Special Issue "Modeling of Variable Renewable Generation: Wind and Solar Photovoltaic Power Plants"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Wind, Wave and Tidal Energy".

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Prof. Dr. Emilio Gomez-Lazaro
Website
Guest Editor
1. Renewable Energy Research Institute, Universidad de Castilla-La Mancha, 13001 Ciudad Real, Spain;
2. Department of Electrical Engineering, Electronics, Control Communications, Escuela Técnica Superior de Ingenieros Industriales de Albacete, 02071 Albacete, Spain
Interests: power electronics and power systems; renewable energy systems; modeling; dynamic performance of inverter-based generation in power systems; maintenance of renewable energy power installations; transmission and distribution studies
Special Issues and Collections in MDPI journals
Dr. Sergio Martin-Martinez
Website
Guest Editor
Renewable Energy Research Institute, Escuela de Ingenieros Industriales de Albacete. Department of Electrical Engineering, Electronics, Control Communications. Universidad de Castilla-La Mancha, 02071 Albacete, Spain
Interests: renewable energy systems; variability and uncertainty of variable renewable energy sources; maintenance of renewable energy power installations; Participation of VRES in balancing markets; PV systems performance

Special Issue Information

Dear Colleagues,

At present, variable renewable energy (VRE) generation is becoming of key importance due to the relevant impact on power systems. Specifically, wind and solar PV power modeling should be addressed due to the importance in the energy mix of actual and future power systems. Modeling issues could address real time and hardware-in-the-loop (HIL) simulations, too.

This Special Issue aims to present solutions facing the challenges related to VRE modeling, specifically wind and solar PV generation. Topics of interest include but are not limited to:

  • Detailed VRE modeling (wind turbines, wind power plants, and solar PV power plants) for accurate response and design purposes;
  • Simplified VRE modeling (wind turbines, wind power plants, and solar PV power plants) with application to power system studies; model assessment according to national and international standards, such as IEC 61400-27 or WECC;
  • Modeling of new control strategies for wind power plants and solar PV power plants;
  • Modeling of power system operation with large amounts of wind and solar power, including transnational or intercontinental studies; transient stability studies;
  • Modeling of transmission planning and operation, taking into account VRE resource location and characteristics;
  • Grid support and ancillary services provided by wind and solar PV generation; grid code requirements;
  • Modeling of efficient electricity markets with large amounts of VREs;
  • Model validation.

Prof. Dr. Emilio Gomez-Lazaro
Dr. Sergio Martin-Martinez
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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

  • wind power plants
  • solar PV power plants
  • variable renewable energy modeling
  • variable renewable energy integration
  • power systems
  • model validation

Published Papers (8 papers)

