Flexibility mechanisms and pathways to a highly renewable US electricity future

Abstract

This study explores various scenarios and flexibility mechanisms to integrate high penetrations of renewable energy into the United States (US) power grid. A linear programming model-POWER-is constructed and used to (1) quantify flexibility cost-benefits of geographic aggregation, renewable overgeneration, storage, and flexible electric vehicle charging, and (2) compare pathways to a fully renewable electricity system. Geographic aggregation provides the largest flexibility benefit with ~5-50% cost savings, but each region's contribution to the aggregate renewable portfolio standard (RPS) target is disproportionate, suggesting the need for regional-and-resource-specific RPS targets. Electric vehicle charging yields a lower levelized system cost, revealing the benefits of demand-side flexibility. However, existing demand response price structures may need adjustment to encourage optimal flexible load in highly renewable systems. Two scenarios with RPS targets from 20% to 100% for the US (peak load ~729GW) and California (peak load ~62GW) find each RPS target feasible from a planning perspective, but with 2x the cost and 3x the overgeneration at a 100% versus 80% RPS target. Emission reduction cost savings for the aggregated US system with an 80% versus 20% RPS target are roughly $200 billion/year, outweighing the $80 billion/year cost for the same RPS range.

Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches

“…Dedicated transmission expansion planning models are beyond the scope of this review. Examples of GEP models are Balmorel (Ravn et al, ), LIMES‐EU (Nahmmacher et al, ), OptGEN (PSR, ), POWER (Frew et al, ), ReEDS (Short et al, ), REMix (Gils, Scholz, Pregger, Luca de Tena, & Heide, ), SWITCH (Fripp, ) and WASP (IAEA, ). GEP models incorporate some operational details but mainly consider investment possibilities and policy constraints such as annual carbon limits.…”

Electrical Energy Storage with Engineered Biological Systems

“…By contrast, Shaner et al predict that 20 PJ of storage, about 12 hours of supply, will be needed to support 80% renewables [6]. To implement a 100% renewable electricity portfolio in the US, Frew et al estimate that between 6 (without electric vehicles) and 21 (with electric vehicles) PJ of storage would be needed [2,5,7]. Shaner et al make an even bigger prediction, that several weeks of stored supply will be needed to support 100% renewables [6].…”

“…At the time of writing, the US consumes electricity at a rate of ≈ 500 gigawatts (GW) [3] (total US energy consumption is ≈ 3 terawatts (TW) [4]). Frew et al predict that to support an 80% renewable electricity portfolio in the US, between 0.72 and 11.2 petajoules (PJ; 1 PJ = 1 × 10 15 J or 277.8 gigawatt-hours (GWh)) of storage are needed [2,5]. By contrast, Shaner et al predict that 20 PJ of storage, about 12 hours of supply, will be needed to support 80% renewables [6].…”

Silver Buckshot or Bullet: Is a Future “Energy Mix” Necessary?

“…In some published scenarios, arbitrary allocations of wind, water and sunlight are accumulated to reach a total target energy supply [11][12][13]. In other modelled futures, attempts are made to balance electricity demand with supply at all times, using gas (bio or fossil), hydro, stored heat and dispersed "supergrids" to try to cover shortfalls [16,[36][37][38][39].…”