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Energies
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Design and Optimization of Sustainable Energy Systems
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Design and Optimization of Sustainable Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A: Sustainable Energy".

Deadline for manuscript submissions: closed (25 April 2022) | Viewed by 11173

Special Issue Editor

Prof. Dr. Sara Lumbreras

E-Mail Website
Guest Editor
Institute for Research in Technology (IIT), ICAI School of Engineering, Comillas Pontifical University, 28015 Madrid, Spain
Interests: power systems; transmission expansion planning; offshore wind farm design; stochastic programming
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We invite you to submit your original research or overview papers to this Special Issue on the “Design and Optimization of Sustainable Energy Systems” in Energies.

The decarbonization of the energy system is a deep transformation that implies the design—and redesign—of its most fundamental structures. From region-wide generation expansion planning to the short-term operation of battery storage, a myriad perspective emerges with its own interrelated challenges. These issues call for the application of decision-making tools to take advantage of the technological possibilities in the most efficient manner. This Special Issue is dedicated to the application of advanced optimization methods to the design and operation of sustainable energy systems, focusing on innovative methods applied to the integration of renewables and the management of flexibility. The approaches can be based on mathematical optimization or on heuristic techniques, but, in any case, the selection of the technique must be justified and its performance shown with rigor. Results that can be clearly interpreted in terms of simple best-design policies will be highly valued.

The design problems of interest include, but are not limited to:

  • Generation Expansion Planning
  • Transmission Expansion Planning
  • Distribution Expansion Planning
  • Rural Electrification
  • Hydrothermal coordination
  • Unit-Commitment
  • Electric Vehicle management
  • Battery-storage management

Prof. Dr. Sara Lumbreras
Guest Editor

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. Energies 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 2600 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

  • Renewable generation
  • Optimization
  • Design

Published Papers (4 papers)

