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Smart Photovoltaic Energy Systems for a Sustainable Future
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Smart Photovoltaic Energy Systems for a Sustainable Future

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".

Deadline for manuscript submissions: closed (31 January 2021) | Viewed by 51285

Special Issue Editors

Dr. Venizelos Efthymiou

E-Mail
Guest Editor
FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia 1678, Cyprus
Interests: smart grids; power systems; PV; RES; storage; microgrids; protection; energy communities
Special Issues, Collections and Topics in MDPI journals
Dr. Christina N. Papadimitriou

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Guest Editor
FOSS Research Centre for Sustainable Energy, Department of Electrical and Computer Engineering, University of Cyprus, Nicosia, Cyprus
Interests: smart grids; sustainable energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are inviting submissions to a Special Issue of Energies Journal on the subject area of “Smart Photovoltaic Energy Systems for a Sustainable Future”.

In order to tackle the climate emergency and meet set out targets through the Paris Agreement, the decarbonization of the energy system is needed. Renewables are a major contributor to this solution, and due to technologies maturing and now offering low-cost solutions, they can, in real terms, lead an energy transition. PVs have gathered momentum, and they are expected to expand dramatically over the coming years compared to any other renewable-energy technology due to the following attractive features:

  • Mature technology/low O&M cost;
  • Increasing efficiency;
  • Good grid integration and hybridization prospects.

Integrating PVs without jeopardizing the security of supplies and the economic operation of the power system is quite a challenge. Therefore, PV systems need to be supported by enabling technologies such as smart systems that facilitate their integration under the concept of smart grids employing advance communication systems, IoT usability, and market solutions to serve the vision of an energy transition.

Smart PVs can play a role within the smart grid concept as the backbone of a green energy transition, combined with other technologies as an active component, responsive and adaptive to local needs.

The topics of interest in this Special Issue may include but are not limited to the following:

  • Power system planning and operation with high penetrations of PV;
  • Control/coordination strategies in managing disturbances and events;
  • Advanced protection of distribution grids with high penetrations of PV;
  • Cybersecurity for PV systems integration;
  • Integrating energy storage with PV, including microgrid/distributed control functionalities;
  • Solar generation analysis and forecasting;
  • PV in support of energy islands/communities: planning and operation;
  • PV contributing to RES synthesis for supporting an integrated grid;
  • Zero energy districts/buildings with PV as the main energy source;
  • PV in the built environment.

Dr. Venizelos Efthymiou
Dr. Christina N. Papadimitriou
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. 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

  • photovoltaics
  • smart grids
  • storage
  • EVs
  • microgrids
  • energy communities
  • energy islands

Published Papers (16 papers)

