Spatio-Temporal Solar–Wind Complementarity Assessment in the Province of Kalinga-Apayao, Philippines Using Canonical Correlation Analysis

Pilario, Karl Ezra S.; Ibañez, Jessa A.; Penisa, Xaviery N.; Obra, Johndel B.; Odulio, Carl Michael F.; Ocon, Joey D.

doi:10.3390/su14063253

Cited by 3 publications

(4 citation statements)

References 21 publications

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“…Dynamic time warping distance (DTW) is suitable for measuring the similarity of source charge time series in both numerical and morphological aspects [16,17]. In [18,19], a quantitative evaluation method for source load timing matching that considers the output fluctuation of renewable energy was proposed. However, currently, for renewable energy combined with energy storage power generation systems, the analysis focuses on the correlation characteristics of renewable energy output and load, whereas the temporal correlation of SGLS requires further study.…”

Section: Introductionmentioning

confidence: 99%

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Huang

Liu³

2023

IET Generation Trans & Dist

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The multi‐scale flexibility coordination of multiple storages is a key technology to enhance the diversified regulation ability of the power system. This paper first considers the interaction mechanism of multi‐type storage peak regulation time sequences based on the Euclidian distance, dynamic time warping distance, and storage correlation distance. A matching index was proposed to consider the temporal correlation, overall distribution characteristics, and dynamic characteristics of the net load and energy storage. The multitype storage coordination mode, including battery storage, pumped storage, and electric vehicles, was formulated, and a collaborative optimal scheduling system architecture of source‐grid‐load‐storage (SGLS) was constructed. To attain a low‐carbon economy, a collaborative optimal scheduling model of SGLS considering the dynamic time‐series complementarity of multiple energy storage systems was constructed. The Nash equilibrium theory was used to achieve friendly interaction among the source, grid, load, and storage. Then, an improved transfer reinforcement learning algorithm for SGLS was proposed, which used reinforcement learning and transfer learning algorithms combined with K‐means clustering and dual‐structure experience pool technology. The test results of actual regional power grid data indicated that the proposed strategy can effectively reduce the economic and carbon treatment costs of the system and improve the absorption capacity of renewable energy.

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Section: Introductionmentioning

confidence: 99%

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Huang

Liu³

2023

IET Generation Trans & Dist

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“…Studies have shown that high-frequency variations of the two resources mostly appear random with no correlation, while longer cycles show a stronger positive or negative correlation to each other. Studies have also proven that RES have high spatial complementarity as their separation distances between sites increase [44], [47], [53], [58].…”

Section: Generation Complementaritymentioning

confidence: 99%

“…Although geographical diversity has been explored and implemented through inter-regional connections moving surplus energy from one network to another, this option must be redesigned through spatial complementarity analysis for intermittent RES [48], [49]. Spatio-temporal complementarity considers both the temporal and spatial correlation and identifies the best complementary relationship [51], [58].…”

Section: Generation Complementaritymentioning

confidence: 99%

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Assessing Complementarity for Wind and Solar Energy in New Zealand

Tomon

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In recent years, there has been an increase in intermittent renewable energy sources (RES) in power system electricity mixes, leading to extensive research on quantifying the intermittency of primarily wind turbine generation (WTG) and solar PV generation and proposing mitigation strategies. Amongst other impacts that these fluctuations have on a traditional power grid, System Operators (SO) face the challenge of accurately predicting generation patterns across various time intervals. Studies conducted in other countries have explored different methods to minimize the impacts of intermittent generation, such as employing storage devices, smart grids, and geographical diversity based on generation complementarity. Generation complementarity refers to the negative correlation between different types of generation, which effectively smooths out intermittencies. For countries like New Zealand, with substantial potential for WTG and solar PV generation, investigating complementarity is crucial for system operators, plant owners, and investors. Previous generation correlation studies conducted in New Zealand did not include solar data until recently, so this study investigates the prospect of utilizing temporal (multiple RES in one location), spatial (one RES in multiple locations) and spatio-temporal (multiple RES in multiple locations) complementarity in New Zealand. The study utilizes 5 years’ worth of hourly observational data from local meteorological services and real power outputs of operating wind farms. The typical pre-processing steps were applied to data after which Spearman’s Rank Correlation (SRC), Cross-correlation and Canonical Correlation (CCA) analyses were applied to the modelled power data and derived datasets to determine complementarity. The site with the highest modelled solar PV power is located at the top of the South Island, while Northland, Bay of Plenty, and Hawkes Bay also demonstrate high solar PV generation. The modelled WTGs operate above 50% of their capacity for approximately 12% of the period while solar PV generation remains below 40% of its modelled capacity for 99% of the time. Among the operating wind farms, generators in the North Island operate at a higher percentage of their capacity compared to those on the South Island, particularly during the middle of summer, spring, and autumn.Although the temporal complementarity analysis does not identify significant complementarity, there is a higher likelihood of exhibiting complementary characteristics during colder months and the time window between 12 pm and 2 pm daily. Spatial complementarity analysis results follow a similar trend as observed in studies conducted in other countries but the correlation coefficients in this study are also influenced by its proximity to the coast and the degree of exposure or sheltering from sea winds even at considerable separation distances. The spatio-temporal complementarity analysis reveals a dependence on seasonal cycles. The most optimal spatio-temporal complementary pairs exhibit higher coefficients during transitional months, suggesting that their complementary relationship is most prominent during the shift from one primary season to another. The study reveals the need for further work to be done in this research area particularly for New Zealand. This will require contributions from multi-disciplines to reveal reliable studies that investigate the effects of weather variables on the evolving power system.

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Assessing Complementarity for Wind and Solar Energy in New Zealand

Tomon,

Vong,

Rayudu

2024

2024 18th International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)

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invaluable wisdom and guidance and for challenging me to exceed my expectations. I could not have had better mentors.I would also like to thank my family, friends, NCC team members and my loving husband for their unwavering support throughout the past year and a half, which enabled me to undertake this level of study while also managing the organization of my wedding within the same year.Lastly, I would like to extend my thanks to the Te Herenga Waka -Victoria University of Wellington for awarding me the "School of Engineering and Computer Science Master's by Thesis Scholarship (July 2022)." This financial support has been instrumental in enabling me to pursue my academic journey.To everyone who has contributed to my journey thus far, I Thank You.

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Spatio-Temporal Solar–Wind Complementarity Assessment in the Province of Kalinga-Apayao, Philippines Using Canonical Correlation Analysis

Cited by 3 publications

References 21 publications

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Collaborative optimization strategy of source‐grid‐load‐storage considering dynamic time series complementarity of multiple storages

Assessing Complementarity for Wind and Solar Energy in New Zealand

Assessing Complementarity for Wind and Solar Energy in New Zealand

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