| |
|
|
|
|
|
|
|
|
1. |
Record Nr. |
UNISA996418258003316 |
|
|
Autore |
Jacob Maria |
|
|
Titolo |
Forecasting and Assessing Risk of Individual Electricity Peaks [[electronic resource] /] / by Maria Jacob, Cláudia Neves, Danica Vukadinović Greetham |
|
|
|
|
|
|
|
Pubbl/distr/stampa |
|
|
Cham, : Springer Nature, 2020 |
|
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
|
|
|
|
|
|
|
|
|
ISBN |
|
|
|
|
|
|
Edizione |
[1st ed. 2020.] |
|
|
|
|
|
Descrizione fisica |
|
1 online resource (XII, 97 p. 38 illus., 35 illus. in color.) |
|
|
|
|
|
|
Collana |
|
SpringerBriefs in Mathematics of Planet Earth, Weather, Climate, Oceans, , 2509-7326 |
|
|
|
|
|
|
|
|
Disciplina |
|
|
|
|
|
|
Soggetti |
|
Mathematics |
Statistics |
Energy efficiency |
Algorithms |
Energy systems |
Mathematics of Planet Earth |
Statistical Theory and Methods |
Energy Efficiency |
Energy Systems |
|
|
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Nota di contenuto |
|
Preface -- Introduction -- Short Term Load Forecasting -- Extreme Value Theory -- Extreme Value Statistics -- Case Study -- References -- Index. |
|
|
|
|
|
|
|
|
Sommario/riassunto |
|
The overarching aim of this open access book is to present self-contained theory and algorithms for investigation and prediction of electric demand peaks. A cross-section of popular demand forecasting algorithms from statistics, machine learning and mathematics is presented, followed by extreme value theory techniques with examples. In order to achieve carbon targets, good forecasts of peaks are essential. For instance, shifting demand or charging battery depends on correct demand predictions in time. Majority of forecasting |
|
|
|
|
|
|
|
|
|
|
|
|
|
algorithms historically were focused on average load prediction. In order to model the peaks, methods from extreme value theory are applied. This allows us to study extremes without making any assumption on the central parts of demand distribution and to predict beyond the range of available data. While applied on individual loads, the techniques described in this book can be extended naturally to substations, or to commercial settings. Extreme value theory techniques presented can be also used across other disciplines, for example for predicting heavy rainfalls, wind speed, solar radiation and extreme weather events. The book is intended for students, academics, engineers and professionals that are interested in short term load prediction, energy data analytics, battery control, demand side response and data science in general. . |
|
|
|
|
|
|
2. |
Record Nr. |
UNINA9910227350403321 |
|
|
Autore |
Judy Simon |
|
|
Titolo |
Plant Competition in a Changing World |
|
|
|
|
|
Pubbl/distr/stampa |
|
|
|
|
|
|
Descrizione fisica |
|
1 online resource (154 p.) |
|
|
|
|
|
|
Collana |
|
Frontiers Research Topics |
|
|
|
|
|
|
Soggetti |
|
|
|
|
|
|
Lingua di pubblicazione |
|
|
|
|
|
|
Formato |
Materiale a stampa |
|
|
|
|
|
Livello bibliografico |
Monografia |
|
|
|
|
|
Sommario/riassunto |
|
Competitiveness describes a key ability important for plants to grow and survive abiotic and biotic stresses. Under optimal, but particularly under non-optimal conditions, plants compete for resources including nutrients, light, water, space, pollinators and other. Competition occurs above- and belowground. In resource-poor habitats, competition is generally considered to be more pronounced than in resource-rich habitats. Although competition occurs between different players within an ecosystem such as between plants and soil microorganisms, our |
|
|
|
|
|
|
|
|
|
|
topic focusses on plant-plant interactions and includes inter-specific competition between different species of similar and different life forms and intra-specific competition. Strategies for securing resources via spatial or temporal separation and different resource needs generally reduce competition. Increasingly important is the effect of invasive plants and subsequent decline in biodiversity and ecosystem function. Current knowledge and future climate predictions suggest that in some situations competition will be intensified with occurrence of increased abiotic (e.g. water and nutrient limitations) and biotic stresses (e.g. mass outbreak of insects), but competition might also decrease in situations where plant productivity and survival declines (e.g. habitats with degraded soils). Changing interactions, climate change and biological invasions place new challenges on ecosystems. Understanding processes and mechanisms that underlie the interactions between plants and environmental factors will aid predictions and intervention. There is much need to develop strategies to secure ecosystem services via primary productivity and to prevent the continued loss of biodiversity. This Research Topic provides an up-to-date account of knowledge on plant-plant interactions with a focus on identifying the mechanisms underpinning competitive ability. The Research Topic aims to showcase knowledge that links ecological relevance with physiological processes to better understanding plant and ecosystem function. |
|
|
|
|
|
| |