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Research

21 pages, 392 KiB  
Article
Photovoltaics Enabling Sustainable Energy Communities: Technological Drivers and Emerging Markets
by Alexandros-Georgios Chronis, Foivos Palaiogiannis, Iasonas Kouveliotis-Lysikatos, Panos Kotsampopoulos and Nikos Hatziargyriou
Energies 2021, 14(7), 1862; https://doi.org/10.3390/en14071862 - 27 Mar 2021
Cited by 12 | Viewed by 2890
Abstract
In this paper, we investigate the economic benefits of an energy community investing in small-scale photovoltaics (PVs) when local energy trading is operated amongst the community members. The motivation stems from the open research question on whether a community-operated local energy market can [...] Read more.
In this paper, we investigate the economic benefits of an energy community investing in small-scale photovoltaics (PVs) when local energy trading is operated amongst the community members. The motivation stems from the open research question on whether a community-operated local energy market can enhance the investment feasibility of behind-the-meter small-scale PVs installed by energy community members. Firstly, a review of the models, mechanisms and concepts required for framing the relevant concepts is conducted, while a clarification of nuances at important terms is attempted. Next, a tool for the investigation of the economic benefits of operating a local energy market in the context of an energy community is developed. We design the local energy market using state-of-the-art formulations, modified according to the requirements of the case study. The model is applied to an energy community that is currently under formation in a Greek municipality. From the various simulations that were conducted, a series of generalizable conclusions are extracted. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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15 pages, 1590 KiB  
Article
Photovoltaic Power Forecasting: Assessment of the Impact of Multiple Sources of Spatio-Temporal Data on Forecast Accuracy
by Xwégnon Ghislain Agoua, Robin Girard and Georges Kariniotakis
Energies 2021, 14(5), 1432; https://doi.org/10.3390/en14051432 - 5 Mar 2021
Cited by 17 | Viewed by 2041
Abstract
The efficient integration of photovoltaic (PV) production in energy systems is conditioned by the capacity to anticipate its variability, that is, the capacity to provide accurate forecasts. From the classical forecasting methods in the state of the art dealing with a single power [...] Read more.
The efficient integration of photovoltaic (PV) production in energy systems is conditioned by the capacity to anticipate its variability, that is, the capacity to provide accurate forecasts. From the classical forecasting methods in the state of the art dealing with a single power plant, the focus has moved in recent years to spatio-temporal approaches, where geographically dispersed data are used as input to improve forecasts of a site for the horizons up to 6 h ahead. These spatio-temporal approaches provide different performances according to the data sources available but the question of the impact of each source on the actual forecasting performance is still not evaluated. In this paper, we propose a flexible spatio-temporal model to generate PV production forecasts for horizons up to 6 h ahead and we use this model to evaluate the effect of different spatial and temporal data sources on the accuracy of the forecasts. The sources considered are measurements from neighboring PV plants, local meteorological stations, Numerical Weather Predictions, and satellite images. The evaluation of the performance is carried out using a real-world test case featuring a high number of 136 PV plants. The forecasting error has been evaluated for each data source using the Mean Absolute Error and Root Mean Square Error. The results show that neighboring PV plants help to achieve around 10% reduction in forecasting error for the first three hours, followed by satellite images which help to gain an additional 3% all over the horizons up to 6 h ahead. The NWP data show no improvement for horizons up to 6 h but is essential for greater horizons. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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22 pages, 3830 KiB  
Article
Comparative Analysis of Machine Learning Models for Day-Ahead Photovoltaic Power Production Forecasting
by Spyros Theocharides, Marios Theristis, George Makrides, Marios Kynigos, Chrysovalantis Spanias and George E. Georghiou
Energies 2021, 14(4), 1081; https://doi.org/10.3390/en14041081 - 18 Feb 2021
Cited by 25 | Viewed by 3421
Abstract
A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance [...] Read more.
A main challenge for integrating the intermittent photovoltaic (PV) power generation remains the accuracy of day-ahead forecasts and the establishment of robust performing methods. The purpose of this work is to address these technological challenges by evaluating the day-ahead PV production forecasting performance of different machine learning models under different supervised learning regimes and minimal input features. Specifically, the day-ahead forecasting capability of Bayesian neural network (BNN), support vector regression (SVR), and regression tree (RT) models was investigated by employing the same dataset for training and performance verification, thus enabling a valid comparison. The training regime analysis demonstrated that the performance of the investigated models was strongly dependent on the timeframe of the train set, training data sequence, and application of irradiance condition filters. Furthermore, accurate results were obtained utilizing only the measured power output and other calculated parameters for training. Consequently, useful information is provided for establishing a robust day-ahead forecasting methodology that utilizes calculated input parameters and an optimal supervised learning approach. Finally, the obtained results demonstrated that the optimally constructed BNN outperformed all other machine learning models achieving forecasting accuracies lower than 5%. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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20 pages, 1954 KiB  
