Assessment of large scale wind power generation with new generation locations without measurement data

Abstract

a b s t r a c tLarge amounts of new wind power are currently under construction or planning in many countries. The constantly increasing percentage of wind power in the electricity generation mix has to be taken into consideration when planning power systems. This paper introduces a Monte Carlo simulation based methodology that can be used to assess the effects (e.g. need for new transmission lines, reserves, wind curtailment or demand side management) of large amounts of existing and planned wind power generation on the power system. The presented methodology is able to assess new wind power scenarios spread over a wide geographical area, comprising numerous existing and planned wind generation locations. The Monte Carlo simulation results are verified against measured aggregated wind power generation in Finland from 2008 to 2014. In addition, case studies of future scenarios with 232 individual wind generation locations are presented to show the applicability of the methodology as a tool in power system planning.

Sizing Hydrogen Energy Storage in Consideration of Demand Response in Highly Renewable Generation Power Systems

“…Wind power generation can be modelled utilizing a statistical methodology developed for modelling wind power generation scenarios with new generation locations without any measurement data. The methodology is presented in detail in Ekström et al [17]. On the other hand, the required PV generation can be modelled with a statistical methodology designed for the simulation of new PV generation scenarios, as presented in Ekström et al [18].…”

“…This approach combines the simulation methodologies presented for wind and PV generation in studies by Ekström et al in 2015 and2016 [17,18] and as shown in a paper by Ekström et al in 2017 [19]. The methodology was designed for long-term simulation studies of new intermittent renewable generation scenarios using Monte Carlo simulations and produces both synthetic wind and PV generation time series.…”

Assessing the Potential Benefits and Limits of Electric Storage Heaters for Wind Curtailment Mitigation: A Finnish Case Study

“…In this paper, time series of wind generation with varying levels of penetration in the system are obtained using a well-known statistical approach as utilized in previous works [18,19]. This is centered on a statistical method combining probability integral transformations and time-series modeling, thereby simulating wind speed discrete-time data for a new group of wind turbines.…”

“…In the next step, using a wind speed time series and a wind turbines model (specifications differ for each turbine type and wind farm), a wind generation time series is simulated. This wind generation model is modified from work in [18] as it accounts the real wind power installation scenarios in Finland until the beginning of 2016. The 2016 generation structure is used as a base for the simulated scenarios which consists of an aggregate of 1008 MW of generation capacity with 377 individually modeled wind turbines with real world specifications (turbine technical information including e.g., power curve parameters and nominal power).…”

A Statistical Model for Hourly Large-Scale Wind and Photovoltaic Generation in New Locations

“…The methodologies to model PV and wind power generation and variability separately in new generation locations without actual measurement data, i.e. in non-measured locations, have been presented in [10], [11]. The modelling of power systems with both PV and wind power is a current topic, and is being actively researched and published, [12]- [15].…”