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Distributed Renewable Generation 2018
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Distributed Renewable Generation 2018

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

Deadline for manuscript submissions: closed (30 June 2018) | Viewed by 26777

Special Issue Editor

Prof. Dr. João P. S. Catalão

E-Mail Website
Guest Editor
Faculty of Engineering, University of Porto, Porto, Portugal
Interests: power system operations and planning; hydrothermal scheduling and wind/price forecasting; power system economics and electricity markets; risk analysis, uncertainty, and stochastic programming; renewable energies and demand-side management
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

“Distributed Renewable Generation 2018” is a continuation of the previous and successful Special Issue, “Distributed Renewable Generation”.

We are inviting submissions to the Energies Special Issue on “Distributed Renewable Generation 2018”.

This is the second special issue to focus on the distributed generation of electric energy industry. Prospects for a decentralized and renewable-based power generation, eventually displacing conventional power plants, reducing the balancing role of the transmission grid, and shifting intelligence to the distribution grid through the creation of local and regional energy systems, become increasingly likely in the near future. The widespread use of distributed generation, renewable technologies, and energy storage at the residential level is a major paradigm shift for the electric energy industry, which has traditionally relied on large centralized power generation, allowing the share of locally- and domestically-produced electricity to increase.

On the one hand, depending on its location and size, it can be beneficial in reducing power losses and increasing the overall efficiency of the power system, enabling the evolution towards a sustainable and smart grid. Distributed renewable generation is also an excellent way to power microgrids, increasing grid resilience through the local ability to deal with an emergency by operating off-grid. On the other hand, new difficulties arise related to stability, voltage control, and power quality issues, among others, which have to be addressed with novel research studies and innovative solutions.

Indeed, integrating massive distributed renewable generation into the grid poses many challenges to the electric energy sector. The uncertainty and variability of solar photovoltaic and wind energy resources add significant complexity to maintaining the security and reliability of the system, so adequate control, operations, and planning methodologies and tools are required, as well as demand-side management capabilities. More sophisticated balancing and forecasting tools should also be developed to accommodate renewables’ intermittency.

The potential benefits, impacts, and drawbacks must be properly ascertained using realistic case studies, advanced simulation studies, and/or comprehensive experimental tests, as well as cost–benefit and SWOT analyses. Hence, this Special Issue aims to address this important area of research related to “Distributed Renewable Generation”.

Prof. João P. S. Catalão
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

  • Distributed generation
  • Renewable technologies
  • Energy storage
  • Control, operations, and planning
  • Demand-side management
  • Forecasting tools

Published Papers (6 papers)

