Short-term variability and extremes in wind and solar resources under a changing climate

The increasing share of variable renewable energy (VRE) generation poses challenges to power systems. Possible challenges include adequacy of reserves, planning and operation of power systems, and interconnection expansion studies in future power systems with very different generation patterns compared to today. To meet these challenges, there is a need to develop models and tools to analyze the variability and uncertainty in VRE generation. To address the varied needs, the tools should be versatile and applicable to different geographical and temporal scales. Time series simulation tools can be used to model both today and future scenarios with varying VRE installations. Correlations in Renewable Energy Sources (CorRES) is a simulation tool developed at Technical University of Denmark, Department of Wind Energy capable of simulating both wind and solar generation. It uses a unique combination of meteorological time series and stochastic simulations to provide consistent VRE generation and forecast error time series with temporal resolution in the minute scale. Such simulated VRE time series can be used in addressing the challenges posed by the increasing share of VRE generation. These capabilities will be demonstrated through three case studies: one about the use of large‐scale VRE generation simulations in energy system analysis, and two about the use of the simulations in power system operation, planning, and analysis.This article is categorized under: Wind Power > Systems and Infrastructure Energy Infrastructure > Systems and Infrastructure Energy Systems Economics > Systems and Infrastructure

Optimize and analyze a large-scale grid-tied solar PV-powered SWRO system for sustainable water-energy nexus

This paper presents an evaluation of two simulations by regional climate model (RCM) ALADIN-Climate/CZ with different sizes of integration domain and their driving simulation of global climate model (GCM) ARPEGE-Climat over central Europe during the period 1961–2010. After a brief evaluation of seasonal means of air temperature characteristics (daily mean, maximum and minimum temperature) and their variability, we focus on the ability of the simulations to represent observed changes in seasonal mean air temperature and its variability. We distinguish between intrinsic and trend-induced variability. Moreover, the dependence on the size of the integration domain and the improvement brought about by the nested RCM compared to the driving GCM are analysed. Both the evaluation of temperature means and variability and the evaluation of their changes confirm that RCM simulation on a larger domain often differs more considerably from driving GCM than simulation on a smaller domain. The larger domain simulation usually produces smaller biases for mean temperature but has worse agreement with observations in terms of variability. Further, the areas with the greatest discrepancies are often in the south-eastern region. In addition, noticeable differences between RCM and GCM simulations mostly emerge for the Alpine region and eastern regions. A possible explanation is the complex terrain and larger distance from domain boundaries. Moreover, it was analysed whether removing of the linear trend enhances the representation of changes in variability. This was not generally confirmed. Only in summer the simulations underestimated the observed increase in intrinsic variability less considerably than for total variability. However, biases were still considerable in many cases.

Solar energy system is one of the most promising renewable energy resources to meet the energy demand. This resource has been developed and utilized in many countries. Indonesia, as one of the tropical countries has been blessed with a huge amount of radiant energy from the sun during the whole year. However, the solar energy resource data is very limited. Therefore, the purpose of this research is to develop an automatic solar station to measure the potential of solar energy resource in the unique tropical region like Pekanbaru City. The availability of solar energy resource data are the foundation of information for designing, utilizing and deploying of solar energy generation and technologies. It is expected that the automatic solar station has capability to measure not only solar radiation data but also other related parameters such as air temperature and humidity. The measured solar energy resource data are also designed as foundation of solar energy resource data base of Pekanbaru City Indonesia.

