Implementation and applications of chaotic oscillatory based neural network for wind prediction problems

Author name used in this publication: J. N. K. LIU2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Wind Power Forecasting Methods Based on Deep Learning: A Survey

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power grid. Aiming to provide reference strategies for relevant researchers as well as practical applications, this paper attempts to provide the literature investigation and methods analysis of deep learning, enforcement learning and transfer learning in wind speed and wind power forecasting modeling. Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure, temperature, roughness, and obstacles. As an effective method of high-dimensional feature extraction, deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design, such as adding noise to outputs, evolutionary learning used to optimize hidden layer weights, optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for forecasting. The establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness, instantaneity and seasonal characteristics

Towards the prediction of renewable energy unbalance in smart grids

The production of renewable energy is increasing worldwide. To integrate renewable sources in electrical smart grids able to adapt to changes in power usage in heterogeneous local zones, it is necessary to accurately predict the power production that can be achieved from renewable energy sources. By using such predictions, it is possible to plan the power production from non-renewable energy plants to properly allocate the produced power and compensate possible unbalances. In particular, it is important to predict the unbalance between the power produced and the actual power intake at a local level (zones). In this paper, we propose a novel method for predicting the sign of the unbalance between the power produced by renewable sources and the power intake at the local level, considering zones composed of multiple power plants and with heterogeneous characteristics. The method uses a set of historical features and is based on Computational Intelligence techniques able to learn the relationship between historical data and the power unbalance in heterogeneous geographical regions. As a case study, we evaluated the proposed method using data collected by a player in the energy market over a period of seven months. In this preliminary study, we evaluated different configurations of the proposed method, achieving results considered as satisfactory by a player in the energy market

Improving meteorological information to air transport

Meteorological information and services supporting the various operations of air transport enable a safe, efficient and cost-effective operating environment for airspace users, air navigation service providers and air traffic management. The continuing pursuit towards an improved quality of observation, forecasting and decision support services is driven by an increasingly weather-sensitive society and growing impacts of hazardous weather events. This thesis provides an overview of the field of aeronautical meteorological research by introducing the organisations involved, global and regional strategies, impacts of weather on air transport, current state of the art in meteorological research and decision support systems serving air transport needs with a view of where the field should evolve next. This thesis is an attempt to highlight key findings and point the reader towards the direction of further research on the given topics. Research supporting air transport operations with the optimal use of weather information is a specialized field where advances are led by the needs of various airspace users. Research institutions for example in the United States have contributed greatly due to the severe weather impacts experienced by the National Airspace System (NAS), the ability of the Federal Aviation Administration (FAA) and the National Oceanic and Atmospheric Administration (NOAA) to direct long-term funding to solve specific aviation-related research questions. The creation and maintenance of long-lived teams of scientists and engineers working together to produce end-to-end solutions that meet the needs of the aviation industry is the key to improving meteorological information to aviation users while university research is typically shorter duration and typical does not result in operational systems. From a global perspective, research is yet to be organised in a way that would contribute to solving aviation issues beyond single research projects and/or programmes. There is a lot more the scientific community could do to develop tailored information to decision support systems used by the aviation sector, but it would require systematic investments and the establishment of research groups focusing on the applied science questions and technology transfer. This thesis provides an overview of recommended decision support system development topics with an outline of potential milestones.Tieto ilmakehän nykyisestä ja tulevasta tilasta sekä tätä tietoa ilmailun tarpeisiin tuottavat palvelut mahdollistavat turvallisen, toimivan sekä kustannustehokkaan toimintaympäristön ilmatilan käyttäjille, ilmailun palveluiden tuottajille sekä ilmatilan hallintaa toteuttaville tahoille. Vaarallisille sääilmiöille herkemmäksi kehittyvä yhteiskunta vaatii havaintojen, ennusteiden sekä päätöksenteon tukijärjestelmien jatkuvaa kehittämistä asiakkaiden tarpeisiin. Tämä lisensiaatintutkielma tarjoaa maailmanlaajuisen yleiskatsauksen ilmailun sääpalveluiden tutkimukseen ja tuotekehitykseen pyrkimyksenään esitellä keskeiset toimijat, alueelliset ja kansalliset kehittämisohjelmat ja strategiat, sään vaikutukset ilmailulle, ilmailun sääpalveluiden nykytila sekä tulevaisuuden toimintaympäristön edellyttämät uudet lentosääpalvelut. Tavoitteena on korostaa ilmailun kannalta tärkeimpiä meteorologisia kehityskohteita ja ohjata lukija jo tehdyn tutkimuksen pariin. Ilmailun toimintoja tukevien sääpalveluiden kehittämiseen tähtäävä tutkimus on hyvin soveltava erikoisala, missä asiakkaiden tarpeet määrittävät tutkimuskohteet. Kehitys on keskittynyt voimakkaasti Yhdysvaltoihin, mihin on syynä kapasiteetin äärirajoilla toimiva ilmatila sekä kyky rahoittaa pitkäkestoisia meteorologisia tutkimushankkeita ilmailun tarpeisiin. Meteorologian tutkijoiden ja insinöörien pitkäkestoinen yhteistyö tuottaa koko arvoketjun kattavia projekteja, joiden lopputuloksena syntyy asiakkaan tarpeisiin räätälöityjä palveluita hyödyntäen yliopistoissa tehtävää tutkimusta sekä tietoteknisten ratkaisujen kehittymistä. Maailmanlaajuisesti katsottuna ilmailun sääpalveluiden tutkimusta ja tuotekehitystä ei ole toistaiseksi järjestetty yhtenäisen strategian tai tavoitteiden alle. Tieteellinen yhteisö pystyisi kasvattamaan merkittävästi panostaan ilmailun turvallisuuden kehittämiseksi, mikäli tuotekehityksen rahoitus organisoitaisiin paremmin ja osaaminen keskitettäisiin soveltavan tutkimuksen ryhmiin. Tämä tutkielma sisältää suosituksia päätöksenteon tukijärjestelmiin integroitavista sääpalveluista, joiden avulla säätilan vaikutus lentotoiminnalle voidaan viedä suoraan päätöksentekotasolle. Tutkielmassa esitettyjen projektiaihioiden tarkoituksena esittää konkreettisia toimenpiteitä, joilla varmistutaan tutkimuksen soveltuvuudesta loppukäyttäjien toimintaan