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Research

16 pages, 7357 KiB  
Article
Deep Learning to Forecast Solar Irradiance Using a Six-Month UTSA SkyImager Dataset
by Ariana Moncada, Walter Richardson, Jr. and Rolando Vega-Avila
Energies 2018, 11(8), 1988; https://doi.org/10.3390/en11081988 - 31 Jul 2018
Cited by 40 | Viewed by 4882
Abstract
Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera. Reconfigurable for different operational environments, it has been deployed at the National Renewable [...] Read more.
Distributed PV power generation necessitates both intra-hour and day-ahead forecasting of solar irradiance. The UTSA SkyImager is an inexpensive all-sky imaging system built using a Raspberry Pi computer with camera. Reconfigurable for different operational environments, it has been deployed at the National Renewable Energy Laboratory (NREL), Joint Base San Antonio, and two locations in the Canary Islands. The original design used optical flow to extrapolate cloud positions, followed by ray-tracing to predict shadow locations on solar panels. The latter problem is mathematically ill-posed. This paper details an alternative strategy that uses artificial intelligence (AI) to forecast irradiance directly from an extracted subimage surrounding the sun. Several different AI models are compared including Deep Learning and Gradient Boosted Trees. Results and error metrics are presented for a total of 147 days of NREL data collected during the period from October 2015 to May 2016. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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18 pages, 7648 KiB  
Article
Direct-Lyapunov-Based Control Scheme for Voltage Regulation in a Three-Phase Islanded Microgrid with Renewable Energy Sources
by Hadi Hosseini Kordkheili, Mahdi Banejad, Ali Akbarzadeh Kalat, Edris Pouresmaeil and João P. S. Catalão
Energies 2018, 11(5), 1161; https://doi.org/10.3390/en11051161 - 06 May 2018
Cited by 6 | Viewed by 2966
Abstract
In this paper, the local control structure of a microgrid is partially modified by a Lyapunov-based controller. This controller is derived based on direct Lyapunov stability theory (DLST) in order to calculate proper switching functions for the stable operation of the local controller [...] Read more.
In this paper, the local control structure of a microgrid is partially modified by a Lyapunov-based controller. This controller is derived based on direct Lyapunov stability theory (DLST) in order to calculate proper switching functions for the stable operation of the local controller as well as proper local performance of each inverter-based distributed generation (DG) unit. The main contribution is the use of DLST-based controller in a hierarchical primary control structure along with a DC-side voltage regulator. A current-based droop controller is also introduced along with a voltage harmonic compensation technique. The control limits of droop equations are calculated based on steady-state and dynamic capability curve as well as voltage-frequency ellipse curve. The effect of the variations of voltages and circuit parameters on the capability curves are also investigated and the microgrid (MG) steady-state operation area is obtained. In the proposed method, the DC-voltage variations are regulated by an additional voltage control loop based on a current reference correction signal. The above-mentioned approaches are derived thoroughly with mathematical equations. The effectiveness of the designed controllers is verified by a MATLAB/SIMULINK simulation platform (Matlab/Simulink R2014a, Mathworks, Inc.) with harmonically distorted intermittent loads. The results show the appropriate performance of the proposed controllers during both steady-state and transient dynamic conditions. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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23 pages, 12252 KiB  
Article
Optimal Load-Tracking Operation of Grid-Connected Solid Oxide Fuel Cells through Set Point Scheduling and Combined L1-MPC Control
by Siwei Han, Li Sun, Jiong Shen, Lei Pan and Kwang Y. Lee
Energies 2018, 11(4), 801; https://doi.org/10.3390/en11040801 - 30 Mar 2018
Cited by 16 | Viewed by 4033
Abstract
An optimal load-tracking operation strategy for a grid-connected tubular solid oxide fuel cell (SOFC) is studied based on the steady-state analysis of the system thermodynamics and electrochemistry. Control of the SOFC is achieved by a two-level hierarchical control system. In the upper level, [...] Read more.
An optimal load-tracking operation strategy for a grid-connected tubular solid oxide fuel cell (SOFC) is studied based on the steady-state analysis of the system thermodynamics and electrochemistry. Control of the SOFC is achieved by a two-level hierarchical control system. In the upper level, optimal setpoints of output voltage and the current corresponding to unit load demand is obtained through a nonlinear optimization by minimizing the SOFC’s internal power waste. In the lower level, a combined L1-MPC control strategy is designed to achieve fast set point tracking under system nonlinearities, while maintaining a constant fuel utilization factor. To prevent fuel starvation during the transient state resulting from the output power surging, a fuel flow constraint is imposed on the MPC with direct electron balance calculation. The proposed control schemes are testified on the grid-connected SOFC model. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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17 pages, 7127 KiB  
Article
Risk-Based Two-Stage Stochastic Optimization Problem of Micro-Grid Operation with Renewables and Incentive-Based Demand Response Programs
by Pouria Sheikhahmadi, Ramyar Mafakheri, Salah Bahramara, Maziar Yazdani Damavandi and João P. S. Catalão
Energies 2018, 11(3), 610; https://doi.org/10.3390/en11030610 - 09 Mar 2018
Cited by 27 | Viewed by 4591
Abstract
The operation problem of a micro-grid (MG) in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO) is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. [...] Read more.
The operation problem of a micro-grid (MG) in grid-connected mode is an optimization one in which the main objective of the MG operator (MGO) is to minimize the operation cost with optimal scheduling of resources and optimal trading energy with the main grid. The MGO can use incentive-based demand response programs (DRPs) to pay an incentive to the consumers to change their demands in the peak hours. Moreover, the MGO forecasts the output power of renewable energy resources (RERs) and models their uncertainties in its problem. In this paper, the operation problem of an MGO is modeled as a risk-based two-stage stochastic optimization problem. To model the uncertainties of RERs, two-stage stochastic programming is considered and conditional value at risk (CVaR) index is used to manage the MGO’s risk-level. Moreover, the non-linear economic models of incentive-based DRPs are used by the MGO to change the peak load. The numerical studies are done to investigate the effect of incentive-based DRPs on the operation problem of the MGO. Moreover, to show the effect of the risk-averse parameter on MGO decisions, a sensitivity analysis is carried out. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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16 pages, 3926 KiB  
Article
Maximum Permissible Integration Capacity of Renewable DG Units Based on System Loads
by Kadir Doğanşahin, Bedri Kekezoğlu, Recep Yumurtacı, Ozan Erdinç and João P. S. Catalão
Energies 2018, 11(1), 255; https://doi.org/10.3390/en11010255 - 21 Jan 2018
Cited by 23 | Viewed by 4378
Abstract
Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number [...] Read more.
Increasing demand for electricity, as well as rising environmental and economic concerns have resulted in renewable energy sources being a center of attraction. Integration of these renewable energy resources into power systems is usually achieved through distributed generation (DG) techniques, and the number of such applications increases daily. As conventional power systems do not have an infrastructure that is compatible with these energy sources and generation systems, such integration applications may cause various problems in power systems. Therefore, planning is an essential part of DG integration, especially for power systems with intermittent renewable energy sources with the objective of minimizing problems and maximizing benefits. In this study, a mathematical model is proposed to calculate the maximum permissible DG integration capacity without causing overvoltage problems in the power systems. In the proposed mathematical model, both the minimum loading condition and maximum generation condition are taken into consideration. In order to prove the effectiveness and the consistency of the proposed mathematical model, it is applied to a test system with different case studies, and the results are compared with the results obtained from other models in the literature. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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16 pages, 3162 KiB  
Article
Scheduling Model for Renewable Energy Sources Integration in an Insular Power System
by Gerardo J. Osório, Miadreza Shafie-khah, Juan M. Lujano-Rojas and João P. S. Catalão
Energies 2018, 11(1), 144; https://doi.org/10.3390/en11010144 - 07 Jan 2018
Cited by 17 | Viewed by 5219
Abstract
Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has [...] Read more.
Insular power systems represent an asset and an excellent starting point for the development and analysis of innovative tools and technologies. The integration of renewable energy resources that has taken place in several islands in the south of Europe, particularly in Portugal, has brought more uncertainty to production management. In this work, an innovative scheduling model is proposed, which considers the integration of wind and solar resources in an insular power system in Portugal, with a strong conventional generation basis. This study aims to show the benefits of increasing the integration of renewable energy resources in this insular power system, and the objectives are related to minimizing the time for which conventional generation is in operation, maximizing profits, reducing production costs, and consequently, reducing greenhouse gas emissions. Full article
(This article belongs to the Special Issue Distributed Renewable Generation 2018)
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