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Research

Open AccessArticle
A Study on Optimal Power System Reinforcement Measures Following Renewable Energy Expansion
Energies 2020, 13(22), 5929; https://doi.org/10.3390/en13225929 - 13 Nov 2020
Abstract
Renewable energy generation capacity in Korea is expected to reach about 63.8 GW by 2030 based on calculations using values from a power plan survey (Korea’s renewable energy power generation project plan implemented in September 2017) and the “3020” implementation plan prescribed in [...] Read more.
Renewable energy generation capacity in Korea is expected to reach about 63.8 GW by 2030 based on calculations using values from a power plan survey (Korea’s renewable energy power generation project plan implemented in September 2017) and the “3020” implementation plan prescribed in the 8th Basic Plan for Long-Term Electricity Supply and Demand that was announced in 2017. In order for the electrical grid to accommodate this capacity, an appropriate power system reinforcement plan is critical. In this paper, a variety of scenarios are constructed involving renewable energy capacity, interconnection measures and reinforcement measures. Based on these scenarios, the impacts of large-scale renewable energy connections on the future power systems are analyzed and a reinforcement plan is proposed based on the system assessment results. First, the scenarios are categorized according to their renewable energy interconnection capacity and electricity supply and demand, from which a database is established. A dynamic model based on inverter-based resources is applied to the scenarios here. The transmission lines, high-voltage direct current and flexible alternating current transmission systems are reinforced to increase the stability and capabilities of the power systems considered here. Reinforcement measures are derived for each stage of renewable penetration based on static and dynamic analysis processes. As a result, when large-scale renewable energy has penetrated some areas in the future in Korean power systems, the most stable systems could be optimally configured by applying interconnection measure two and reinforcement measure two as described here. To verify the performance of the proposed methodology, in this paper, comprehensive tests are performed based on predicted large-scale power systems in 2026 and 2031. Database creation and simulation are performed semi-automatically here using Power System Simulator for Engineering (PSS/E) and Python. Full article
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Open AccessArticle
Parametric Study on a Performance of a Small Counter-Rotating Wind Turbine
Energies 2020, 13(15), 3880; https://doi.org/10.3390/en13153880 - 29 Jul 2020
Abstract
A small Counter-Rotating Wind Turbine (CRWT) has been proposed and its performance has been investigated numerically. Results of a parametric study have been presented in this paper. As parameters, the axial distance between rotors and a tip speed ratio of each rotor have [...] Read more.
A small Counter-Rotating Wind Turbine (CRWT) has been proposed and its performance has been investigated numerically. Results of a parametric study have been presented in this paper. As parameters, the axial distance between rotors and a tip speed ratio of each rotor have been selected. Performance parameters have been compared with reference to a Single Rotor Wind Turbine (SRWT). Simulations were carried out with Computational Fluids Dynamics (CFD) solver and a Large Eddy Scale approach to model turbulences. An Actuator Line Model has been chosen to represent rotors in the computational domain. Summing up the results of simulation tests, it can be stated that when constructing a CRWT turbine, rotors should be placed at a distance of at least 0.5 D (where D is rotor outer diameter) or more. One can then expect a noticeable power increase compared to a single rotor turbine. Placing the second rotor closer than 0.5 D guarantees a significant increase in power, but in such configurations, dynamic interactions between the rotors are visible, resulting in fluctuations in torque and power. Dynamic interactions between rotor blades above 0.5 D are invisible. Full article
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Open AccessArticle
Verification of Utility-Scale Solar Photovoltaic Plant Models for Dynamic Studies of Transmission Networks
Energies 2020, 13(12), 3191; https://doi.org/10.3390/en13123191 - 19 Jun 2020
Cited by 1
Abstract
In recent years, there has been a growing need for accurate models that describe the dynamics of renewable energy sources, especially photovoltaic sources and wind turbines. In light of this gap, this work focuses on the validation of standard dynamic models developed by [...] Read more.
In recent years, there has been a growing need for accurate models that describe the dynamics of renewable energy sources, especially photovoltaic sources and wind turbines. In light of this gap, this work focuses on the validation of standard dynamic models developed by the Western Electricity Coordinating Council (WECC), using actual measurements from the Western Texas and Southern California transmission networks. The tests are based on the North American Electric Reliability Corporation compliance standards and include dynamic stability tests for volt-varcontrol and primary frequency response. Through an extensive set of field tests, we show that the WECC generic models can be used to simulate real dynamic phenomena in large-scale solar photovoltaic power plants, and we propose guidelines for correct usage of these models. The results show that the WECC models are especially accurate when the photovoltaic system is connected with a low impedance to the main network. We also show that the tested WECC models successfully predict the frequency response of an actual grid event that occurred in the Electric Reliability Council of Texas and which resulted in a loss of nearly 1.365 GW. This result supports the use of these models in the study of large-scale dynamic phenomena that include renewable energy sources. Full article
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Open AccessArticle
Less Information, Similar Performance: Comparing Machine Learning-Based Time Series of Wind Power Generation to Renewables.ninja
Energies 2020, 13(9), 2277; https://doi.org/10.3390/en13092277 - 05 May 2020
Abstract
Driven by climatic processes, wind power generation is inherently variable. Long-term simulated wind power time series are therefore an essential component for understanding the temporal availability of wind power and its integration into future renewable energy systems. In the recent past, mainly power [...] Read more.
Driven by climatic processes, wind power generation is inherently variable. Long-term simulated wind power time series are therefore an essential component for understanding the temporal availability of wind power and its integration into future renewable energy systems. In the recent past, mainly power curve-based models such as Renewables.ninja (RN) have been used for deriving synthetic time series for wind power generation, despite their need for accurate location information and bias correction, as well as their insufficient replication of extreme events and short-term power ramps. In this paper, we assessed how time series generated by machine learning models (MLMs) compare to RN in terms of their ability to replicate the characteristics of observed nationally aggregated wind power generation for Germany. Hence, we applied neural networks to one wind speed input dataset derived from MERRA2 reanalysis with no location information and two with additional location information. The resulting time series and RN time series were compared with actual generation. All MLM time series feature an equal or even better time series quality than RN, depending on the characteristics considered. We conclude that MLM models show a similar performance to RN, even when information on turbine locations and turbine types is unavailable. Full article
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Open AccessArticle
