Load Matching and Grid Interaction of Net Zero Energy Buildings

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monthly daily hourly% load, 79% grid, 37%100% load, 77% grid, 25%100% load, 36% grid, 31%100505050000-50-50-50-100Jan DecSolar XXI, Portugal-100Jan Dec-100Jan Dec% load, 87% grid, 55%100% load, 81% grid, 29%100% load, 41% grid, 29%100505050000-50-50-50-100Jan DecOberlin College, USA-100Jan Dec-100Jan Dec% load, 79% grid, 43%100% load, 76% grid, 35%100% load, 36% grid, 25%100505050000-50-50-50-100Jan DecSolar Decathlon, Germany-100Jan Dec-100Jan DecFig. 5: Load match (f load ) and grid interaction indices (f grid , refer 4.2) for all projects addressed in figure 3. Dataare given in monthly, daily and hourly resolution together with the annual average for the load index as well asstandard deviation for the grid interaction index.4. Grid Interaction4.1. BackgroundFeeding electricity from on-site generation into utility grids is part of the strategy to increase the gridsoverall system efficiency and the share of power from renewables. On the other hand large scaledistributed generation may generate problems with power stability and quality in today´s gridstructures, mainly on the local distribution grid level. Developments to so-called “smart grids” areongoing to fully benefit from distributed generation with respect to the grids primary energy andcarbon emission factor as well as the costs. Time-dependent electricity costs (supply) and prices (feedin)may communicate the needs of the grid to the consumer (the building owner), thereby leadingtowards improved sizing of the building energy system and DSM as well as integrating appropriate on-
site storage options. Within a least-cost planning approach, on-site options have to be compared withmeasures at the grid level, which take advantage of the economy of scale and equalization of localpeaks.4.2. The Grid Interaction IndexWith respect to the fact that the value of exported power is dependent on the local grid performance,the appropriate index from the viewpoint of the building is proposed as grid interaction index insteadof grid match index. Making use of the data already introduced, the grid interaction index is based onthe ratio of the net grid metering over a given period (e.g. monthly) compared to themaximum/minimum within an annual cycle. A positive value describes a net exporting building. Thegrid interaction index describes the average grid stress using the standard deviation of the gridinteraction over the period of a year:fgrid, igrid, yearnet grid= ⋅100[%]i = time interval, (4)max net grid( f )f = STD(5)grid,iThe index describes the fluctuation of the energy exchange of the building with the grid, not theamount of grid electricity needed. An almost constant import (or export) instead of high fluctuations ischaracterised by a low value of the annual f grid . Figure 5 includes the grid interaction index in theresolution of months, days and hours for the projects already addressed together with the annualstandard deviation. Fig. 6 and 7 summarize the results for the annual indices based on differentresolutions. The Solar XXI project profits from the even solar yield during the year although not fullymatching the annual energy needs.10075load match index in %Solar XXIOberlin CollegeSolar Decathlon10075grid interaction indexSolar XXI Oberlin College Solar Decathlon505025250annually monthly daily hourly0annually monthly daily hourlyFig. 6: Comparison of the load match indicesbased on different time resolutions.Fig. 7: Comparison of the grid interaction indices basedon different time resolutions.5. ConclusionsThe investigation consequently addresses the load match and grid interaction issue on the buildinglevel, taking into account energy use and generation on-site. Fuel switching is not yet fully addressedat this stage of work. The investigation focuses on electricity, as the major energy exchanged with agrid in both directions. This includes plug loads and appliances as part of the total load and excludesoff-site power generation. With respect to data availability and the suitability for a future spread sheetcalculation tool and national building code applications a monthly resolution seems to the appropriate
Page 4 and 5: monthly data in sequence cumulative
Page 8: level to characterise the major dif

Load Matching and Grid Interaction of Net Zero Energy Buildings

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