Improving meteorological information to air transport

Meteorological information and services supporting the various operations of air transport enable a safe, efficient and cost-effective operating environment for airspace users, air navigation service providers and air traffic management. The continuing pursuit towards an improved quality of observation, forecasting and decision support services is driven by an increasingly weather-sensitive society and growing impacts of hazardous weather events. This thesis provides an overview of the field of aeronautical meteorological research by introducing the organisations involved, global and regional strategies, impacts of weather on air transport, current state of the art in meteorological research and decision support systems serving air transport needs with a view of where the field should evolve next. This thesis is an attempt to highlight key findings and point the reader towards the direction of further research on the given topics. Research supporting air transport operations with the optimal use of weather information is a specialized field where advances are led by the needs of various airspace users. Research institutions for example in the United States have contributed greatly due to the severe weather impacts experienced by the National Airspace System (NAS), the ability of the Federal Aviation Administration (FAA) and the National Oceanic and Atmospheric Administration (NOAA) to direct long-term funding to solve specific aviation-related research questions. The creation and maintenance of long-lived teams of scientists and engineers working together to produce end-to-end solutions that meet the needs of the aviation industry is the key to improving meteorological information to aviation users while university research is typically shorter duration and typical does not result in operational systems. From a global perspective, research is yet to be organised in a way that would contribute to solving aviation issues beyond single research projects and/or programmes. There is a lot more the scientific community could do to develop tailored information to decision support systems used by the aviation sector, but it would require systematic investments and the establishment of research groups focusing on the applied science questions and technology transfer. This thesis provides an overview of recommended decision support system development topics with an outline of potential milestones

A decision support system for wind power production

Renewable energy production is constantly growing worldwide, and some countries produce a relevant percentage of their daily electricity consumption through wind energy. Therefore, decision support systems that can make accurate predictions of wind-based power production are of paramount importance for the traders operating in the energy market and for the managers in charge of planning the nonrenewable energy production. In this paper, we present a decision support system that can predict electric power production, estimate a variability index for the prediction, and analyze the wind farm (WF) production characteristics. The main contribution of this paper is a novel system for long-term electric power prediction based solely on the weather forecasts; thus, it is suitable for the WFs that cannot collect or manage the real-time data acquired by the sensors. Our system is based on neural networks and on novel techniques for calibrating and thresholding the weather forecasts based on the distinctive characteristics of the WF orography. We tuned and evaluated the proposed system using the data collected from two WFs over a two-year period and achieved satisfactory results. We studied different feature sets, training strategies, and system configurations before implementing this system for a player in the energy market. This company evaluated the power production prediction performance and the impact of our system at ten different WFs under real-world conditions and achieved a significant improvement with respect to their previous approach

Aeronautical engineering: A cumulative index to a continuing bibliography (supplement 274)

This publication is a cumulative index to the abstracts contained in supplements 262 through 273 of Aeronautical Engineering: A Continuing Bibliography. The bibliographic series is compiled through the cooperative efforts of the American Institute of Aeronautics and Astronautics (AIAA) and the National Aeronautics and Space Administration (NASA). Seven indexes are included: subject, personal author, corporate source, foreign technology, contract number, report number, and accession number