Comparative analysis of tertiary control systems for smart grids using the Flex Street model

Various smart grid control systems have been developed with different architectures. Comparison helps developers identify their strong and weak points. A three-step analysis method is proposed to facilitate the comparison of independently developed control systems. In the first step, a microgrid model is created describing demand and supply patterns of controllable and non-controllable devices (Flex Street). In the second step, a version of Flex Street is used to design a case, with a given control objective and key performance indicators. In the last step, simulations of different control systems are performed and their results are analysed and compared. The Flex Street model describes a diverse set of households based on realistic data. Furthermore, its bottom-up modelling approach makes it a flexible tool for designing cases. Currently, three cases with peak-shaving objectives are developed based on scenarios of the Dutch residential sector, specifying various penetration rates of renewable and controllable devices. The proposed method is demonstrated by comparing IntelliGator and TRIANA, two independently developed control systems, on peak reduction, energy efficiency, savings and abated emissions. Results show that IntelliGator---a real-time approach---is proficient in reducing peak demand, while TRIANA---a planning approach---also levels intermediate demand. Both systems yield benefits (\geneuro5--54 per household per year) through reduced transport losses and network investments in the distribution network

Greenhouse gas emission curves for advanced biofuel supply chains

Most climate change mitigation scenarios that are consistent with the 1.5–2 °C target rely on a large-scale contribution from biomass, including advanced (second-generation) biofuels. However, land-based biofuel production has been associated with substantial land-use change emissions. Previous studies show a wide range of emission factors, often hiding the influence of spatial heterogeneity. Here we introduce a spatially explicit method for assessing the supply of advanced biofuels at different emission factors and present the results as emission curves. Dedicated crops grown on grasslands, savannahs and abandoned agricultural lands could provide 30 EJBiofuel yr−1 with emission factors less than 40 kg of CO2-equivalent (CO2e) emissions per GJBiofuel (for an 85-year time horizon). This increases to 100 EJBiofuel yr−1 for emission factors less than 60 kgCO2e GJBiofuel −1. While these results are uncertain and depend on model assumptions (including time horizon, spatial resolution, technology assumptions and so on), emission curves improve our understanding of the relationship between biofuel supply and its potential contribution to climate change mitigation while accounting for spatial heterogeneity

Conservation of birds in fragmented landscapes requires protected areas

For successful conservation of biodiversity, it is vital to know whether protected areas in increasingly fragmented landscapes effectively safeguard species. However, how large habitat fragments must be, and what level of protection is required to sustain species, remains poorly known. We compiled a global dataset on almost 2000 bird species in 741 forest fragments varying in size and protection status, and show that protection is associated with higher bird occurrence, especially for threatened species. Protection becomes increasingly effective with increasing size of forest fragments. For forest fragments >50 ha our results show that strict protection (International Union for Conservation of Nature [IUCN] categories I–IV) is strongly associated with higher bird occurrence, whereas fragments had to be at least 175 ha for moderate protection (IUCN categories V and VI) to have a positive effect. This meta-analysis quantifies the importance of fragment size, protection status, and their interaction for the conservation of bird species communities, and stresses that protection should not be limited to large pristine areas

