Tuulivoima; kehitys, investoinnit ja työllisyys Suomessa

Tuulivoimalla on pitkä historia. Tuulivoima soveltuu nykyajan energiantuotantoon. Suunniteltaessa ja rakennettaessa uusia tuulivoimaloita on tunnettava tuulisuuteen vaikuttavat tekijät samoin kuin tuulivoimalan sijoituspaikalla on tehtävä perusteelliset tuu-liolosuhdemittaukset. Nykyisellä sähkön hinnalla tuulivoimalat eivät ole täysin kilpailukykyisiä, joten niitä on tuettava. Tukimuotoja on monia. Suomessa pääasiallinen tukimuoto on syöttötariffi. Vallitseva politiikka on ratkaisevassa asemassa luotaessa tukijärjestelmiä tuulivoimalle. Suomessa tehtävät tuulivoimainvestoinnit ovat kasvussa. Tuulivoimaan liittyy niin hyviä kuin huonoja puolia. Huonot puolet ovat ratkaistavissa. Päästökaupan kannalta on tuulivoima yksi keino alentaa kasvihuonekaasuja ilmakehässä. Tuulivoiman osuuden kasvattaminen sähköntuotannossa luo työpaikkoja Suomeen ja luo vientimahdollisuuksia ulkomaille. Tuulivoimalla on valoisa tulevaisuus.

Real-Time Simulation of Real-Time Pricing Demand Response to Meet Wind Variations

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer’ loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

Using reanalysis data to quantify extreme wind power generation statistics : a 33 year case study in Great Britain

With a rapidly increasing fraction of electricity generation being sourced from wind, extreme wind power generation events such as prolonged periods of low (or high) generation and ramps in generation, are a growing concern for the efficient and secure operation of national power systems. As extreme events occur infrequently, long and reliable meteorological records are required to accurately estimate their characteristics. Recent publications have begun to investigate the use of global meteorological “reanalysis” data sets for power system applications, many of which focus on long-term average statistics such as monthly-mean generation. Here we demonstrate that reanalysis data can also be used to estimate the frequency of relatively short-lived extreme events (including ramping on sub-daily time scales). Verification against 328 surface observation stations across the United Kingdom suggests that near-surface wind variability over spatiotemporal scales greater than around 300 km and 6 h can be faithfully reproduced using reanalysis, with no need for costly dynamical downscaling. A case study is presented in which a state-of-the-art, 33 year reanalysis data set (MERRA, from NASA-GMAO), is used to construct an hourly time series of nationally-aggregated wind power generation in Great Britain (GB), assuming a fixed, modern distribution of wind farms. The resultant generation estimates are highly correlated with recorded data from National Grid in the recent period, both for instantaneous hourly values and for variability over time intervals greater than around 6 h. This 33 year time series is then used to quantify the frequency with which different extreme GB-wide wind power generation events occur, as well as their seasonal and inter-annual variability. Several novel insights into the nature of extreme wind power generation events are described, including (i) that the number of prolonged low or high generation events is well approximated by a Poission-like random process, and (ii) whilst in general there is large seasonal variability, the magnitude of the most extreme ramps is similar in both summer and winter. An up-to-date version of the GB case study data as well as the underlying model are freely available for download from our website: http://www.met.reading.ac.uk/~energymet/data/Cannon2014/.

A real time pricing approach to deal with excessive wind power situations

The introduction of wind power generation in several countries around the world, including in European countries, where energy policy directives have encouraged the use of renewables, led to several changes in market and power systems operation. The intensive integration of these sources has led to situations in which the demand is lower than the available renewable resources. In these situations a part of the available generation is wasted if not used for storage or to supply additional demand. This paper proposes a real time demand response methodology based on changing the electricity price for the consumers expecting an increase in the demand in the periods in which that demand is lower than the available renewable generation. The consumers response to the changes in electricity price is characterized by their price elasticity of demand considered distinct for each consumer type. The proposed methodology is applied to the Portuguese power system, in the context of the Iberian electricity market (MIBEL). The renewable-based producers are considered as special producers, with special tariffs, and so it is important to use the energy available as it will be paid anyway. In this context, consumers are entities actively participating in the operation of the market.

