Business use cases
Business use cases
Business use cases - how a battery storage system creates economic value
Business use cases - how a battery storage system creates economic value
Business use cases - how a battery storage system creates economic value
An industrial battery storage system is, above all, a tool to directly influence specific cost blocks in your power bill.
This page explains the five most important economic use cases:
Peak shaving
Atypical grid usage
Self consumption optimisation
Time-of-use (time-varying and dynamic prices)
Arbitrage
The examples show how these levers work and what orders of magnitude are typically possible. In the analysis for your site, FION calculates which mix of these use cases actually applies.
An industrial battery storage system is, above all, a tool to directly influence specific cost blocks in your power bill.
This page explains the five most important economic use cases:
Peak shaving
Atypical grid usage
Self consumption optimisation
Time-of-use (time-varying and dynamic prices)
Arbitrage
The examples show how these levers work and what orders of magnitude are typically possible. In the analysis for your site, FION calculates which mix of these use cases actually applies.
An industrial battery storage system is, above all, a tool to directly influence specific cost blocks in your power bill.
This page explains the five most important economic use cases:
Peak shaving
Atypical grid usage
Self consumption optimisation
Time-of-use (time-varying and dynamic prices)
Arbitrage
The examples show how these levers work and what orders of magnitude are typically possible. In the analysis for your site, FION calculates which mix of these use cases actually applies.
1. Peak shaving
1. Peak shaving
Initial situation
Many plants have a relatively stable load level with short, high demand peaks, for example when:
several large consumers start up at the same time
compressors, furnaces or chillers start in parallel
shifts change and loads overlap
These few minutes with very high demand determine the annual peak load and thus a substantial part of demand charges and grid fees.
What the battery does
charges in periods of normal load
discharges specifically during expected peaks
reduces the measured grid power in those moments
The load curve is smoothed and peaks are reduced.
Illustrative example (simplified)
current annual peak load: 3.2 MW
target: reduce by 400 kW to 2.8 MW
typical demand charges: e.g. 150-220 €/kW per year (range based on real grid tariff sheets from projects)
Annual savings from demand charges alone:
400 kW × 150 €/kW = 60,000 €/year
400 kW × 220 €/kW = 88,000 €/year
Additional effects from other demand-related tariff components are possible and are calculated project-specifically in the detailed analysis.
Initial situation
Many plants have a relatively stable load level with short, high demand peaks, for example when:
several large consumers start up at the same time
compressors, furnaces or chillers start in parallel
shifts change and loads overlap
These few minutes with very high demand determine the annual peak load and thus a substantial part of demand charges and grid fees.
What the battery does
charges in periods of normal load
discharges specifically during expected peaks
reduces the measured grid power in those moments
The load curve is smoothed and peaks are reduced.
Illustrative example (simplified)
current annual peak load: 3.2 MW
target: reduce by 400 kW to 2.8 MW
typical demand charges: e.g. 150-220 €/kW per year (range based on real grid tariff sheets from projects)
Annual savings from demand charges alone:
400 kW × 150 €/kW = 60,000 €/year
400 kW × 220 €/kW = 88,000 €/year
Additional effects from other demand-related tariff components are possible and are calculated project-specifically in the detailed analysis.
Initial situation
Many plants have a relatively stable load level with short, high demand peaks, for example when:
several large consumers start up at the same time
compressors, furnaces or chillers start in parallel
shifts change and loads overlap
These few minutes with very high demand determine the annual peak load and thus a substantial part of demand charges and grid fees.
What the battery does
charges in periods of normal load
discharges specifically during expected peaks
reduces the measured grid power in those moments
The load curve is smoothed and peaks are reduced.
Illustrative example (simplified)
current annual peak load: 3.2 MW
target: reduce by 400 kW to 2.8 MW
typical demand charges: e.g. 150-220 €/kW per year (range based on real grid tariff sheets from projects)
Annual savings from demand charges alone:
400 kW × 150 €/kW = 60,000 €/year
400 kW × 220 €/kW = 88,000 €/year
Additional effects from other demand-related tariff components are possible and are calculated project-specifically in the detailed analysis.
2. Atypical grid usage
2. Atypical grid usage
Regulatory background
In Germany, energy-intensive companies can apply for individual grid fees under section 19 StromNEV if they relieve the grid during the high load periods defined by the grid operator. This is called atypical grid usage.