Due to the long and narrow regional characteristics of Inner Mongolia, there are obvious climatic differences between the east and the west, and various meteorological factors have different influences on the development and utilization of solar energy. The abundance and stability index of solar energy resources are relatively high in the central and western region of Inner Mongolia, but there are more sandstorms, high temperature and strong wind. The eastern region is greatly affected by cloud cover, relative humidity and snowfall, which weakens the solar radiation. Through the comprehensive evaluation of the solar energy resources and meteorological elements, it is found that from the Alashan League to the west of Xilin Gol League, and the most of the Chifeng City are low-risk areas, which are relatively suitable for the development and utilization of rooftop solar energy. The central and northern areas of hulunbuir are high-risk areas, which is not suitable for that. Based on the meteorological industry standard “Solar Energy Resource Assessment Method”, we calculate the solar energy resources abundance and stability index, combined with the annual surface meteorological data of 119 meteorological stations in Inner Mongolia from 1988 to 2018. The distribution characteristics of solar energy resources and meteorological elements in Inner Mongolia is analyzed and the suitability and meteorological risks of rooftop solar resources development and utilization are evaluated.

Variation of surface solar radiation components from 2016 to 2020 in China: Perspective from geostationary satellite observation with a high spatiotemporal resolution

Background:The geographic range of the tick Amblyomma americanum, a vector of diseases of public health significance such as ehrlichiosis, has expanded from the southeast of the United States northward during the 20th century. Recently, populations of this tick have been reported to be present close to the Canadian border in Michigan and New York states, but established populations are not known in Canada. Previous research suggests that changing temperature patterns with climate change may influence tick life cycles and permit northward range expansion of ticks in the northern hemisphere.Objectives:We aimed to estimate minimal temperature conditions for survival of A. americanum populations at the northern edge of the tick’s range and to investigate the possibility of range expansion of A. americanum into northern U.S. states and southern Canada in the coming decades.Methods:A simulation model of the tick A. americanum was used, via simulations using climate data from meteorological stations in the United States and Canada, to estimate minimal temperature conditions for survival of A. americanum populations at the northern edge of the tick’s range.Results:The predicted geographic scope of temperature suitability [ annual cumulative degree days (DD) ] included most of the central and eastern U.S. states east of longitude 110°W, which is consistent with current surveillance data for the presence of the tick in this region, as well as parts of southern Quebec and Ontario in Canada. Regional climate model output raises the possibility of northward range expansion into all provinces of Canada from Alberta to Newfoundland and Labrador during the coming decades, with the greatest northward range expansion (up to by the year 2100) occurring under the greenhouse gas (GHG) emissions of Representative Concentration Pathway (RCP) 8.5. Predicted northward range expansion was reduced by approximately half under the reduced GHG emissions of RCP4.5.Discussion:Our results raise the possibility of range expansion of A. americanum into northern U.S. states and southern Canada in the coming decades, and conclude that surveillance for this tick, and the diseases it transmits, would be prudent. https://doi.org/10.1289/EHP5668

Several countries continue to invest in variable renewable energy (VRE) sources to replace fossil fuels and achieve a nationally determined contribution. Consequently, as the share of VRE generation in each country's power grid increases, its curtailment also increases. Current studies on VRE curtailment are based on a comparative analysis of statistical data collected from different countries. However, only a few studies present detailed results based on historical curtailment data collected from individual wind farms. This study analyzes the curtailment data collected for three wind farms over four years. The duration, curtailed output, and cost per curtailment were determined to be 200 min, 38 MWh, and $3.02k, respectively. Finally, the curtailment loss to wind farms caused by the increasing share of VRE generation in the power grid was estimated. The curtailed output and curtailment cost are estimated to increase by 1.3 GWh and $107.6k, respectively, when the share of VRE in the power grid increases by 1%. These findings can aid in identifying the curtailment experienced by wind farm operators and subsequent potential economic losses. Moreover, they can form the basis for establishing an efficient curtailment cost compensation system.

