A kelly criterion based optimal scheduling of a microgrid on a steam-assisted gravity drainage (SAGD) facility

Abstract

Steam Assisted Gravity Drainage (SAGD) is one of the major thermal recovery techniques to extract the Canadian bitumen. In the process, there is substantial amount of heat left behind in the reservoir at the end of SAGD operations, which can be converted to electricity and distributed profitably utilizing a microgrid. Concurrently, based on Canada’s green energy initiative, we present the integration and optimal power management of a microgrid on a SAGD facility, comprising of an Organic Rankine Cycle based turbine (ORC), a Gas Turbine (GT), a Battery Storage System (BSS), the central grid and the SAGD facility as the load. We introduce a Kelly Criterion (KC) based microgrid scheduling technique, which is based on maximizing information gain and is independent of supply-demand relationships. Based on the formulation, it was hypothesized that the KC based algorithm is superior compared to standard optimization techniques in a highly volatile electricity market. The electricity market volatility is captured via a wavelet network based forecasting technique. The case study presented highlights the advantages of the KC approach and its efficacy in a highly volatile energy market. The results show the superiority of the KC based scheduling algorithm in highly volatile energy markets, with forecast data irregularities.