Risk-aware two-stage stochastic programming for electricity procurement of a large consumer with storage system and demand response

In this paper, a two-stage stochastic model is put forward for electricity procurement in large consumers (LCs) with storage system, photovoltaic, wind and geothermal units, slow demand response (SDR) and fast demand response (FDR), bilateral contracts and pool market. The model considers the uncertainties of pool market prices, demands, wind and photovoltaic power. Conditional-value-at-risk (CVaR) as a risk metric is used to take the variability of procurement cost into account. Major findings indicate that SDR and FDR collectively decrease the expected procurement cost by 9.4% and CVaR by 10.5% and also show that FDR is more efficient than SDR in decreasing the electricity procurement cost and its associated risk. The superiority of FDR over SDR is attributed to its flexibility which enables it to adjust its shift-ups and shift-downs according to the occurred scenario. The results imply that demand response programs and in particular, FDR decrease the purchased electricity from pool market. According to the results, the increase in confidence level increases CVaR, but does not significantly change the expected procurement cost. The results also show that at low weight factors, the increase in weight factor increases expected procurement cost and decreases CVaR, but at weight factors beyond 8, the increase in weight factor changes neither expected procurement cost nor CVaR.