Generalized Empirical Regret Bounds for Control of Renewable Energy Systems in Spatiotemporally Varying Environments

2021 ◽  
Author(s):  
Ben Haydon ◽  
Jack Cole ◽  
Laurel Dunn ◽  
Patrick Keyantuo ◽  
Fotini Chow ◽  
...  
Keyword(s):  
Renewable Energy ◽  
Control Strategies ◽  
Energy Resource ◽  
Mobile Systems ◽  
Wind Data ◽  
Maximum Probability ◽  
Data Set ◽  
Actual Performance ◽  
Regret Bounds ◽  
Varying Environments

Abstract This paper focuses on the empirical derivation of regret bounds for mobile systems that can optimize their locations in real time within a spatiotemporally varying renewable energy resource. The case studies in this paper focus specifically on an airborne wind energy system, where the replacement of towers with tethers and a lifting body allows the system to adjust its altitude continuously, with the goal of operating at the altitude that maximizes net power production. While prior publications have proposed control strategies for this problem, often with favorable results based on simulations that use real wind data, they lack any theoretical or statistical performance guarantees. In the present work, we make use of a very large synthetic data set, identified through parameters from real wind data, to derive probabilistic bounds on the difference between optimal and actual performance, termed regret. The results are presented for a variety of control strategies, including maximum probability of improvement, upper confidence bound, greedy, and constant altitude approaches. In addition, we use dimensional analysis to generalize the aforementioned results to other spatiotemporally varying environments, making the results applicable to a wider variety of renewably powered mobile systems. Finally, to deal with more general environmental mean models, we introduce a novel approach to modify calculable regret bounds to accommodate any mean model through what we term an "effective spatial domain."

Empirical Regret Bounds for Control in Spatiotemporally Varying Environments: A Case Study in Airborne Wind Energy

2019 ◽  
Author(s):  
Ben Haydon ◽  
Jack Cole ◽  
Laurel Dunn ◽  
Patrick Keyantuo ◽  
Tina Chow ◽  
...  
Keyword(s):  
Wind Energy ◽  
Control Strategies ◽  
Synthetic Data ◽  
Energy System ◽  
Mobile Systems ◽  
Wind Data ◽  
Maximum Probability ◽  
Data Set ◽  
Actual Performance ◽  
Regret Bounds

Abstract This paper focuses on the empirical derivation of regret bounds for mobile systems that can vary their locations within a spatiotemporally varying environment in order to maximize performance. In particular, the paper focuses on an airborne wind energy system, where the replacement of towers with tethers and a lifting body allows the system to adjust its altitude continuously, with the goal of operating at the altitude that maximizes net power production. While prior publications have proposed control strategies for this problem, often with favorable results based on simulations that use real wind data, they lack any theoretical or statistical performance guarantees. In the present work, we make use of a very large synthetic data set, identified through parameters from real wind data, to derive probabilistic bounds on the difference between optimal and actual performance, termed regret. The results are presented for a variety of control strategies, including a maximum probability of improvement, upper confidence bound, greedy, and constant altitude approaches.

Bias-correction of Surface Wind over Reunion and Mauritius Islands using CORDEX Regional Climate Model: RegCM4.7

2021 ◽  
Author(s):  
Swati Singh ◽  
Chao Tang ◽  
Béatrice Morel
Keyword(s):  
Renewable Energy ◽  
Wind Energy ◽  
Wind Turbines ◽  
Bias Correction ◽  
Energy Demand ◽  
Regional Climate ◽  
Surface Wind ◽  
Reanalysis Data ◽  
Wind Data ◽  
Data Set

<p>The world needs energy for its social and economic development. In the growing population and industrialization, there is an increasing demand for energy worldwide. The fossil fuel resources are still major resources for fulfilling this energy demand though they are responsible for the increased GHG emissions. Renewable energy is an alternative and greener approach towards meeting increasing energy demand. The wind energy is one of the most prominent resources of greener and renewable energy. The islands of Mauritius and Reunion in the southwest Indian Ocean are blessed with wind resources. The wind energy can be used to meet the demand of energy requirement of these two islands by increasing the number of wind turbines. However, energy generation with wind turbines is sensitive to the variability in the surface wind due to climate variability. The surface wind data available is sparse due to limited ground-based observation. The data quality is also affected by instrumental errors, and data is available only for past and present. Regional Climate Models (RCMs) are the main source of climate information for the present and the future. However, simulations from RCMs deal with biases from various sources and therefore need to bias-corrected. Here we use a transfer function based on the method proposed by Li et al. (2010) for the bias-correction of surface wind over Reunion and Mauritius islands. For this purpose, RegCM4.7 RCM from CORDEX AFR22 domain has been chosen for the time period of 1981-2004. The data is interpolated at 9 km resolution and bias-corrected with respect to surface wind data obtained from ERA5 land reanalysis data. The bias-corrected results are validated with the ERA5 land reanalysis data set.</p>

scholarly journals Offshore Wind Energy Resource Assessment across the Territory of Oman: A Spatial-Temporal Data Analysis

2021 ◽  
Vol 13 (5) ◽  
pp. 2862
Author(s):  
Amer Al-Hinai ◽  
Yassine Charabi ◽  
Seyed H. Aghay Kaboli
Keyword(s):  
Data Analysis ◽  
Wind Energy ◽  
Wind Turbines ◽  
Energy Resource ◽  
Wind Farms ◽  
Offshore Wind ◽  
Wind Data ◽  
Offshore Wind Energy ◽  
Offshore Wind Turbines ◽  
Wind Potential

