Intermittency of renewable power

Impact on the grid

Moving clouds and gusty winds make the renewable power unstable over time. Since the share of renewable energy sources (RES) grows in the grid, their random power fluctuations and lack of inertia pose an increasing risk to the grid's overload and destabilization, and worsen the power quality. To mitigate this impact, the grid's transmission capacity is being reinforced in order to balance the power on a high aggregation level, and over long distances by large-scale water pumps or gass turbines. Increasing the share of renewable energy requires ever greater investment in building the grid infrastructure, which increases the price of electricity and is aesthetically damaging to the landscape.

Smoothing of renewable power

A lot of grid investments, transmission losses and landscape could be saved, if the renewable power was stabilized on a low aggregation level in the grid. Its first stage is a lossless smoothing of renewable power on the low aggregation level, or per-RES in case of utitlity-scale RES. Balancing of power between the grid and a storage (ESS) by means of its low-pass filtering may smooth the renewable power almost loss-free. Its disadvantage is that the low-pass filter (LPF) needs a large-capacity, fast ESS for the power filtering which is too expensive, unless the filter is excited by the exact future power singal that has to be filtered. Ultra-short-term predicting (nowcasting) of the renewable power is possible, though not enough accurate to shrink the accumulated energy near to its theoretical minimum. Actually, the smoothing of renewable power is not yet affordable on a commercial basis.
Our first objective was to analyze the ideal power smoothing model IPLPF, exciting the LPF with the exact future PV power signal, in theory eliminating the unnecessary accumulation of energy caused by the LPF's time lag, thus accumulating a minimum of energy by the filter. Based on the measured solar radiation GI(t) over a time span of 1+ year, the ideal PV power smoothing model was numerically simulated and the parameters of LPF have been optimized in order to minimize the accumulated energy. Under such condition, the aggregated specific accumulation rate quantifies the solar intermittency on one side, while the corresponding specific accumulation cost indicates a potential affordability of the lossless PV power smoothing.
Next, a novel SPLPF smoothing method has been designed in order to minimize the accumulated energy by LPF even when its input future power signal is distorted by a prediction error, since this error increases the accumulated energy either way. Given the measured solar data GI(t), the accumulation rate of SPLPF smoothing was aggregated while applying a variable prediction error at the LPF input: With low to medium prediction error, the SPLPF smoothing performs close to the IPLPF model and much better than the LPF excited by the same predicted input signal does. The numeric simulation has confirmed that the SPLPF smoothing is affordable with the predicted PV power signal.

Ramping limit of RES

However low is the energy accumulated by the smoothing of renewable power, its storage is not for free. Smoothing of either local or aggregated renewable power pays-off only with a favourable tariff granted for meeting the prescribed power ramping limits. The goal is to minimize the sum "smoothing costs" plus "costs of other power balancing measures" plus "power losses due to a curtailment regulation of RES" and if possible, to get rid of the RES curtailment. Given the power ramping limit of RES and the measured signal GI(t) and its prediction error, the specific accumulation rate and the specific cost of the real smoothing can be aggregated. The minimum criterion can be eventually iterated by changing the RES power ramping limit, untill this is optimized.