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Energies
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Decentralised Energy Supply Systems
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Decentralised Energy Supply Systems

A special issue of Energies (ISSN 1996-1073).

Deadline for manuscript submissions: closed (28 February 2018) | Viewed by 32284

Special Issue Editor

Prof. Dr. Matthew Leach

E-Mail Website
Guest Editor
The centre for Environment and Sustainability, University of Surrey, Guildford, UK
Interests: decentralised energy supply systems; sustainable energy; demand-side management; energy economics; energy policy

Special Issue Information

Dear Colleagues,

Decentralized energy supply refers to energy that is produced and used locally, whether for electricity, heating or cooling, and can be derived from small renewables, biomass, waste-to energy or combined heat and power. Driven by both low carbon and security of supply priorities, there has been increasing interest commercially and amongst policy makers in meeting energy service demands through local installations.

This Special Issue will address key opportunities and challenges for expansion of decentralized energy supply systems. Attention will be given to emerging technologies offering improved performance, and to local or community scale business models in which they can thrive. Methods for local energy systems modeling and decision making for system design will be considered, and the influences of current and future policy initiatives will be explored. Local supply cannot be considered in isolation, and attention will also be given to its interaction with emerging energy storage and demand side management opportunities, and to impacts on conventional power systems.

Prof. Dr. Matthew Leach
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

  • sustainable energy
  • renewable energy
  • distributed generation
  • community energy
  • smart grids
  • energy transition
  • power systems

Published Papers (5 papers)

