Download Category: Power Grids

Power grids move electrical energy from power producers to consumers. Total capex averaged $280bn pa in 2015-20, of which one-third was transmission, two-thirds distribution. But the capex needed for global power networks likely rises by 4x in the energy transition to over $1trn pa in the 2040s. Our power grid research looks for opportunities.

Power quality matters for electrification. And it presents an increasing challenge, as utility-scale wind and solar are inherently situated far from consumers, while they may also have high power volatility and low power quality (e.g., low inertia, reactive power). These shortcomings can all be compensated synthetically via power electronics.

In addition, power grids can be made more efficient. This includes technologies such as VAR-optimization, which keep power factors near unity, and avoid wasteful power losses. The average power grid is 93% efficient from generation source to consumer. Opportunities to improve stretch deep into the weeds of power-electronic capital goods.

Overall, 40% of the upside in our power grid models comes from ramping renewables, 35% is demand growth linked to economic progress, 15% is ramping EVs, 10% is grid-scale batteries. We have constructive outlooks on different components, from long-distance HVDCs through to small-scale components such as variable frequency drives and power-MOSFETs.

Desalination by reverse osmosis: the economics?

Costs and economics of desalination via reverse osmosis

35bn tons of desalinated water are produced each year, absorbing 250 TWH of energy, or 0.4% of total global energy consumption.

These numbers have already doubled since 2005 and could rise sharply in the future: water use per capita remains 50-90% lower in the emerging world than in the United States, populations are growing and aquifers depleting.

Hence, this model quantifies the energy economics of desalination via reverse osmosis, which requires 3.6kWh of energy per m3 of desalinated sea-water. A cost of $1.0/m3 is necessary for a passable IRR.

Impacts can be stress-tested from varying energy prices, CO2 prices, capex costs, opex costs and energy efficiency. Our own base case estimates are derived from past projects and technical papers.

Variable Power Tariffs Exacerbate Social Inequalities?

Renewable Electricity Tariffs Exacerbate Social Inequality

This data-file tabulates the impacts of variable electricity tariffs, after switching 4.622 households over from fixed electricity tariffs, across a large-scale sample in the United States. This theme is increasingly important as intermittent renewables reach in developed world power grids (note here).

Residential electricity demand is inelastic, with a 20% price-increase yielding a mere 1% reduction in end-demand. Peakload demand fell by 4%.

However, socially “vulnerable” consumers suffered disproportionately, only achieving a 2% decrease in peakload demand. Hence, while monthly power prices rose by 18% for non-vulnerable consumers, they rose by 22% for vulnerable consumers. The results, data and study are in the data-file.

We do think that power grids will increasingly need to offer economic incentives for demand shifting, amidst increasing deployment of renewables. However based on past studies, they may need to tread carefully.

Fast-charge the electric vehicles with gas?

Fast-charge the electric vehicles with gas

When electric vehicles are widespread, how will we fuel them? Our model shows the economics can be compelling for powering fast-chargers using gas turbines.

The electricity would cost 13c/kWh, at $3/mcf input gas (e.g., in the US), 20% utilisation of the infrastructure and a c7.5% pre-tax IRR.

Carbon emissions are lowered by c70% compared to oil-fired vehicles. And the grid is spared the strain of sudden demand surges.

Is upside suggested for gas? Utilisation of the fast-charging infrastructure is much more important to the overall economics than the gas price. This means that greater EV adoption can accommodate considerably higher gas prices.

Our model is constructed as a sensitivity analysis, based on economic data from gas turbines (chart below), so you can flex the assumptions.

Copyright: Thunder Said Energy, 2019-2023.