In practice - depending on the specific case - parts of the general grid fees can be significantly reduced, in some cases by several tens to several hundreds of thousands of euros per year.
Role of the battery
the battery reduces load specifically during high load time windows
production can continue largely unchanged
the resulting load profile moves closer to the criteria for atypical grid usage
Illustrative example (simplified)
current grid fees: 800,000 €/year
conservative scenario: 25-40% reduction through atypical grid usage
Savings:
25%: 200,000 €/year
40%: 320,000 €/year
Whether this order of magnitude is achievable depends on grid area, load profile, industry and legal conditions. In FION’s analysis, this use case is always evaluated based on your actual load profiles and the rules of your grid operator.
Regulatory background
In Germany, energy-intensive companies can apply for individual grid fees under section 19 StromNEV if they relieve the grid during the high load periods defined by the grid operator. This is called atypical grid usage.
In practice - depending on the specific case - parts of the general grid fees can be significantly reduced, in some cases by several tens to several hundreds of thousands of euros per year.
Role of the battery
the battery reduces load specifically during high load time windows
production can continue largely unchanged
the resulting load profile moves closer to the criteria for atypical grid usage
Illustrative example (simplified)
current grid fees: 800,000 €/year
conservative scenario: 25-40% reduction through atypical grid usage
Savings:
25%: 200,000 €/year
40%: 320,000 €/year
Whether this order of magnitude is achievable depends on grid area, load profile, industry and legal conditions. In FION’s analysis, this use case is always evaluated based on your actual load profiles and the rules of your grid operator.
Regulatory background
In Germany, energy-intensive companies can apply for individual grid fees under section 19 StromNEV if they relieve the grid during the high load periods defined by the grid operator. This is called atypical grid usage.
In practice - depending on the specific case - parts of the general grid fees can be significantly reduced, in some cases by several tens to several hundreds of thousands of euros per year.
Role of the battery
the battery reduces load specifically during high load time windows
production can continue largely unchanged
the resulting load profile moves closer to the criteria for atypical grid usage
Illustrative example (simplified)
current grid fees: 800,000 €/year
conservative scenario: 25-40% reduction through atypical grid usage
Savings:
25%: 200,000 €/year
40%: 320,000 €/year
Whether this order of magnitude is achievable depends on grid area, load profile, industry and legal conditions. In FION’s analysis, this use case is always evaluated based on your actual load profiles and the rules of your grid operator.
3. Self consumption optimisation
3. Self consumption optimisation
Initial situation
Many sites already have their own generation, for example:
PV systems on roofs or ground-mounted
CHP plants (combined heat and power)
Typical pattern:
at midday, PV generates significantly more power than is currently consumed
part of this power is exported to the grid at relatively low remuneration
at the same time, the price you pay for grid power is significantly higher than the feed-in tariff
What the battery does
absorbs surplus PV or CHP power
makes it available later at times when
grid power is more expensive, or
other use cases (e.g. peak shaving) are supported
Illustrative example (simplified)
PV generation: 4 GWh/year
today: 50% self consumption, 50% export
with battery: increase self consumption from 50% to 70%
additional self consumed volume: 20% of 4 GWh = 0.8 GWh = 800,000 kWh
grid power price: 18 ct/kWh
feed-in tariff: 6 ct/kWh
Added value per additionally self consumed kWh: 18 ct - 6 ct = 12 ct
Annual effect:
800,000 kWh × 0.12 €/kWh = 96,000 €/year
The actual values depend on your tariff, your generation assets and your load profile. In FION’s simulation, these parameters are configured specifically for your site.
Initial situation
Many sites already have their own generation, for example:
PV systems on roofs or ground-mounted
CHP plants (combined heat and power)
Typical pattern:
at midday, PV generates significantly more power than is currently consumed
part of this power is exported to the grid at relatively low remuneration
at the same time, the price you pay for grid power is significantly higher than the feed-in tariff
What the battery does
absorbs surplus PV or CHP power
makes it available later at times when
grid power is more expensive, or
other use cases (e.g. peak shaving) are supported
Illustrative example (simplified)
PV generation: 4 GWh/year
today: 50% self consumption, 50% export
with battery: increase self consumption from 50% to 70%
additional self consumed volume: 20% of 4 GWh = 0.8 GWh = 800,000 kWh
grid power price: 18 ct/kWh
feed-in tariff: 6 ct/kWh
Added value per additionally self consumed kWh: 18 ct - 6 ct = 12 ct
Annual effect:
800,000 kWh × 0.12 €/kWh = 96,000 €/year
The actual values depend on your tariff, your generation assets and your load profile. In FION’s simulation, these parameters are configured specifically for your site.