Article
Citizen Participation to Finance PV Power Plants Focused on Self-Consumption on Company Roofs—Findings from an Austrian Case Study
by Matthias Linhart, Valerie Rodin, Simon Moser and Andrea Kollmann
Energies 2021, 14(3), 738; https://doi.org/10.3390/en14030738 - 31 Jan 2021
Cited by 7 | Viewed by 5720
Abstract
Despite large amounts of available roof space, long pay-back periods for investments in photovoltaic (PV) power plants often hinder PV installations in industrial parks. Photovoltaic citizen participation initiatives (PV-CPI) are an alternative way of financing PV power plants that add non-financial benefits to [...] Read more.
Despite large amounts of available roof space, long pay-back periods for investments in photovoltaic (PV) power plants often hinder PV installations in industrial parks. Photovoltaic citizen participation initiatives (PV-CPI) are an alternative way of financing PV power plants that add non-financial benefits to these investments. This paper analyzed the feasibility of the installation of PV power plants focused on high rates of self-consumption financed by citizen participation initiatives on the roofs of five companies located in the Austrian Ennshafen industrial business park based on the net present value and the discounted pay-back period and compared it to a standard financing scheme, assuming a predetermined interest rate for participants as well as economies of scale with respect to the specific installation costs due to a joint purchase of the PV power plants. To calculate the feasibility, site-specific data and literature input have been used. The results show that despite an interest rate above the current interest rates of conservative forms of investments provided to (small-scale) investors, a payback-period of 17–23 years can be reached while the joint purchase can lead to a competitive feasibility of the PV-CPI compared to an individual purchase of PV power plants. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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12 pages, 2176 KiB  
Article
Economic Evaluation of PV Installations for Self-Consumption in Industrial Parks
by Juan Pedrero, Patxi Hernández and Álvaro Martínez
Energies 2021, 14(3), 728; https://doi.org/10.3390/en14030728 - 30 Jan 2021
Cited by 12 | Viewed by 2419
Abstract
This paper presents an analysis of the economic performance of photovoltaic (PV) self-consumption systems at an industrial park in the Basque Country (north of Spain). The economic feasibility of the installations is largely dependent on self-consumption and compensation due to electricity injected into [...] Read more.
This paper presents an analysis of the economic performance of photovoltaic (PV) self-consumption systems at an industrial park in the Basque Country (north of Spain). The economic feasibility of the installations is largely dependent on self-consumption and compensation due to electricity injected into the grid, as well as the assumed evolution of the electricity prices. A sensitivity analysis is carried out for different installation sizes and different evolution scenarios concerning electricity prices. The potential for installations for shared self-consumption with dynamic and static distribution coefficients is also analyzed. The results show that medium sized installations are generally a cost effective way to reduce energy bills, while the economic performance of larger installations is more uncertain, and is largely dependent on the selling price for electricity injected into the grid. This case study found that the economic benefits of shared self-consumption between different companies are substantial, and are slightly more favorable when applying dynamic distribution factors. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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30 pages, 11457 KiB  
Article
A Comprehensive Analysis of the Voltage Unbalance Factor in PV and EV Rich Non-Synthetic Low Voltage Distribution Networks
by Tomislav Antić, Tomislav Capuder and Martin Bolfek
Energies 2021, 14(1), 117; https://doi.org/10.3390/en14010117 - 28 Dec 2020
Cited by 27 | Viewed by 3137
Abstract
With the development of technology and the decrease in prices, power systems are facing a strong growth in the number of end-users with photovoltaics (PVs), battery storages and electric vehicles (EVs). A penetration of low carbon (LC) technologies has an impact not only [...] Read more.
