Variability Characteristics of European Wind and Solar Power Resources—A Review

Abstract

This paper reviews the most recent and relevant research into the variability characteristics of wind and solar power resources in Europe. The background for this study is that wind and solar resources will probably constitute major components of the future European power system. Such resources are variable, and EU plans to balance the variability with more grids and demand response. Thus, planning for the future power system requires an in-depth understanding of the variability. Resource variability is a multi-faceted concept best described using a range of distinct characteristics, and this review is structured on the basis of seven of these: Distribution Long-Term (hours to years), Distribution Short-Term (less than one hour), Step Changes, Autocorrelation, Spatial Correlation, Cross Correlation and Predictable Patterns. The review presents simulations and empirical results related to resource variability for each of these characteristics. Results to date reveal that the variability characteristics of the future power system is limited understood. This study recommends the development of a scheme for greater systematic assessment of variability. Such a scheme will contribute to the understanding of the impacts of variability and will make it possible to compare alternative power production portfolios and impacts of grid expansions, demand response and storage technologies.

Principal Mismatch Patterns Across a Simplified Highly Renewable European Electricity Network

“…The planning for such systems requires an in-depth understanding of the variable mismatch between weather and demand patterns on multiple time and length scales [1,2]. The spectrum of prominent temporal fluctuations of wind and solar power generation ranges from seconds to years [3][4][5][6], and impacts the design and operation of power systems [7][8][9][10][11][12][13].…”

Impact of the Complementarity between Variable Generation Resources and Load on the Flexibility of the Korean Power System

“…Each generator has two states, i.e., 0 (failure) or 1 (online). Thus, C 1 consists of "(0, 0), (0, 1), (1, 0), (1,1)." The probability of each element is calculated using a Markov-chain-based two-state model [29].…”

“…Among the RES, variable generation resources (VGRs) share the largest percentage, and their expansion is already progressing rapidly. For example, the share of RES capacity in Denmark and Spain in 2013 was 56% and 42%, respectively, and VGRs, such as wind and PV systems constituted 83% and 59% of this share, respectively [1]. In Korea, according to the national expansion plan [2], the share of VGR is expected to account for approximately 22% of the total installed capacity by 2029.…”

Correlation Characteristic Analysis for Wind Speed in Different Geographical Hierarchies

“…Especially in the northwest of China, the Hexi Corridor, known for its abundant wind and solar resources, has continuously developed large-scale wind power bases. In addition to the intermittency and uncertainty of wind energy, wind speed correlation information is of great necessity for power system planning and operation [1][2][3][4][5][6] with geographically distributed wind farms driven by the presence of increasing scale of wind power bases.…”