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Research

21 pages, 4137 KiB  
Article
Network Cost Estimation for Mini-Grids in Large-Scale Rural Electrification Planning
by Pedro Ciller, Sara Lumbreras and Andrés González-García
Energies 2021, 14(21), 7382; https://doi.org/10.3390/en14217382 - 5 Nov 2021
Cited by 3 | Viewed by 1836
Abstract
Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among [...] Read more.
Universal access to electricity is a crucial challenge in many developing countries. Establishing the electrification agenda of an underserved region is a complicated task where computer models play a critical role in calculating geospatial plans that efficiently allocate resources. Such plans should include—among other things—reasonable estimations of the designs and economic costs of standalone systems, mini-grids, and grid extensions. This implies that computer models need to estimate the network cost for many potential mini-grids. To that end, most planning tools apply quick rules of thumb or geometric methods that ignore power flows and electric constraints, which play a significant role in network designs. This paper presents a methodology that rapidly estimates any low-voltage mini-grid network cost without neglecting the impact of electrical feasibility in such cost. We present a case study where we evaluate our method in terms of accuracy and computation time. We also compare our method with a quick estimation similar to the ones most regional planning tools apply, showing the effectiveness of our method. Full article
(This article belongs to the Special Issue Design and Optimization of Sustainable Energy Systems)
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16 pages, 697 KiB  
Article
An Optimal Energy Management System for University Campus Using the Hybrid Firefly Lion Algorithm (FLA)
by Haneef Ullah, Murad Khan, Irshad Hussain, Ibrar Ullah, Peerapong Uthansakul and Naeem Khan
Energies 2021, 14(19), 6028; https://doi.org/10.3390/en14196028 - 22 Sep 2021
Cited by 25 | Viewed by 2036
Abstract
As the world population and its dependency on energy is growing exponentially day by day, the existing energy generating resources are not enough to fulfill their needs. In the conventional grid system, most of the generated energy is wasted because of improper demand [...] Read more.
As the world population and its dependency on energy is growing exponentially day by day, the existing energy generating resources are not enough to fulfill their needs. In the conventional grid system, most of the generated energy is wasted because of improper demand side management (DSM). This leads to a difficulty in keeping the equilibrium between the user need and electric power production. To overcome these difficulties, smart grid (SG) is introduced, which is composed of the integration of two-way communication between the user and utility. To utilize the existing energy resources in a better way, SG is the best option since a large portion of the generated energy is consumed by the educational institutes. Such institutes also need un-interrupted power supply at the lowest cost. Therefore, in this paper, we have taken a university campus load. We have not only applied two bio-inspired heuristic algorithms for energy scheduling—namely, the Firefly Algorithm (FA) and the Lion Algorithm (LA)—but also proposed a hybrid version, FLA, for more optimal results. Our main objectives are a reduction in both, that is, the cost of energy and the waiting time of consumers or end users. For this purpose, in our proposed model, we have divided all appliances into two categories—shiftable appliances and non-shiftable appliances. Shiftable appliances are feasible to be used in any of the time slots and can be planned according to the day-ahead pricing signal (DAP), provided by the utility, while non-shiftable appliances can be used for a specified duration and cannot be planned with the respective DAP signal. So, we have scheduled shiftable appliances only. We have also used renewable energy sources (RES) for achieving maximum end user benefits. The simulation results show that our proposed hybrid algorithm, FLA, has reduced the cost excellently. We have also taken into consideration the consumers’ waiting times, due to scheduling of appliances. Full article
(This article belongs to the Special Issue Design and Optimization of Sustainable Energy Systems)
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23 pages, 4811 KiB  
Article
Metaheuristics and Transmission Expansion Planning: A Comparative Case Study
by Hamdi Abdi, Mansour Moradi and Sara Lumbreras
Energies 2021, 14(12), 3618; https://doi.org/10.3390/en14123618 - 17 Jun 2021
Cited by 14 | Viewed by 1819
Abstract
Transmission expansion planning (TEP), the determination of new transmission lines to be added to an existing power network, is a key element in power system planning. Using classical optimization to define the most suitable reinforcements is the most desirable alternative. However, the extent [...] Read more.
Transmission expansion planning (TEP), the determination of new transmission lines to be added to an existing power network, is a key element in power system planning. Using classical optimization to define the most suitable reinforcements is the most desirable alternative. However, the extent of the under-study problems is growing, because of the uncertainties introduced by renewable generation or electric vehicles (EVs) and the larger sizes under consideration given the trends for higher renewable shares and stronger market integration. This means that classical optimization, even using efficient techniques, such as stochastic decomposition, can have issues when solving large-sized problems. This is compounded by the fact that, in many cases, it is necessary to solve a large number of instances of a problem in order to incorporate further considerations. Thus, it can be interesting to resort to metaheuristics, which can offer quick solutions at the expense of an optimality guarantee. Metaheuristics can even be combined with classical optimization to try to extract the best of both worlds. There is a vast literature that tests individual metaheuristics on specific case studies, but wide comparisons are missing. In this paper, a genetic algorithm (GA), orthogonal crossover based differential evolution (OXDE), grey wolf optimizer (GWO), moth–flame optimization (MFO), exchange market algorithm (EMA), sine cosine algorithm (SCA) optimization and imperialistic competitive algorithm (ICA) are tested and compared. The algorithms are applied to the standard test systems of IEEE 24, and 118 buses. Results indicate that, although all metaheuristics are effective, they have diverging profiles in terms of computational time and finding optimal plans for TEP. Full article
(This article belongs to the Special Issue Design and Optimization of Sustainable Energy Systems)
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26 pages, 2974 KiB  
Article
Techno-Economic Analysis for the Optimal Design of a National Network of Agro-Energy Biomass Power Plants in Egypt
by Suzan Abdelhady, Mohamed A. Shalaby and Ahmed Shaban
Energies 2021, 14(11), 3063; https://doi.org/10.3390/en14113063 - 25 May 2021
Cited by 16 | Viewed by 4091
Abstract
Extensive studies are conducted to investigate the potential and techno-economic feasibility of bioenergy routes in different countries. However, limited researches have been focused on the whole national agricultural bioenergy resources in Egypt. This research provides an assessment of the potential agricultural biomass resources [...] Read more.
Extensive studies are conducted to investigate the potential and techno-economic feasibility of bioenergy routes in different countries. However, limited researches have been focused on the whole national agricultural bioenergy resources in Egypt. This research provides an assessment of the potential agricultural biomass resources for electric energy production in Egypt. It provides a strategic perspective for the design of a national network of biomass power plants to utilize the spatially available agricultural residues throughout a country. A comprehensive approach is presented and is applied to Egypt. First, the approach estimates the amount, type, and characteristics of the agricultural residues in each Egyptian governorate. Then, a techno-economic appraisal for locating a set of collection stations, and installing a direct combustion biomass power plant in each governorate is conducted. SAM simulation software is used for the technical and economic appraisals, and preliminary plant capacities are estimated assuming one plant in each governorate. Secondly, a new mixed integer linear programming (MILP) model is proposed and applied to optimally design a biomass supply chain national network to maximize the overall network profit. The network is composed of the collection stations, the potential biomass power plants, and the flow distribution of residues to supply the selected plants. Results indicate that the Egyptian agricultural residue resources can produce 10 million ton/year of dry residues, generate 11 TWh/year, an average levelized cost of electricity (LCOE) of 6.77 ¢/kWh, and supply about 5.5% of Egypt’s current energy needs. Moreover, the optimization results reveal that a network of 5 biomass power plants with capacities of 460 MW each should be established in Egypt. This approach is thought to be particularly suitable to other developing countries whose energy demand depends on fossil fuels and poses a heavy economic burden, and whose residues are massive, wasted, and not industrialized. The obtained results may also enrich future comparative research that studies the impact and feasibility of implementing agro-residue based biomass electric energy generation. Full article
(This article belongs to the Special Issue Design and Optimization of Sustainable Energy Systems)
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