With the development of technology and the decrease in prices, power systems are facing a strong growth in the number of end-users with photovoltaics (PVs), battery storages and electric vehicles (EVs). A penetration of low carbon (LC) technologies has an impact not only on the financial aspect, but also on parameters of the power quality (PQ) in the power system. Since most of end-users with renewable energy sources (RES) are connected to a low-voltage (LV) distribution network, there is a high number of single-phase loads and distributed generators (DG) that can cause unwanted effects in LV networks. According to standards, electric energy must be of a certain quality in order to avoid harmful effects on the power system, being both the network or the end-users equipment. One of the PQ parameters is the voltage unbalance. Voltage unbalance occurs in networks with the high share of single-phase loads and generators. Since most loads in households are connected to the only one phase, the voltage unbalance is constantly present in the network, even without LC technologies. Single-phase connected PVs, residential battery storages and EV charging stations can increase voltage unbalance in the system. This paper systematically analyzes a real-world LV network and different stages and shares of connected PVs, residential battery storages and EVs to different phases. The value of the voltage unbalance factor (VUF) is observed for one week in January and August in 10-min intervals. It is shown that connected systems can significantly increase the VUF and potentially cause negative impact on the equipment and the power system as a whole. In turn we analyze a three-phase connection of these new LC technologies and demonstrate how in all analyzed cases PQ values remain within boundaries defined by the EN 50160 and the IEC 61000-3-13. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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27 pages, 4348 KiB  
Article
A Novel Integrated Profit Maximization Model for Retailers under Varied Penetration Levels of Photovoltaic Systems
by Ioannis P. Panapakidis, Nikolaos Koltsaklis and Georgios C. Christoforidis
Energies 2021, 14(1), 92; https://doi.org/10.3390/en14010092 - 26 Dec 2020
Cited by 6 | Viewed by 1369
Abstract
In contemporary energy markets, the Retailer acts as the intermediate between the generation and demand sectors. The scope of the Retailer is to maximize its profits by selecting the appropriate procurement mechanism and selling price to the consumers. The wholesale market operation influences [...] Read more.
In contemporary energy markets, the Retailer acts as the intermediate between the generation and demand sectors. The scope of the Retailer is to maximize its profits by selecting the appropriate procurement mechanism and selling price to the consumers. The wholesale market operation influences the profits since the mix of generation plants determines the system marginal price (SMP). In the related literature, the SMP is treated as a stochastic variable, and the wholesale market conditions are not taken into account. The present paper presents a novel methodology that aims at connecting the wholesale and retail market operations from a Retailer’s perspective. A wholesale market clearing problem is formulated and solved. The scope is to examine how different photovoltaics (PV) penetration levels in the generation side influences the profits of the Retailer and the selling prices to the consumers. The resulting SMPs are used as inputs in a retailer profit maximization problem. This approach allows the Retailer to minimize economic risks and maximize profits. The results indicate that different PV implementation levels on the generation side highly influences the profits and the selling prices. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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13 pages, 1215 KiB  
Article
Reliability Assessment of a Fault-Tolerant PV Multistring Inverter
by Hugues Renaudineau, Pol Paradell-Solà, Lluís Trilla, Alber Filba-Martinez, David Cardoner and José Luis Domínguez-García
Energies 2020, 13(24), 6525; https://doi.org/10.3390/en13246525 - 10 Dec 2020
Cited by 6 | Viewed by 2173
Abstract
In photovoltaic (PV) systems, the reliability of the system components, especially the power converters, is a major concern in obtaining cost effective solutions. In order to guarantee service continuity in the case of failure of elements of the PV converter, in particular, semiconductor [...] Read more.
In photovoltaic (PV) systems, the reliability of the system components, especially the power converters, is a major concern in obtaining cost effective solutions. In order to guarantee service continuity in the case of failure of elements of the PV converter, in particular, semiconductor switching devices, a solution is to design power converter with fault-tolerance capability. This can be realized by aggregating hardware redundancy on an existing converter, providing the possibility of replacement of faulty elements. This paper evaluates the reliability of a fault-tolerant power electronics converter for PV multistring application. The considered fault-tolerant design includes a single redundant switching leg, which is used in order to reconfigure the structure in case of a switch failure either on DC-AC or DC-DC stages. This paper details the reliability estimation of the considered PV multistring fault-tolerant converter. Furthermore, a comparison with a conventional structure without fault-tolerant capability is provided. The results show that the introduction of a single redundant leg allows for improving the converter mean time to failure by a factor of almost two and it reduces, by half, the power loss due to system-failure shutdowns in PV applications, while only increasing the converter cost by 2–3%. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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17 pages, 6562 KiB  
Article
High-Resolution PV Forecasting from Imperfect Data: A Graph-Based Solution
