Stochastic optimisation with risk aversion for virtual power plant operations: a rolling horizon control

Descriptive statistical approach for the assessment of the output of a virtual power plant in a secondary distribution network

“…Hence, most of the load variations after normalisation (BRZ) ranges between ±2S. This normalised range is divided into seven clusters in this work and form the behavioural response cluster (BRC) as given in (8). It should be noted that the load variations of all the customers in a secondary distribution transformer are within a specified limited range and hence z-score normalisation shall not eliminate any significant behavioural patterns of the customers.…”

“…The BRZs obtained are then employed to obtain BRCs using (8). The ranges for each of the BRC defined in (8), groups the customers into seven clusters: EH-extremely high, VH-very high, H-high, M-medium, L-low, VL-very low and EL-extremely low. The BRZ range of each BRC is chosen based on the standard normal distribution curve of the z-score values (Fig.…”

“…The customer's load in kW is available for classification and the customers BRZ score is calculated using (2)-(7). The customers are categorised into different clusters based on their BRZ, using (8). The cluster to which the consumption of a customer for the ith interval of a season or a 'specific day of the week' in the season is obtained from (9).…”

“…The profiling of customers during the specified time-intervals for the years 2014 and 2015 is employed to predict the 'future' load X i, k j, (Y r + 1) of any customer k at the same time-interval i on a particular day of a season for the year 2016. The hourly profiling of the customers from the available historical data (previous two years 2014, 2015) has been carried out by adopting the (1)- (8). Consequent to the profiling, (10)-(13) are adopted to predict the customer's load/generation on a specific time-interval, i, of the day.…”

“…The net behaviour of the combination of generation and loads in a specific location is increasingly construed as a virtual power plant (VPP) [5,6]. An appropriate interactive and coordinated approach makes the VPP an equivalent conventional power plant while providing greater flexibility to the prosumers [7][8][9][10]. The earlier works on VPP operation have considered generation side dispatches, energy storage and demand response (DR) [6,[11][12][13][14][15] only.…”