The Impact of Imperfect Weather Forecasts on Wind Power Forecasting Performance: Evidence from Two Wind Farms in Greece
Energies 2020, 13(8), 1880; https://doi.org/10.3390/en13081880 - 12 Apr 2020
Cited by 1
Abstract
Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of [...] Read more.
Weather variables are an important driver of power generation from renewable energy sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the power generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical and machine learning) for the case of wind power generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% prediction intervals. The results indicate that different methods should be considered according to the uncertainty characterizing the weather forecasts. Full article
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Open AccessArticle
Submission of a WECC DFIG Wind Turbine Model to Spanish Operation Procedure 12.3
Energies 2019, 12(19), 3749; https://doi.org/10.3390/en12193749 - 30 Sep 2019
Cited by 6
Abstract
Power systems are currently witnessing a high wind-power penetration due to the development and commissioning of an increasing number of wind-power plants. This new scenario inevitably changes the way power systems are operated, mainly due to the uncertainties associated with wind, with the [...] Read more.
Power systems are currently witnessing a high wind-power penetration due to the development and commissioning of an increasing number of wind-power plants. This new scenario inevitably changes the way power systems are operated, mainly due to the uncertainties associated with wind, with the proper integration of this renewable energy source into the grid emerging as a new challenge. Unlike other highly flexible energy sources that can be used on demand according to the market needs, wind energy production is intermittent and non-dispatchable. In this context, transient stability analyses through the dynamic simulation of wind-turbine models and wind-power plants must be carried out. Moreover, as many countries have their own grid codes, the compliance requirements to connect wind farms to the network may be significantly different, depending on the specific region. In light of the above, this paper addresses the submission to Spanish Operation Procedure 12.3 (PO 12.3), for the first time, of one of the most advanced wind-turbine models, the generic Type 3 or doubly fed induction generator defined by the Western Electricity Coordinating Council (WECC) Second-Generation guidelines. The results show, on the one hand, the notable effect of the transformer inrush current, which influences the accuracy of the behavior of the generic wind-turbine model, and, on the other hand, the inability of the generic model to represent the transient periods of actual wind turbines. However, when the validation criteria is applied at the low-voltage measurement point, the WECC model fully complies with Spanish grid code PO 12.3. Full article
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Open AccessArticle
Renewable Energy Sources Penetration in Greece: Characteristics and Seasonal Variation of the Electricity Demand Share Covering
Energies 2019, 12(12), 2441; https://doi.org/10.3390/en12122441 - 25 Jun 2019
Cited by 4
Abstract
The significant penetration of renewables, in the Hellenic electricity system, during the last 12 years, was based on feed-in tariff-supporting schemes, according to the compliance to European Directives. The characteristics of this penetration are presented and analyzed in this paper based on real [...] Read more.
The significant penetration of renewables, in the Hellenic electricity system, during the last 12 years, was based on feed-in tariff-supporting schemes, according to the compliance to European Directives. The characteristics of this penetration are presented and analyzed in this paper based on real data. Photovoltaics, wind parks, hydroelectric plants, biomass-driven plants, and cogeneration systems are examined. The cost of the feed-in tariff incentives is qualified and analyzed. Simple but effective models are proposed to describe renewable seasonal variation: (a) A simple cosine model adequately describes the seasonal performance of various renewable technologies in terms of capacity factor; (b) a smart seasonal model based on the separation between winter and summer consumption activities (both following normal distributions) adequately describes the electricity consumption profile. The predicted values of renewable shares using the proposed models were also validated with historical data. Thus, the applied models can be used to forecast renewable shares under different penetration scenarios. Full article
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Open AccessArticle
Identifying the Drivers of Wind Capacity Additions: The Case of Spain. A Multiequational Approach
Energies 2019, 12(10), 1944; https://doi.org/10.3390/en12101944 - 21 May 2019
Cited by 4
Abstract
An abundant volume of literature has been devoted to the analysis of the drivers of renewable electricity capacity additions in general and wind energy in particular. Nevertheless, whereas the direct influence of several explanatory variables has been considered, indirect effects, which refer to [...] Read more.
An abundant volume of literature has been devoted to the analysis of the drivers of renewable electricity capacity additions in general and wind energy in particular. Nevertheless, whereas the direct influence of several explanatory variables has been considered, indirect effects, which refer to impacts of explanatory variables on another explanatory variable which, in turn, influence capacity additions, have been neglected. However, those effects need to be taken into account in order to properly grasp the full influence of the explanatory variables in general, and the policy variable in particular, on capacity additions (whether in wind energy generation or other energy systems). The aim of this paper is to identify the drivers of wind energy capacity additions. Based on data over the 1998–2015 period for Spain, a country with a substantial deployed wind capacity, we estimate a three-stage least squares multiecuational econometric model, which allows the analysis of direct and indirect effects as mediated by their influence on intermediate variables. Our results show that, as expected, wind capacity additions are positively and significantly driven by renewable energy support and negatively driven by the material costs of wind energy. Other variables are related to capacity additions in an indirect manner, i.e., through their influence on intermediate variables, i.e., electricity demand and electricity prices. This includes the positive impact of GDP, wind share, capacity load and price of oil. Others have a negative impact (tax share in the electricity price and electricity transport costs). Finally, no statistically significant relationship can be observed for the risk premium, interest rates and the price of gas. Our findings suggest that the success of renewable energy policy instruments might be contingent upon the level of other variables and, particularly, electricity consumption. Full article
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Title:The impact of imperfect weather forecasts on wind forecasting performance

Authors: Evangelos Spiliotis (National Technical University of Athens), Fotios Petropoulos (University of Bath) and Konstantinos Nikolopoulos (Bangor University)

Abstract: Weather variables are an important driver to energy generation from alternative sources. However, accurately predicting such variables is a challenging task, which has a significant impact on the accuracy of the energy generation forecasts. In this study, we explore the impact of imperfect weather forecasts on two classes of forecasting methods (statistical versus machine learning) for the case of wind energy generation. We perform a stress test analysis to measure the robustness of different methods on the imperfect weather input, focusing on both the point forecasts and the 95% confidence intervals.
 
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