by Rafael E. Carrillo, Martin Leblanc, Baptiste Schubnel, Renaud Langou, Cyril Topfel and Pierre-Jean Alet
Energies 2020, 13(21), 5763; https://doi.org/10.3390/en13215763 - 3 Nov 2020
Cited by 10 | Viewed by 3809
Abstract
Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In [...] Read more.
Operating power systems with large amounts of renewables requires predicting future photovoltaic (PV) production with fine temporal and spatial resolution. State-of-the-art techniques combine numerical weather predictions with statistical post-processing, but their resolution is too coarse for applications such as local congestion management. In this paper we introduce computing methods for multi-site PV forecasting, which exploit the intuition that PV systems provide a dense network of simple weather stations. These methods rely entirely on production data and address the real-life challenges that come with them, such as noise and gaps. Our approach builds on graph signal processing for signal reconstruction and for forecasting with a linear, spatio-temporal autoregressive (ST-AR) model. It also introduces a data-driven clear-sky production estimation for normalization. The proposed framework was evaluated over one year on both 303 real PV systems under commercial monitoring across Switzerland, and 1000 simulated ones based on high-resolution weather data. The results demonstrate the performance and robustness of the approach: with gaps of four hours on average in the input data, the average daytime NRMSE over a six-hour forecasting horizon (in 15 min steps) and over all systems is 13.8% and 9% for the real and synthetic data sets, respectively. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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13 pages, 2842 KiB  
Article
The Influence of Weather Conditions on the Optimal Setting of Photovoltaic Thermal Hybrid Solar Collectors—A Case Study
by Ryszard Myhan, Karolina Szturo, Monika Panfil and Zbigniew Szwejkowski
Energies 2020, 13(18), 4612; https://doi.org/10.3390/en13184612 - 4 Sep 2020
Cited by 3 | Viewed by 2098
Abstract
The potential absorption of solar energy in photovoltaic thermal (PVT) hybrid solar collectors at different tilt angles was compared in the present study. The optimal tilt angles were tested in three variants: during 1 day, 1 year and a period of 30 years. [...] Read more.
The potential absorption of solar energy in photovoltaic thermal (PVT) hybrid solar collectors at different tilt angles was compared in the present study. The optimal tilt angles were tested in three variants: during 1 day, 1 year and a period of 30 years. Simulations were performed based on actual weather data for 30 years, including average hourly total radiation, insolation and air temperature. The apparent movement of the Sun across the sky, solar radiation properties, and the electrical and thermal efficiency of a PVT collector were also taken into account in the simulation model. The optimal orientation of the absorber surface was determined by solving an optimization task. The results of the study indicate that in the long-term perspective, the collector’s performance is maximized when the absorber is positioned toward the south at an elevation angle of 34.1°. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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17 pages, 768 KiB  
Article
Volt-Var Curve Reactive Power Control Requirements and Risks for Feeders with Distributed Roof-Top Photovoltaic Systems
by C. Birk Jones, Matthew Lave, Matthew J. Reno, Rachid Darbali-Zamora, Adam Summers and Shamina Hossain-McKenzie
Energies 2020, 13(17), 4303; https://doi.org/10.3390/en13174303 - 19 Aug 2020
Cited by 10 | Viewed by 4738
Abstract
The benefits and risks associated with Volt-Var Curve (VVC) control for management of voltages in electric feeders with distributed, roof-top photovoltaic (PV) can be defined using a stochastic hosting capacity analysis methodology. Although past work showed that a PV inverter’s reactive power can [...] Read more.
The benefits and risks associated with Volt-Var Curve (VVC) control for management of voltages in electric feeders with distributed, roof-top photovoltaic (PV) can be defined using a stochastic hosting capacity analysis methodology. Although past work showed that a PV inverter’s reactive power can improve grid voltages for large PV installations, this study adds to the past research by evaluating the control method’s impact (both good and bad) when deployed throughout the feeder within small, distributed PV systems. The stochastic hosting capacity simulation effort iterated through hundreds of load and PV generation scenarios and various control types. The simulations also tested the impact of VVCs with tampered settings to understand the potential risks associated with a cyber-attack on all of the PV inverters scattered throughout a feeder. The simulation effort found that the VVC can have an insignificant role in managing the voltage when deployed in distributed roof-top PV inverters. This type of integration strategy will result in little to no harm when subjected to a successful cyber-attack that alters the VVC settings. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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17 pages, 2915 KiB  
Article
A Photovoltaic Power Curtailment Method for Operation on Both Sides of the Power-Voltage Curve
by Jose Miguel Riquelme-Dominguez and Sergio Martinez
Energies 2020, 13(15), 3906; https://doi.org/10.3390/en13153906 - 30 Jul 2020
Cited by 10 | Viewed by 3165
Abstract
