) can mitigate the effects of this unbalancing by providing a connection between the electricity grid and and other energy vectors such as heat, gas or hydrogen. These couplings can activate synergies among networks that, all together, increase the share of renewable sources helping a decarbonisation of the energy sector. As the energy system becomes more and more complex, the need for simulation and optimisation tools increases. Mathematical optimisation can be used to look for a management strategy maximising a specific target, for instance economical, i.e. the minimum management cost, or environmental as the best exploitation or RES. The present work presents a Mixed Integer Linear Programming (MILP) optimisation procedure that looks for the minimum running cost of a system made up by a large-scale PV plant where hydrogen production, storage and conversion to electricity is present. In addition, a connection to a natural gas grid where hydrogen can be sold is considered. Different running strategies are studied and analysed as functions of electricity prices and other forms of electrical energy exploitation. Full article
(This article belongs to the Special Issue Optimization and Modeling of Complex Energy Systems)
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10 pages, 1327 KiB  
Article
Uncertainty Quantification in Energy Management Procedures
by Luca Giaccone, Paolo Lazzeroni and Maurizio Repetto
Electronics 2020, 9(9), 1471; https://doi.org/10.3390/electronics9091471 - 09 Sep 2020
Cited by 3 | Viewed by 2080
Abstract
Complex energy systems are made up of a number of components interacting together via different energy vectors. The assessment of their performance under dynamic working conditions, where user demand and energy prices vary over time, requires a simulation tool. Regardless of the accuracy [...] Read more.
Complex energy systems are made up of a number of components interacting together via different energy vectors. The assessment of their performance under dynamic working conditions, where user demand and energy prices vary over time, requires a simulation tool. Regardless of the accuracy of this procedure, the uncertainty in data, obtained both by measurements or by forecasting, is usually non-negligible and requires the study of the sensitivity of results versus input data. In this work, polynomial chaos expansion technique is used to evaluate the variation of cogeneration plant performance with respect to the uncertainty of energy prices and user requests. The procedure allows to obtain this information with a much lower computational cost than that of usual Monte-Carlo approaches. Furthermore, all the tools used in this paper, which were developed in Python, are published as free and open source software. Full article
(This article belongs to the Special Issue Optimization and Modeling of Complex Energy Systems)
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