As this problem includes complex physical laws of gas flow, standard optimization solvers cannot guarantee convergence to a feasible solution. To address this issue, we develop an input-convex neural network (ICNN) aided optimization routine which incorporates a set of trained ICNNs approximating the gas flow equations with high precision. Numerical tests on the Belgium gas network demonstrate that the ICNN-aided optimization dominates non-convex and relaxation-based solvers, with larger optimality gains pertaining to stricter emission targets. Moreover, whenever the non-convex solver fails, the ICNN-aided optimization provides a feasible solution to network planning.

Australia will need to double the pace of its renewable energy uptake to meet the 2030 emissions target set by the Albanese government, even without any increase in demand, according to Bruce Mountain, head of the Victoria Energy Policy Centre. Labor's main energy policy, Rewiring the Nation, includes the creation of a special corporation to funnel $20bn into new transmission links to accelerate the uptake of more clean energy. The plan is part of Labor's pledge to cut Australia's 2005-level greenhouse gas emissions 43% by 2030, projecting renewables reach an 82% share of renewables in the National Electricity Market by then. Excluding hydro power, renewable energy has increased its share of the market 3% annually in the past five years, Mountain says. "Deducting 10% from hydro, the target is 72%," he says of Labor's goal.