Massive integration of non-dispatchable energy into electric power systems is a challenging task. Electric power systems are becoming increasingly vulnerable in terms of frequency stability, as renewable energy displaces conventional synchronous generation from the energy mix. For this reason, grid codes are starting [...] Read more.
Massive integration of non-dispatchable energy into electric power systems is a challenging task. Electric power systems are becoming increasingly vulnerable in terms of frequency stability, as renewable energy displaces conventional synchronous generation from the energy mix. For this reason, grid codes are starting to demand different ancillary services from renewable generators, such as frequency control. In contrast to wind generators, which can deliver to the grid part of the kinetic energy stored in their rotating mass, photovoltaic generators must provide this service using batteries or power curtailment methods. The latter approach is preferable regarding the initial investment and its implementation cost, and several methods have been presented in the literature for this purpose. However, there is no consensus in which is the most appropriate side for operating the photovoltaic system in the curtailed mode. As both possible options have advantages and drawbacks, this paper proposes a novel photovoltaic power curtailment strategy that allows operation on both sides of the power-voltage curve depending on the needs. Moreover, in order to estimate the output characteristic of the photovoltaic system, a real-time nonlinear least squares curve fitting is applied. The proposed methodology has been tested in a simulation environment and the results show that this strategy achieves the requested active power reserves, regardless of the operation side. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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20 pages, 7303 KiB  
Article
Frequency Stability Evaluation in Low Inertia Systems Utilizing Smart Hierarchical Controllers
by Minas Patsalides, Christina N. Papadimitriou, Venizelos Efthymiou, Roberto Ciavarella, Marialaura Di Somma, Anna Wakszyńska, Michał Kosmecki, Giorgio Graditi and Maria Valenti
Energies 2020, 13(13), 3506; https://doi.org/10.3390/en13133506 - 7 Jul 2020
Cited by 11 | Viewed by 2520
Abstract
The high penetration of the Renewable Energy Sources and other emerging technologies likely to be installed in future power grids will pose new operational challenges to grid operators. One of the main issues expected to affect the operation of the power grid is [...] Read more.
The high penetration of the Renewable Energy Sources and other emerging technologies likely to be installed in future power grids will pose new operational challenges to grid operators. One of the main issues expected to affect the operation of the power grid is the impact of inverter-based technologies to the power system inertia and, hence, to system stability. Consequently, the main challenge of the future grid is the evaluation of the frequency stability in the presence of inverter-based systems and how the aforementioned technology can support frequency stability without the help of the rotating masses of the traditional power grid systems. To assess the above problem, this paper proposes a methodology to evaluate the frequency stability in a projection of the real distribution grid in Cyprus with the time horizon to be the year 2030. The power grid under investigation is evaluated with and without the presence of smart hierarchical controllers for providing support to the power system under disturbance conditions. The advanced controllers were applied to manage the available power resource in a fast and effective manner to maintain frequency within nominal levels. The controllers have been implemented in two hierarchical levels revealing useful responses for managing low-inertia networks. The first is set to act locally within a preselected area and the second level effectively supporting the different areas for optimal operation. After undertaking a significant number of simulations for time-series of one year, it was concluded from the results that the local control approach manages to minimize the frequency excursion effectively and influence all related attributes including the rate of change of frequency (RoCoF), frequency nadir and frequency zenith. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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22 pages, 5927 KiB  
Article
The Economic and Geographical Aspects of the Status of Small-Scale Photovoltaic Systems in Hungary—A Case Study
by Gábor Pintér, Henrik Zsiborács, Nóra Hegedűsné Baranyai, András Vincze and Zoltán Birkner
Energies 2020, 13(13), 3489; https://doi.org/10.3390/en13133489 - 6 Jul 2020
Cited by 12 | Viewed by 3535
Abstract
The use of solar energy is an obvious choice; the energy of the sun is not only indispensable for most processes in nature but it is also a clean, abundant, sustainable, and—most importantly—universally available resource. Although the further spread of photovoltaic systems, which [...] Read more.
