A new performance index for evaluating community virtual power plant with domestic storage

Peukert Effects on Domestic Energy Storage in Virtual Power Plants

“…Both E dis (min,i) and E dis (max,i) values were initially chosen to be 0 and 10 per unit respectively in order to be able to account for Peukert effect. These values were later normalize to 0 and 1 per unit respectively base on the maximum load of the prosumers [10]- [12]. The same also applies to E chg (min,i) and E chg (max,i) .…”

“…However, this could varies. The pricing scheme and the load profile in [10]- [12] was used as the input data in this experiment. Genetic Algorithm was used to optimize F in (16) for N = 3, and T = 24 [10], [11], by setting w 1 = 0.257, w 2 = 0.257, w 3 = 0.229, w 4 = 0.257.…”

“…The effective battery capacity of prosumer i, namely E ef f i , when E dis (i,t) > E rate (i) , can be expressed as follows [11,12]:…”

“…Earlier studies have shown the benefits of energy storage under VPP operation to the VPP stakeholders in terms of providing the grid with its required load shape during DSM, as well as cost minimization and profit maximization for the prosumers, VPP aggregators and grid operators [10]- [12]. However, there is no clarity on how the Peukert condition of battery storage can affect the benefits of the VPP stakeholders.…”