Introducing a new wind speed complementarity model

The power system inertia is gradually decreasing with the growing share of variable renewable energy (VRE). This may jeopardize the frequency dynamics and challenges the secure operation of power systems. In this paper, the concept of frequency security margin is proposed to quantify the system frequency regulation ability under contingency. It is defined as the maximum power imbalance that the system can tolerate while keeping frequency within the tolerable frequency range. A frequency constrained unit commitment (FCUC) model considering frequency securitymargin is proposed. Firstly, the analytical formulation of system frequency nadir is derived while considering both the frequency regulation characteristics of the thermal generators and the frequency support from VRE plants. Then, the frequency security margin is analytically formulated and piecewise linearized. A novel FCUC model is proposed by incorporating linear frequency security constraints into the traditional unit commitment model. Case studies on a modified IEEE RTS-79 system and HRP-38 system are provided to verify the effectiveness of the proposed FCUC model. The impacts of VRE penetration on system frequency security are analyzed using frequency security margin.

Energy systems with a high share of variable renewable energy are more vulnerable to sudden changes in the system operation. This is especially emphasized on small systems such as energy systems on geographical islands. Because of these reasons, there is a need for quantifying the risk of energy scenarios of such systems. This paper presents a novel robust risk assessment method under demand uncertainty for energy planning scenarios for the islands. The method uses graph theory for the representation of power system topology. The Poisson distribution is used for calculating the probability of power system element failure. The robust modelling approach is applied by the introduction of auxiliary variables and compared to the deterministic model results. Four energy planning scenarios for Unije island are modelled and subjugated to several power system outages resulting in a risk vector calculated as the product of probability vector and damage matrix. The study also presents a zero-import risk energy planning scenario for Unije island that is achieved for a system of 0.5 MW photovoltaic plant and 3.55 MWh battery storage system.

Spatial variability analysis of the solar energy resources for future urban energy applications using Meteosat satellite-derived datasets

Despite South Africa’s international recognition in solar energy investments, the country is struggling to meet its growing energy needs. In recent years, national blackouts and load shedding have been a recurring experience in the country. The high cost of electrification and the overstrained national grid have left several rural communities without access to electricity. This study aims to explore the solar energy resources and performance of a 3.8 kWp stand-alone residential photovoltaic (PV) power system in one of the underutilised regions in South Africa. The study mainly uses ground measured solar radiation data to evaluate the solar resources of Alice and compare them with those in other parts of the world with mega solar PV projects. The components of solar radiation considered are global horizontal irradiance (GHI), direct normal irradiance (DNI), and diffuse horizontal irradiance (DHI). The average total daily GHI, DNI, and DHI of Alice were 4.98, 5.74, and 1.44 kWh/m2. Clear sky conditions were found to occur on 233 days in the monitoring year, resulting in an average total daily GHI of 6.13 kWh/m2, DNI of 6.73 kWh/m2 and DHI of 0.17 kWh/m2. The findings indicated that Alice possesses abundant solar resources for PV and concentrated solar power generation, and is comparable to other regions internationally.

Many regions in the world exhibit temporal complementarity of solar and wind energy. In such regions, during certain time periods, when more solar energy is present, lesser amount of wind energy is available and vice-verse. The motivation of this work is to develop a general planning methodology for the integration of these variable renewable energy (VRE) resources in smart power grids, while exploiting temporal complementarity to minimize the supply demand mismatch. We develop an appropriate analytical framework to determine the total investment needed in such VRE resources and the fraction of the total investment in each resource. A multivariate optimization problem is formulated and an optimal algorithm is developed to determine these parameters. To test the proposed methodology, a case study is developed for a region in Northern Ireland. In this region, based on the historical data of past 10 years and using daily average wind and solar capacity factors, we determine the Pearson correlation coefficient, which turns out to be −0.34, showing a sufficient degree of complementarity (anti-correlation) between solar and wind energy. Planning parameters are determined for different load profiles in our case study. General conclusion of the work is that once the temporal complementarity of solar and wind energy resources is exploited, the net supply variability is significantly reduced in microgrids. However, the total investment costs also increases, which is offset by the savings in the storage costs. In addition, reduced variability also leads to a reduction in storage losses, emissions losses, dispatch losses, fuel costs and network congestion.

Enhancing solar energy generation utilization along highways: optimizing electric vehicle charging-swapping schemes and scheduling mobile energy storage systems