The use of solar energy is an obvious choice; the energy of the sun is not only indispensable for most processes in nature but it is also a clean, abundant, sustainable, and—most importantly—universally available resource. Although the further spread of photovoltaic systems, which make use of this source of energy, is expected in the future all around the world, no comprehensive investigation has been conducted into the current situation of the small-scale photovoltaic power plants in Hungary, where this type of photovoltaic system is the most popular. By means of a case study, whose novelty lies in its focus on small-scale power plants and their complex examination, including economic and geographic indicators, this paper analyzes their status in Hungary. The study endeavors to establish the reasons for the popularity of this type of power plant and to identify some typical geographical locations with well-illustrated photovoltaic density. Residential, as well as business prosumers, were examined with the aim of learning more about the density of the small-scale photovoltaic systems and their geographical locations. Another goal was to calculate the average size of small-scale photovoltaic power plants and to gain more understanding of their economic aspects. The outcomes of this research include maps displaying the density of the small-scale photovoltaic power plants in Hungary and the results of the economic calculations for such investments. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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18 pages, 4158 KiB  
Article
Evaluation of Load Matching Indicators in Residential PV Systems-the Case of Cyprus
by Vladimir Z. Gjorgievski, Nikolas G. Chatzigeorgiou, Venizelos Venizelou, Georgios C. Christoforidis, George E. Georghiou and Grigoris K. Papagiannis
Energies 2020, 13(8), 1934; https://doi.org/10.3390/en13081934 - 15 Apr 2020
Cited by 11 | Viewed by 3542
Abstract
Three load matching indicators (self-consumption rate, self-sufficiency rate, loss of load probability) and the CO2 emissions were evaluated for 55 Cypriot households with 3 kWp rooftop photovoltaic (PV) generators. The calculations were performed using 30-minute generation and consumption data from a large [...] Read more.
Three load matching indicators (self-consumption rate, self-sufficiency rate, loss of load probability) and the CO2 emissions were evaluated for 55 Cypriot households with 3 kWp rooftop photovoltaic (PV) generators. The calculations were performed using 30-minute generation and consumption data from a large scale smart meter project in Cyprus. To investigate the effects of recent advances in local legislation, an analysis for higher PV capacities (5 kWp and 10 kWp) was also performed. The PV generation profiles for 5 kWp and 10 kWp PVs were obtained by scaling the 3 kWp PV generation profiles. The results showed that the self-consumption of the analyzed households varied seasonally, as it was related to their heating and cooling demand. More interestingly, the ratio between the households’ annual electricity generation and demand, formally defined here as generation-to-demand ratio (GTDR), was found to be related to the value ranges of the studied load matching indicators. Hence, on average, households with 3 kWp PV generators annually self-consumed 48.17% and exported 2,415.10 kWh of their PV generation. On the other hand, households with larger PV generators were characterized by a higher GTDR, but lower load matching capabilities. For the cases of 5 kWp and 10 kWp PV generators, the average self-consumption fell to 34.05% and 19.31%, while the exported PV generation was equal to 5,122.47 kWh, and 12,534.90 kWh, respectively. Along with lower load matching capabilities, households that generated more than they consumed were also found to have a lower potential for CO2 emissions reduction per installed kWp within the boundaries of the building. In this context, the GTDR could be used by stakeholders to characterize buildings, infer possible value ranges of more complex indicators and make evidence based decisions on policy and legislation. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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16 pages, 3663 KiB  
Article
A New Method for Peer-to-Peer Energy Exchange in Distribution Grids
by Ehsan Reihani, Pierluigi Siano and Michael Genova
Energies 2020, 13(4), 799; https://doi.org/10.3390/en13040799 - 12 Feb 2020
Cited by 17 | Viewed by 2745
Abstract
In this paper, distribution-level peer-to-peer energy exchange is proposed that allows increased matching between load and generation nodes. Contributions of the proposed improved matching system between the local load and generation nodes aim at making efficient use of unused power generation, reducing the [...] Read more.
In this paper, distribution-level peer-to-peer energy exchange is proposed that allows increased matching between load and generation nodes. Contributions of the proposed improved matching system between the local load and generation nodes aim at making efficient use of unused power generation, reducing the cost of electrical energy for consumers, and assisting utility companies by reducing transmission line congestion. The proposed system for matching the load and generation nodes consists of a financial layer and technical layer. In the financial layer, nodes with an excess of energy provide a price to sell energy, while the nodes needing energy bid on a price to purchase energy. A market-clearing mechanism using pool clearing is applied to determine a final price for peer-to-peer exchange. The technical layer determines the connection of energy transfer between the generation and load nodes while considering the distance, power flow constraints, and specified time windows. The proposed approach is verified in a five-node system and the results are discussed. Full article
(This article belongs to the Special Issue Smart Photovoltaic Energy Systems for a Sustainable Future)
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