The Global Forest Transition as a Human Affair

Peer reviewe

Chasing the Clouds: Irradiance Variability and Forecasting for Photovoltaics

The stochastic part of the variability of irradiance is captured through the variability of the clear-sky index. If variability is correlated for close locations, the aggregated PV-output will be relatively high compared to aggregate PV-output of locations that are far apart (and more likely to be de-correlated). Aggregate fluctuations of PV power output will eventually be added up at a local LV substation in the case of a residential neighborhood, or MV network when large PV-plants are concerned. Successful integration of high-levels of PV capacity depends on the correct evaluation of the expected correlate peaking highs and lows. Short-term forecasting deals with the question “what if the aggregation does not reduce variability enough?'': knowing what peak or low will come in the electricity network can help to prepare for this by e.g. planning the smart charging of electric vehicles or short-term spinning reserves, respectively in a smart grid. In general, daily correlation of PV-system pairs is retained longer at increasing temporal resolution from 0.5 km for 5 s data to 3--6 km for 10 min. averaged data, depending strongly on the pattern of clouds (variability). Measured over sub-day periods and specified to azimuthal directions, lagged temporal correlation downwind is retained over much longer distances than in the direction perpendicular to the cloud motion. A trade-off exists between building and maintaining a high-resolution pyranometer sensor-network at this (province) scale and the quality of the derived GHI data of using existing PV-systems as we have done. The principle of using a network of sensors for short-term forecasting is an extension to existing methods, and the application on real-world PV-systems was worthwhile to investigate. The P2P method showed to be useful especially on days with variable irradiance with clear, quasi-statically moving clouds for which the shortest distances retain aggregate variability the most strongly and thus can benefit from short-term detailed forecasting if supply and demand are to be coupled in a future smart grid. The relative Root Mean Square Error of the P2P forecasting method in the studied validation period is in the order of 50%, but performs 6-9% better than naive clear-sky index persistence on the shortest forecast horizon of 5 to 8 min. at 1 min. data resolution, depending on the method of cloud motion detection. The presented technique to infer the direction of motion of the clouds within the sensor-network itself, that would otherwise rely on cloud camera, satellite- or meteorological data, is an essential addition to using the PV-sensor network. The PV-sensor network is, in principle a great tool to have high-resolution measurement data over a large geographic area at relatively low effort of connecting and measuring these existing PV-systems instead of developing an irradiance sensor network from scratch. Using the Inverse PV model (with RMSE of 15.1%), the measured power-output was translated into GHI and hence clear-sky index such that measurement results become independent of PV-system meta data (tilt, orientation, rated power)

Saamaka zeggenschap in besluiten over landgebruik

Dit document is het resultaat van een participatief onderzoek dat tussen 2013 en 2016 is uitgevoerd door Tropenbos Suriname en de Saamaka gemeenschappen in het Boven Suriname gebied. De uitvoering van het project werd ondersteund door de Vereniging van Saamaka Gezagsdragers (VSG). De projectdoelstellingen waren: 1) Kennis en kaarten produceren over de ecosysteemdiensten die belangrijk zijn voor de Saamaka gemeenschappen. 2) Begrijpen hoe een proces van participatieve kartering gebruikt kan worden om inclusief beleid te ondersteunen dat de behoeften en prioriteiten van de Saamaka gemeenschappen met betrekking tot het gebruik van ecosysteemdiensten erkent

Saamaka voices in land use decisions

This document is the result of a participatory research carried out, between 2013 and 2016, by Tropenbos Suriname and the Saamaka communities living in the Upper Suriname River region. It is embedded in a joint project with the Association of Saamaka Authorities (VSG) and WWF. The project objective was twofold: 1) to provide a spatial explicit understanding on the ecosystem services that are important for the Saamaka communities as well as assess their current state in their provision and threats, and 2) to understand how the local knowledge of Saamaka communities can be used to support a process of inclusive policy making that recognizes the needs and priorities of Saamaka communities regarding ecosystem service use

Taki u saamaka sëmbë a di fasi fa wooko o seeka a di matu

Di öndösuku di bi du ka Tropen Suriname bi wooko makandi ku dee Saamaka sëmbë u Libasë Saana lio, a di 2013 te go miti 2016, hën tja di sikifi u di pampia aki. Di Feleniki u dee Takima u Saamaka de kai VSG bi taanpu a di öndösuku aki baka. De hopo di wooko aki u 2 soni hedi: 1) U kisi sabi ku u mbei kaita u dee gudu u di matu dee dë fanöudu da dee Saamaka sëmbë. 2) U fusutan unfa wooko makandi u mbei kaita sa heepi dee Saamaka sëmbë u de sa feni taki a di fasi fa wooko o seeka a di matu, u sölugu taa te wëti o mbei nöö dee soni dee dë fanöudu da dee Saamaka sëmbë musu dë a pakisei