Despite the long shoreline of Oman, the wind energy industry is still confined to onshore due to the lack of knowledge about offshore wind potential. A spatial-temporal wind data analysis is performed in this research to find the locations in Oman’s territorial seas with the highest potential for offshore wind energy. Thus, wind data are statistically analyzed for assessing wind characteristics. Statistical analysis of wind data include the wind power density, and Weibull scale and shape factors. In addition, there is an estimation of the possible energy production and capacity factor by three commercial offshore wind turbines suitable for 80 up to a 110 m hub height. The findings show that offshore wind turbines can produce at least 1.34 times more energy than land-based and nearshore wind turbines. Additionally, offshore wind turbines generate more power in the Omani peak electricity demand during the summer. Thus, offshore wind turbines have great advantages over land-based wind turbines in Oman. Overall, this work provides guidance on the deployment and production of offshore wind energy in Oman. A thorough study using bankable wind data along with various logistical considerations would still be required to turn offshore wind potential into real wind farms in Oman.

scholarly journals Influence of the Share of Renewable Energy Sources on the Level of Energy Security in EECCA Countries

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 903 ◽  
Author(s):  
Ivan Trifonov ◽  
Dmitry Trukhan ◽  
Yury Koshlich ◽  
Valeriy Prasolov ◽  
Beata Ślusarczyk
Keyword(s):  
Renewable Energy ◽  
Energy Security ◽  
Structural Characteristics ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Energy Sources ◽  
Structural Content ◽  
High Degree

In this study we aimed to determine the extent to which changes in the share of renewable energy sources, their structural complex, and the level of energy security in Eastern Europe, Caucasus and Central Asia (EECCA) countries in the medium- and long-term are interconnected. The study was performed through modeling and determination of the structural characteristics of energy security in the countries. The methodology of the approach to modeling was based on solving the problem of nonlinear optimization by selecting a certain scenario. For the study, the data of EECCA countries were used. The ability of EECCA countries to benefit from long-term indirect and induced advantages of the transformation period depends on the extent to which their domestic supply chains facilitate the deployment of energy transformation and induced economic activity. This study provides an opportunity to assess the degree of influence of renewable energy sources on the level of energy security of countries in the context of energy resource diversification. The high degree of influence of renewable energy sources on energy security in the EECCA countries has been proven in the implementation of the developed scenarios for its increase. Energy security is growing. At the same time, its level depends not only on an increase in the share of renewable sources but also on the structure of energy resources complex of countries, and the development of various renewable energy sources. Therefore, today the EECCA countries are forced not only to increase the share of renewable energy sources but also to attach strategic importance to the structural content of their energy complex.

Wind Turbine Aerodynamic Braking System Analysis Using Chord Wise Spacing

2015 ◽  
Vol 787 ◽  
pp. 217-221 ◽  
Author(s):  
B. Navin Kumar ◽  
K.M. Parammasivam
Keyword(s):  
Renewable Energy ◽  
Wind Turbine ◽  
Wind Velocity ◽  
Turbine Blade ◽  
Wind Turbines ◽  
Renewable Energy Sources ◽  
Energy Resource ◽  
Braking System ◽  
Extreme Wind ◽  
Wind Potential

Wind energy is one of the most significant renewable energy sources in the world. It is the only promising renewable energy resource that only can satisfy the nation’s energy requirements over the growing demand for electricity. Wind turbines have been installed all over the wind potential areas to generate electricity. The wind turbines are designed to operate at a rated wind velocity. When the wind turbines are exposed to extreme wind velocities such as storm or hurricane, the wind turbine rotates at a higher speed that affects the structural stability of the entire system and may topple the system. Mechanical braking systems and Aerodynamic braking systems have been currently used to control the over speeding of the wind turbine at extreme wind velocity. As a novel approach, it is attempted to control the over speeding of the wind turbine by aerodynamic braking system by providing the chord wise spacing (opening). The turbine blade with chord wise spacing alters the pressure distribution over the turbine blade that brings down the rotational speed of the wind turbine within the allowable limit. In this approach, the over speeding of the wind turbine blades are effectively controlled without affecting the power production. In this paper the different parameters of the chord wise spacing such as position of the spacing, shape of the spacing, width of the spacing and impact on power generation are analyzed and the spacing parameters are experimentally optimized.

Application of multivariable statistical techniques in plant-wide WWTP control strategies analysis

2007 ◽  
Vol 56 (6) ◽  
pp. 75-83 ◽  
Author(s):  
X. Flores ◽  
J. Comas ◽  
I.R. Roda ◽  
L. Jiménez ◽  
K.V. Gernaey
Keyword(s):  
Cluster Analysis ◽  
Control Strategies ◽  
Treatment Plant ◽  
Principal Component ◽  
Statistical Techniques ◽  
Data Sets ◽  
Data Set ◽  
Casual Relation ◽  
Evaluation Matrix ◽  
Natural Groups

The main objective of this paper is to present the application of selected multivariable statistical techniques in plant-wide wastewater treatment plant (WWTP) control strategies analysis. In this study, cluster analysis (CA), principal component analysis/factor analysis (PCA/FA) and discriminant analysis (DA) are applied to the evaluation matrix data set obtained by simulation of several control strategies applied to the plant-wide IWA Benchmark Simulation Model No 2 (BSM2). These techniques allow i) to determine natural groups or clusters of control strategies with a similar behaviour, ii) to find and interpret hidden, complex and casual relation features in the data set and iii) to identify important discriminant variables within the groups found by the cluster analysis. This study illustrates the usefulness of multivariable statistical techniques for both analysis and interpretation of the complex multicriteria data sets and allows an improved use of information for effective evaluation of control strategies.

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