Electricity Price Distributions in Future Renewables-Dominant Power Grids and Policy Implications

Working Paper: NBER ID: w29510

Authors: Dharik S. Mallapragada; Cristian Junge; Cathy Xun Wang; Johannes Pfeifenberger; Paul L. Joskow; Richard Schmalensee

Abstract: Future electricity systems with tight constraints on carbon emissions will rely much more on wind and solar generation, with zero marginal cost, than today. We use capacity expansion modelling of Texas in 2050 to illustrate wholesale price distributions in future energy-only, carbon-constrained grids without price caps under a range of technology/system assumptions. Tightening carbon emissions constraints dramatically increases the frequency of very low prices. The frequency of high prices also increases, and all resources earn the bulk of their energy market revenues in relatively few hours. The presence of demand response, long-duration energy storage, dispatchable low-carbon generation, or a robust market for hydrogen for non-electricity use (and for energy storage) weakens but does not undo these results. Financial instruments to hedge price volatility will consequently be more costly and it is likely that we will need to redesign capacity remuneration mechanisms to provide adequate incentives for optimal investment in VRE generation and, particularly, storage. In order to encourage economy-wide electrification, the marginal retail price of electricity should be low whenever the wholesale price is low. With automated control of demand via demand response contracts, the risks of price volatility faced by retail customers can be mitigated without sacrificing efficiency. To encourage economy-wide electrification, the marginal retail price of electricity should be low when the wholesale spot price is low. We discuss ways of reducing consumers’ risk in this world while providing adequate investment incentives.

Keywords: electricity prices; renewable energy; capacity expansion modeling; policy implications

JEL Codes: L11; L51; L94; Q41; Q42; Q49


Causal Claims Network Graph

Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.


Causal Claims

CauseEffect
market conditions (P42)financial dynamics in the energy sector (L94)
market pricing structures (D49)consumer protection strategies (D18)
demand response and energy storage (Q41)distribution of price outcomes (D39)
tightening carbon emissions constraints (Q58)frequency of very low electricity prices (L97)
increased VRE generation (O39)frequency of very low electricity prices (L97)
tightening carbon emissions constraints (Q58)frequency of high electricity prices (L97)

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