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For small and isolated electric systems, their inability to be tapped into a continental
transmission grid for emergency power, results in reliability and other economies of scale
impacts. Thus, the power systems operate on the premise that the load is uncontrollable
and that system voltage, frequency and stability are primarily maintained through the
real-time control of the generation. Frequency is a necessary parameter for load control
in interconnected systems, as it is considered as a measure of mismatch between demand
and generation. However, in the great majority of islands and isolated areas power
systems that are not extensively interconnected with many generators and loads, will not
maintain frequency with the same degree of accuracy and therefore cause an automatic
load shedding or other control actions such as temporary power outages. This scenario
is more probable during heavy loads periods, when the accuracy of the system is hard to
maintain [20,29].
Whatever the case, effective planning requires a thorough understanding of the
prevailing electricity demand patterns. Thus, for modeling and forecasting purposes the
existing literature has extensively analyzed the main features of demand. Actually,
electricity consumption is subject to great cyclical and seasonal effects (daily and weekly
cycles, holidays), special events, nonlinearity of meteorological variables and possible
nonlinear time dependence, etc [2,18,19,28,30]. However, the specificity of an open
space, where the mobility of people outside and within a country is usually unrestrained,
impedes the inclusion of an accurate variable that captures the daily population pressure
effect. Contrastingly, this indicator can be accurately measured in islands and isolated
territories that control their population transit. For instance, in the case of islands, where
the only means of access and exit are ports and airports, it is expected that for security
reasons there is a thorough control on the daily flow of incoming and outgoing
passengers. Majority of islands have the possibility to assess the daily population’s
weight present in their territory, which is generally characterized by its high fluctuations
and seasonal aspects.
A natural a priori hypothesis is that the daily electricity demand depends on the
population stock, and most likely this dependence is very relevant in isolated territories
where high seasonal fluctuations could easily affect the efficiency of the electrical system
and provoke serious and costly problems. A high level of seasonality is a distinctive
feature of coastal tourist regions, a problem that often characterizes islands too.
Therefore, the possibility of having a daily population indicator will definitely fulfils the
need of an accurate forecasting model that can predict future electricity demand, and
provide the utility company with a model that reduces the gap between supply and
demand and its concomitant cost.
This article reports on the design and implementation of a medium-run forecasting
model for daily system loads and an evaluation of the forecast performance of the
Balearic Islands (Spain). An archipelago located in the western Mediterranean Sea that
includes four inhabited islands Majorca, Minorca, Ibiza, and Formentera. The last two
form what is known as the Pitiüses, a special unity in terms of electricity system. The
Balearic Islands system supplies electricity annually to 1 million residents and 13 million
tourists concentrated during summer months. The Balearic Islands are taken as a case
study because of their geographical characteristics and relative importance of tourism in
the region. M.BakhatandJ.RosselloNadal / ImprovingDailyElectricityLoadsForecasting 67
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Titel
- Intelligent Environments 2019
- Untertitel
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Autoren
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-Cía
- Verlag
- IOS Press BV
- Datum
- 2019
- Sprache
- deutsch
- Lizenz
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Abmessungen
- 16.0 x 24.0 cm
- Seiten
- 416
- Kategorie
- Tagungsbände