Using demand response to deal with unexpected low wind power generation in the context of smart grid

Demand response is assumed an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed aims the minimization of the operation costs in a smart grid operated by a virtual power player. It is especially useful when actual and day ahead wind forecast differ significantly. When facing lower wind power generation than expected, RTP is used in order to minimize the impacts of such wind availability change. The proposed model application is here illustrated using the scenario of a special wind availability reduction day in the Portuguese power system (8th February 2012).

Virtual Power Player Using Demand Response to Deal with Unexpected Low Wind Power Generation

Demand response is assumed as an essential resource to fully achieve the smart grids operating benefits, namely in the context of competitive markets and of the increasing use of renewable-based energy sources. Some advantages of Demand Response (DR) programs and of smart grids can only be achieved through the implementation of Real Time Pricing (RTP). The integration of the expected increasing amounts of distributed energy resources, as well as new players, requires new approaches for the changing operation of power systems. The methodology proposed in this paper aims the minimization of the operation costs in a distribution network operated by a virtual power player that manages the available energy resources focusing on hour ahead re-scheduling. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs. Real time pricing is also applied. The proposed model is especially useful when actual and day ahead wind forecast differ significantly. Its application is illustrated in this paper implementing the characteristics of a real resources conditions scenario in a 33 bus distribution network with 32 consumers and 66 distributed generators.

Short-term Wind Forecasting to Support Virtual Power Player Operation

This paper proposes a wind speed forecasting model that contributes to the development and implementation of adequate methodologies for Energy Resource Man-agement in a distribution power network, with intensive use of wind based power generation. The proposed fore-casting methodology aims to support the operation in the scope of the intraday resources scheduling model, name-ly with a time horizon of 10 minutes. A case study using a real database from the meteoro-logical station installed in the GECAD renewable energy lab was used. A new wind speed forecasting model has been implemented and it estimated accuracy was evalu-ated and compared with a previous developed forecast-ing model. Using as input attributes the information of the wind speed concerning the previous 3 hours enables to obtain results with high accuracy for the wind short-term forecasting.

Real Time Pricing Approaches to Deal With Unexpected Wind Power Variations

The use of renewables have been increased I several countries around the world, namely in Europe. The wind power is generally the larger renewable resource with very specific characteristics in what concerns its variability and the inherent impacts in the power systems and electricity markets operation. This paper focuses on the Portuguese context of renewables use, including wind power. The work here presented includes the use of a real time pricing methodology developed by the authors aiming the reduction of electricity consumption in the moments of unexpected low wind power. A more specific example of application of real time pricing is demonstrated for the minimization of the operation costs in a distribution network. When facing lower wind power generation than expected from day ahead forecast, demand response is used in order to minimize the impacts of such wind availability change. In this way, consumers actively participate in regulation up and spinning reserve ancillary services through demand response programs.

Business opportunities in power sector of Ukraine : focus small-scale hydro and wind power sectors

In the last few years, the Ukrainian investment market has constantly shown strong performance and significant growth. This is primarily due to the investment attractiveness of Ukraine. From the perspective of investments in energy sector, Ukraine can be described as a country providing significant number of opportunities to multiply invested funds. But there are numbers of risks which hamper large investments. The work objective was to discover opportunities in small-scale hydropower and wind power sectors of Ukraine and more importantly to prove economic expediency of such investments. Thesis covers major of issues, concerning entering the Ukrainian power market as a foreign investor. It provides basic information about the structure of power market, the state of renewables sector in Ukraine, development of power sector in the regions, functioning of Wholesale Electricity Market, formation of electricity prices, possibilities for implementing joint Implementation mechanism, while the most attention, nevertheless, is concentrated on the opportunities in small-scale hydro and wind power sectors. Theoretical part of the study disclosed that Crimea peninsula has perfect wind conditions and could be a prospective area for wind project development. Investment analysis revealed that project profits will be excellent if green tariff for renewable energy is adopted. By the moment uncertainties about green law adoption bring additional risk to the projects and complicate any investment decision.

Doubly fed induction generator versus direct drive permanent magnet synchronous generator in wind power applications

The objective of this master's thesis is to compare two different generator systems for wind turbines. It is the doubly fed induction generator system with three stage gearbox and the direct drive permanent magnet generator system. The comparison of generator systems is based on annual energy production for a given wind climate. For comparison a 3 MW, 15 rpm wind turbine is used. Modelling of a turbine rotor, gearbox and converters were done. Design of two generators was done and their performance was examined.

