Automated Dispatch Logic The control logic then signals the battery bank to set its state to “charge” or “dispatch” for each hour to ensure that electricity is drawn from the grid during low emissions intensity hours and fed back into the grid during high intensity hours, as far as possible. Figure 4 graphically represents this dispatch sequence for the 2020 and 2030 scenarios. An automated dispatch sequence configured this way is employed to parametrically study GHG avoidance from different PV and battery system capacity combinations, for different demand and emission profiles. While the objective for this study was to minimize GHG emissions, the control sequence can as easily be adapted to minimize peak demand or time-of-use energy costs.
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Figure 4: Graphical representation of deployed dispatch sequence design to set the battery to ‘charge’ state during periods of low grid emissions intensity and to ‘dispatch’ state when the grid is dirtier. For 2020 [Top] and 2030 [Bottom] scenarios.
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Maximizing Avoided Emissions
To be able to quantify the magnitude of GHG emissions that can be potentially avoided by load shifting, we developed an automated dispatch logic that tracks and forecasts building electricity demand, renewable generation potential, and grid marginal emissions on an hourly basis for up to 7 days at a time.
