Market Impact Analysis for Renewable Energy Trading

Thinking about the changing energy resource mix and how it impacts electricity prices. In pursuit of insights, it’s helpful to think through edge cases. One is a grid powered by 100% #renewableenergy and energy storage. A recent study by the Leibniz Information Centre for Economics looks at 2 markets, Texas (ERCOT) & Germany, and explores if energy-only markets can function with a resource mix of only #wind, #solar, Demand Response (DR) and storage. Will capacity mechanisms be needed in markets after the energy transition? Can a healthy market exist with energy storage as the only firm capacity? Yes, they conclude, energy-only markets remain perfectly viable even when exclusively #windenergy, solar, DR, and #energy storage. Using cost scenarios based on 2020 data and 2050 forecasts, they find average market prices in #ERCOT are reasonable and could become lower. What happens to the merit order (the electricity supply curve of suppliers in order of their marginal cost)? The figure below shows the new merit order for ERCOT and the residual demand / energy storage utilization. The merit order looks like today’s: relatively few hours have zero prices, a vast middle section has positive prices (mostly $40-$50/MWh), and peak price periods still exist and are an essential element for fixed-cost recovery. In the new merit order, storage plays a critical role because it often sets prices on both the buy and sell sides, thus sets the market price for #electricity. Other interesting ERCOT results: ·       Changes in wind and solar costs from 2020 to 2050 would raise the optimal capacity ratio of solar to wind capacity from about 0.6 to 2.0. ·       In 2050, solar’s share of ERCOT’s power output would need to increase from 3% to 61%, while wind output would need to increase from 23% to 39%. ·       The nominal capacity ratio of storage to wind + solar is about 0.28. Some limitations of the modeling: ·       No explicit transmission infrastructure in the model (i.e., no transmission constraints). ·       Ancillary services still need to be priced separately and are not considered. ·       The duration of storage (MWh) is not accounted for, only power capacity (MW). ·       No negative pricing was allowed. Two additional thoughts: In very high renewable, energy-only markets, where fossil fuel plants are not allowed or available, average energy prices should converge on the Levelized Cost of Storage (LCOS, i.e., the cost per cycle of storage needed to cover all costs and investment returns for the life of the project). Lazard’s most recent analysis shows stand-alone storage LCOS at $124/MWh for 100 MW/ 400MWh BESS, and this needs to – and will – come down in the next decade (it’s $60/MWh and $45/MWh respectively, for solar and wind hybrids). Also, curtailment (or negative pricing) is not necessarily a market flaw - it can offset lower and fewer peak pricing events by allowing #energystorage to charge at zero cost (or less).   References in comments.

Surprising stat: Our Enverus Intelligence® Research team found that over 284 GW of queued US solar & wind projects DON'T require federal tax credits to be competitive! This means they can sign PPAs at or below merchant power + REC costs.   While the IRA's future is debated in the Senate, the renewables market isn't just waiting. We predict 3 key themes for successful development: Revenue Maximization: - Resilient demand for PPAs has been demonstrated through growing demand despite rising prices the last two years. - If PPA demand holds up, we will continue to see support for renewable development through higher PPAs (example: average ERCOT solar LCOEs going from $32/MWh to $53/MWh on average) - Developers are pursing revenue stacking opportunities (co-location with storage and load) to add value across multiple technologies and capitalize on the highest contract values Portfolio Prioritization: Focusing on assets with state support, high REC prices, and competitive network upgrade costs is key. Cost Efficiencies: Slashing capex via smarter site selection (early visibility into network upgrade costs) & iterative design for optimal LCOE. The competitive edge in renewables will belong to developers who proactively enhance their decision-making process through the adoption of intelligent, next-generation tools that transform complex data into decisive action.  

Now out: our latest paper (pre-print) A study on cross-border "cannibalization" of wind and solar energy https://lnkd.in/ebPCdA5m It is now well established theoretically and empirically that the market revenues of wind and solar energy tend to decline as their market share grows. I call this the "market value drop". (Actually, I wrote my very first paper about this: https://lnkd.in/eFtNgpfR) In this paper, we use 2015-23 empirical data in monthly granularity. We see a drop in wind and solar market value (capture rates) in almost all European bidding zones. We are particularly interested in the role of imports and exports as a source of power system flexibility. Many EU bidding zones are *really* well interconnected, with import/export capacity >>100% of their average electricity demand. My favorite results figure shows the impact of domestic wind (dark) and neighbouring wind (light) as a function of my own interconnectedness. If I have no interconnectors, domestic wind depresses market value strongly. Interconnection dampens this effect. However, there is a downside to this: with more interconnectors, the impact of my neighbour's wind on my own value factor becomes stronger. We have tons of more interesting findings. For example: If wind market share increases by 1 pp in Europe, the capture rate drops by about 1.1 pp. This is the combined effect of domestic (0.6) and cross-border (0.5) cannibalization. Many thanks for the great work: Clemens Stiewe, Alice Lixuan Xu, Anselm Eicke! This has been a long haul, but I am pretty proud of how far we got with this! https://lnkd.in/ebPCdA5m