A Method for Sizing Centralised Energy Storage Systems Using Standard Patterns

Abstract

Low Voltage (LV) distribution networks with high penetration levels of photovoltaics have to tackle various challenges such as overvoltages, voltage fluctuations, reverse power flows, and non-coincident demand and local generation. Energy Storage Systems (ESS) can help to ease these issues, if sized properly. This paper proposes a two-step methodology for sizing centralised ESS in LV networks. In the first step, a reoccurring daily pattern is detected using symbolic aggregated approximation (SAX) from the data measured at a German grid. Afterwards, high-and low-frequency components of the power signal are separated using a low-pass filter and then used for sizing different types of ESS. The effect of data resolution on the sizing outcomes is also investigated. The performance of the method was investigated using the full data set. It is concluded that ESS with the characteristics derived using this methodology can effectively be used for peak shaving, power smoothing and load balancing.

Sizing of Hybrid Energy Storage Systems Using Recurring Daily Patterns

“…In [20], we have introduced a novel alternative for finding a representative power profile within the time series, where recurring daily consumption patterns are detected using a pattern recognition algorithm called motif discovery [21], and then used as input for the sizing study. Motif discovery has several advantages in comparison to the state-of-the-art clustering techniques.…”

“…Lastly, motif discovery does not need the additional step of finding optimal cluster parameters. In this paper, we extend the method presented in [20] in the following ways:…”

“…The core innovation in Motif Discovery, in general, is the transformation of a time series into symbols, which reduces the noise and minor variations in the raw time series through approximations. Additionally, eSAX improves the previous Motif Discovery algorithm used in [20] by using a different distance measure and more flexible words.…”

“…with w k defined as the k-th element of the warping path w. In contrast to Euclidean distances used in [20], this distance measure can also accommodate slight shifts in between two time series, such as slight time shifts in the peak demand in this use case. At the end of this fourth step, we are left with motifs containing several sequences.…”

DSO Strategies Proposal for the LV Grid of the Future

“…The second solution is decentralised and consists in using power conversion systems with energy storage systems at the consumer (prosumers) [16][17][18][19][20]. The use of dispersed ESS systems depends on the times of response to the service of the ESS user [21] and/or the availability of the ESS systems at the given adjustment moment [22]. At the given moment, each ESS features different parameters: Capacity, power, ramp, rate, cycle time [23].…”