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Research

19 pages, 4085 KiB  
Article
Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level
by Pol Olivella-Rosell, Pau Lloret-Gallego, Íngrid Munné-Collado, Roberto Villafafila-Robles, Andreas Sumper, Stig Ødegaard Ottessen, Jayaprakash Rajasekharan and Bernt A. Bremdal
Energies 2018, 11(4), 822; https://doi.org/10.3390/en11040822 - 02 Apr 2018
Cited by 178 | Viewed by 11373
Abstract
This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on [...] Read more.
This paper presents a general description of local flexibility markets as a market-based management mechanism for aggregators. The high penetration of distributed energy resources introduces new flexibility services like prosumer or community self-balancing, congestion management and time-of-use optimization. This work is focused on the flexibility framework to enable multiple participants to compete for selling or buying flexibility. In this framework, the aggregator acts as a local market operator and supervises flexibility transactions of the local energy community. Local market participation is voluntary. Potential flexibility stakeholders are the distribution system operator, the balance responsible party and end-users themselves. Flexibility is sold by means of loads, generators, storage units and electric vehicles. Finally, this paper presents needed interactions between all local market stakeholders, the corresponding inputs and outputs of local market operation algorithms from participants and a case study to highlight the application of the local flexibility market in three scenarios. The local market framework could postpone grid upgrades, reduce energy costs and increase distribution grids’ hosting capacity. Full article
(This article belongs to the Special Issue Decentralised Energy Supply Systems)
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1265 KiB  
Article
Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units
by Shan Deng, Qinghua Wu, Zhaoxia Jing, Lilan Wu, Feng Wei and Xiaoxin Zhou
Energies 2017, 10(12), 1966; https://doi.org/10.3390/en10121966 - 25 Nov 2017
Cited by 32 | Viewed by 3450
Abstract
The simulation model is one of the key points affecting the optimal planning and operation of energy hubs (EHs). Since treating the efficiencies of generation units as constants would significantly simplify the calculation, only a simplified model is investigated in most research works. [...] Read more.
The simulation model is one of the key points affecting the optimal planning and operation of energy hubs (EHs). Since treating the efficiencies of generation units as constants would significantly simplify the calculation, only a simplified model is investigated in most research works. In this paper, aiming at optimizing the capacity configuration of an EH, we present a part-load characteristics-based (PLCB) model, in which the efficiencies of generation units will change with the fluctuating load. Based on the PLCB model, the accuracy of the EH model can be improved. Furthermore, a two-stage planning method is proposed to solve the optimal capacity configuration problem of the EH. Group Search Optimizer (GSO) is used to determine the optimal size in the first stage, and a mathematical programming method is applied to obtain the optimal operation of the EH in the second stage. Comparative studies using the PLCB model and the simplified model are performed to examine the impacts of equipment part-load characteristics on the sizing results. Simulation results indicate that the proposed model appears to have a better economic performance than the simplified model. Full article
(This article belongs to the Special Issue Decentralised Energy Supply Systems)
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9913 KiB  
Article
The Fuzzy Logic Method to Efficiently Optimize Electricity Consumption in Individual Housing
by Sébastien Bissey, Sébastien Jacques and Jean-Charles Le Bunetel
Energies 2017, 10(11), 1701; https://doi.org/10.3390/en10111701 - 25 Oct 2017
Cited by 28 | Viewed by 6323
Abstract
Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours [...] Read more.
Electricity demand shifting and reduction still raise a huge interest for end-users at the household level, especially because of the ongoing design of a dynamic pricing approach. In particular, end-users must act as the starting point for decreasing their consumption during peak hours to prevent the need to extend the grid and thus save considerable costs. This article points out the relevance of a fuzzy logic algorithm to efficiently predict short term load consumption (STLC). This approach is the cornerstone of a new home energy management (HEM) algorithm which is able to optimize the cost of electricity consumption, while smoothing the peak demand. The fuzzy logic modeling involves a strong reliance on a complete database of real consumption data from many instrumented show houses. The proposed HEM algorithm enables any end-user to manage his electricity consumption with a high degree of flexibility and transparency, and “reshape” the load profile. For example, this can be mainly achieved using smart control of a storage system coupled with remote management of the electric appliances. The simulation results demonstrate that an accurate prediction of STLC gives the possibility of achieving optimal planning and operation of the HEM system. Full article
(This article belongs to the Special Issue Decentralised Energy Supply Systems)
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4208 KiB  
Article
Designing a Sustainable University Recharge Area for Electric Vehicles: Technical and Economic Analysis
by Rosario Miceli and Fabio Viola
Energies 2017, 10(10), 1604; https://doi.org/10.3390/en10101604 - 13 Oct 2017
Cited by 46 | Viewed by 4934
Abstract
This article addresses the technical and economic challenges regarding the design of a “green” recharge area for electric vehicles at the University of Palermo in order to reduce costs and pollution connected to the charging process. Based on the behaviour of the student [...] Read more.
This article addresses the technical and economic challenges regarding the design of a “green” recharge area for electric vehicles at the University of Palermo in order to reduce costs and pollution connected to the charging process. Based on the behaviour of the student population, the electrical load is identified and two possible solutions are evaluated to manage the peak load: an orientation of the panels increasing the power at defined time and the use of a storage system. The main strength and weakness points of two systems are investigated by taking into account the Levelized Cost of Energy (LCOE), which reaches 75.3 €/MWh for the orientation of panel and 103 €/MWh for the storage system. Furthermore, the cost of the topologies of power plant and the cost of energy are discussed in depth. Full article
(This article belongs to the Special Issue Decentralised Energy Supply Systems)
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1910 KiB  
Article
Super Capacitor Energy Storage Based MMC for Energy Harvesting in Mine Hoist Application
by Xiaofeng Yang, Piao Wen, Yao Xue, Trillion Q. Zheng and Youyun Wang
Energies 2017, 10(9), 1428; https://doi.org/10.3390/en10091428 - 17 Sep 2017
Cited by 9 | Viewed by 5502
Abstract
This paper proposes a super capacitor energy storage-based modular multilevel converter (SCES-MMC) for mine hoist application. Different from the conventional MMCs, the sub-modules employ distributed super capacitor banks, which are designed to absorb the regenerative energy of mine hoist and released in the [...] Read more.
This paper proposes a super capacitor energy storage-based modular multilevel converter (SCES-MMC) for mine hoist application. Different from the conventional MMCs, the sub-modules employ distributed super capacitor banks, which are designed to absorb the regenerative energy of mine hoist and released in the traction condition, so as to improve energy utilization efficiency. The key control technologies are introduced in detail, followed by analysis of the configuration and operation principles. The feasibility of the proposed SCES-MMC topology and the control theory are also verified. Simulation results show that SCES-MMC can adapt to the variable frequency speed regulation of the motor drive, which shows good application prospects in the future for medium- and high-voltage mine hoist systems. Full article
(This article belongs to the Special Issue Decentralised Energy Supply Systems)
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