Optimal trading of wind power in the short term market

The energy reform, which is happening all over the world, is caused by the common concern of the future of the humankind in our shared planet. In order to keep the effects of the global warming inside of a certain limit, the use of fossil fuels must be reduced. The marginal costs of the renewable sources, RES are quite high, since they are new technology. In order to induce the implementation of RES to the power grid and lower the marginal costs, subsidies were developed in order to make the use of RES more profitable. From the RES perspective the current market is developed to favor conventional generation, which mainly uses fossil fuels. Intermittent generation, like wind power, is penalized in the electricity market since it is intermittent and thus diffi-cult to control. Therefore, the need of regulation and thus the regulation costs to the producer differ, depending on what kind of generation market participant owns. In this thesis it is studied if there is a way for market participant, who has wind power to use the special characteristics of electricity market Nord Pool and thus reach the gap between conventional generation and the intermittent generation only by placing bids to the market. Thus, an optimal bid is introduced, which purpose is to minimize the regulation costs and thus lower the marginal costs of wind power. In order to make real life simulations in Nord Pool, a wind power forecast model was created. The simulations were done in years 2009 and 2010 by using a real wind power data provided by Hyötytuuli, market data from Nord Pool and wind forecast data provided by Finnish Meteorological Institute. The optimal bid needs probability intervals and therefore the methodology to create probability distributions is introduced in this thesis. In the end of the thesis it is shown that the optimal bidding improves the position of wind power producer in the electricity market.

Energetic exploitation from a hybrid PV-wind power micro-generation rural electrification

Hybrid system micro-generation integration of PV-wind power is presented by a form of energy in which problems resulting from variability in the intensity of wind and solar intensity are possible mitigation either by complementation between one source to another or the largest stability configured by the generate the system. Based on this context, this work aims to assessing the performance of a hybrid system PV-wind power energy small of a rural property for their electrification. The study has been developed at the Rural Laboratory Powering from Engineering Department of UNESP. In order to present this research, a hybrid system has been installed PV-wind power, composed of one 400Wp windmill and a 300 Wp PV-system. The results obtained allowed us to evaluate the solar and wind energy supplied ranked among 285 and 360 kWh electric power generated by the PV-wind power hybrid system stood between 25,5 and 31 kWh. At is to say achieving yield of approximately than 10% during one year observation period, i.e., it was concluded that the performance of the hybrid system depended essentially the energy received and generated by the PV-system and that there was complementation between generating wind power and PV-systems with regard to time of day and the annual seasons by confirming the technical feasibility of this kind system of micro-generation in small rural properties.

Influence of local wind speed and direction on wind power dynamics - Application to offshore very short-term forecasting

Wind power time series usually show complex dynamics mainly due to non-linearities related to the wind physics and the power transformation process in wind farms. This article provides an approach to the incorporation of observed local variables (wind speed and direction) to model some of these effects by means of statistical models. To this end, a benchmarking between two different families of varying-coefficient models (regime-switching and conditional parametric models) is carried out. The case of the offshore wind farm of Horns Rev in Denmark has been considered. The analysis is focused on one-step ahead forecasting and a time series resolution of 10 min. It has been found that the local wind direction contributes to model some features of the prevailing winds, such as the impact of the wind direction on the wind variability, whereas the non-linearities related to the power transformation process can be introduced by considering the local wind speed. In both cases, conditional parametric models showed a better performance than the one achieved by the regime-switching strategy. The results attained reinforce the idea that each explanatory variable allows the modelling of different underlying effects in the dynamics of wind power time series.

Pre-Feasibility Study of Hybrid Wind Power-H-2 System Connected to Electrical Grid

The growth of wind power as an electric energy source is profitable from an environmental point of view and improves the energetic independence of countries with little fossil fuel resources. However, the wind resource randomness poses a great challenge in the management of electric grids. This study raises the possibility of using hydrogen as a mean to damp the variability of the wind resource. Thus, it is proposed the use of all the energy produced by a typical wind farm for hydrogen generation, that will in turn be used after for suitable generation of electric energy according to the operation rules in a liberalized electric market.