This question has two components:
How do I simulate innovation in energy storage in En-ROADS?
Why is energy storage important?
1. How do I simulate innovation in energy storage in En-ROADS?
You can see in the Storage Costs graph in En-ROADS (under Graphs > Financial), that as renewables grow, demand for energy storage increases. This results in money needing to be spent on this additional infrastructure, and so costs rise as well. While En-ROADS assumes that storage requirements will not limit the use of renewable energy, the costs of renewables in the model reflect the added costs from energy storage. Innovation in energy storage is therefore an important component of a clean energy future. Options to affect energy storage parameters and assumptions in En-ROADS include:
R&D breakthrough cost reduction for storage: In the Renewables advanced settings (click the three dots next to the Renewables slider), scroll down to the “Storage R&D breakthrough cost reduction” and “Storage breakthrough year” sliders. The “Storage R&D breakthrough cost reduction” slider represents the percent that a research and development (R&D) breakthrough suddenly reduces the supply cost of energy storage. The values represent a decrease in cost from the point when the breakthrough occurs.
Assumptions (Go to the Simulation menu in the top toolbar of the En-ROADS interface and select Assumptions):
Max potential for electric demand response technology: You can adjust the assumptions in the model about how much energy storage capacity can be met by demand response measures (rather than innovations in batteries, for example). Demand response measures include shifting energy use toward the times when energy supply is at its peak (for example, when the sun is shining for electric grids dependent on solar). Scroll down to “Maximum potential—electrification, retrofits, and storage” and open the sub-menu by clicking on the triangle next to it, then scroll down to the “Max potential for electric demand response technology” slider and select a value.
Breakthrough commercialization time for storage: You can adjust the assumptions in the model about the breakthrough commercialization time for storage. Scroll down to “Breakthrough commercialization time” and open the sub-menu by clicking on the triangle next to it, then scroll down to the Storage slider and select a value. This slider adjusts the number of years for a breakthrough in technology to reduce costs of storage for renewables to reach its full cost reduction potential.
Progress ratio for storage: You can adjust the assumptions in the model about the progress ratio for storage. Scroll down to “Progress ratio” and open the sub-menu by clicking on the triangle next to it, then scroll down to the Storage slider and select a value. This slider represents how much costs fall due to learning, experience, and ‘economies of scale’. Every doubling of cumulative capacity of storage brings a percentage reduction in costs. The progress ratio equals 1 minus that percentage reduction. For example, if the progress ratio is 0.8, then every doubling would bring a 20% drop in cost (since 1 - 0.8 = 0.2 or 20%). With every doubling of cumulative installed capacity, the cost gets multiplied by the progress ratio. A lower value would indicate faster learning.
2. Why is energy storage important?
The need for storage arises because electrons can’t be stored in the grid: electricity generation and load (electricity consumption) must be equal. Supply must match demand.
In the traditional electric grid, generation is varied by grid operators to meet the load. Load fluctuates throughout the day and across the seasons. Generation can be varied to respond by having some power plants always running (base load, traditionally coal and nuclear), some that are scheduled to run during the daily peak (often natural gas), and some that can be brought online very quickly if demand rises beyond what was forecast on a particular day, such as during a heatwave that boosts electricity use as people turn up their air conditioning (so-called “peakers” and spinning reserve). In this traditional model, demand is assumed to be external; it’s a function of customer decisions, weather, etc., and production must be varied to meet it.
The storage issue arises because wind and solar are variable and are “non-dispatchable.” Unlike conventional power plants they can’t be turned on and off as needed to meet load. However, the underlying need is not storage; it is to ensure that generation and load are equal. This can be accomplished in many ways:
Transmission: Building long-distance transmission lines enables utilities to send power from where it is abundant to where it is needed, e.g. from where it is sunny or windy now to where it is cloudy or calm. Combined with better weather forecasting, this enables grid operators to balance generation and load.
Complementary renewable energy sources: There are complementarities between wind and solar in some regions: for example, in the U.S. Great Plains, it is windier at night, and solar of course is generated during the day. These can help balance generation and load.
Demand response: Real-time pricing and demand response can shape load to match generation. Power applications such as heating and cooling, refrigeration, and home appliances like dishwashers and washer/dryers can be designed to sense the current real-time price of power and then adjust when they run, subject to constraints like “don’t let the temperature in my house go above 75F or below 66F” and “make sure the dishes are clean by morning" (or whatever the user prefers). Similarly, some industrial processes can be demand-responsive.
The combination of these technologies, chosen to be locally appropriate to each region, have already enabled a number of nations to achieve much higher shares of variable renewable power from wind and solar than people thought was possible just a few years ago. Denmark generated half of its energy consumption in 2019 from renewables, predominantly wind. Denmark balances load and generation by, for example, exchanging power with Norway and Sweden. When there is excess wind generation in Denmark, the power goes to Norway and the Norwegian hydro dams run less, storing the water in reservoirs for use when Denmark needs more than its turbines and solar provide.
Battery storage is becoming cheaper, with a roughly 20% learning curve (20% cost reduction per doubling of cumulative experience). There are also potential complementarities between variable generation from wind and solar and the growing number of electric vehicles, each with a battery sitting idle most of the day. These vehicles could provide electricity when the grid needs it and charge when power is abundant and cheap (e.g. mid-day in sunny regions; night in windy ones).
In sum, the problem of balancing generation and load in a system with growing shares of variable renewable generation involves a number of solutions, including but not limited to battery storage.