Initial situation
Many sites already have their own generation, for example:
PV systems on roofs or ground-mounted
CHP plants (combined heat and power)
Typical pattern:
at midday, PV generates significantly more power than is currently consumed
part of this power is exported to the grid at relatively low remuneration
at the same time, the price you pay for grid power is significantly higher than the feed-in tariff
What the battery does
absorbs surplus PV or CHP power
makes it available later at times when
grid power is more expensive, or
other use cases (e.g. peak shaving) are supported
Illustrative example (simplified)
PV generation: 4 GWh/year
today: 50% self consumption, 50% export
with battery: increase self consumption from 50% to 70%
additional self consumed volume: 20% of 4 GWh = 0.8 GWh = 800,000 kWh
grid power price: 18 ct/kWh
feed-in tariff: 6 ct/kWh
Added value per additionally self consumed kWh: 18 ct - 6 ct = 12 ct
Annual effect:
800,000 kWh × 0.12 €/kWh = 96,000 €/year
The actual values depend on your tariff, your generation assets and your load profile. In FION’s simulation, these parameters are configured specifically for your site.
4. Time-of-use and dynamic prices
4. Time-of-use and dynamic prices
Initial situation
Many industrial companies no longer procure electricity at a single flat energy price, but use professional procurement strategies, for example:
structured procurement in tranches
portfolio procurement with a mix of forward and spot exposure
contracts closely linked to wholesale prices (day-ahead, intraday)
models with clearly separated high and low tariff periods
What all these models have in common:
There are clear differences between “cheap” and “expensive” hours. Behind-the-meter batteries can systematically exploit this price structure.
What the battery does
charges in low price hours, for example
when there is high wind or PV generation in the system
during contractually defined low-tariff or low-spot-price phases
discharges in high price hours to reduce expensive imports from the grid
coordinates this use with other use cases (peak shaving, self consumption, atypical grid usage) so that the effects reinforce each other
Illustrative example (simplified)
average price difference between “cheap” and “expensive” hours in the procurement portfolio: 8-12 ct/kWh
the battery shifts an average of 1.5 MWh/day from expensive to cheap hours
annual shifted volume: 1.5 MWh/day × 365 days = 547.5 MWh = 547,500 kWh
Annual effect:
at 8 ct/kWh: approx. 43,800 €/year
at 12 ct/kWh: approx. 65,700 €/year
In the analysis, FION checks how your existing contracts and procurement strategies are structured, whether such time price differences can actually be used, and what order of magnitude of savings is realistically achievable.
Initial situation
Many industrial companies no longer procure electricity at a single flat energy price, but use professional procurement strategies, for example:
structured procurement in tranches
portfolio procurement with a mix of forward and spot exposure
contracts closely linked to wholesale prices (day-ahead, intraday)
models with clearly separated high and low tariff periods
What all these models have in common:
There are clear differences between “cheap” and “expensive” hours. Behind-the-meter batteries can systematically exploit this price structure.
What the battery does
charges in low price hours, for example
when there is high wind or PV generation in the system
during contractually defined low-tariff or low-spot-price phases
discharges in high price hours to reduce expensive imports from the grid
coordinates this use with other use cases (peak shaving, self consumption, atypical grid usage) so that the effects reinforce each other
Illustrative example (simplified)
average price difference between “cheap” and “expensive” hours in the procurement portfolio: 8-12 ct/kWh
the battery shifts an average of 1.5 MWh/day from expensive to cheap hours
annual shifted volume: 1.5 MWh/day × 365 days = 547.5 MWh = 547,500 kWh
Annual effect:
at 8 ct/kWh: approx. 43,800 €/year
at 12 ct/kWh: approx. 65,700 €/year
In the analysis, FION checks how your existing contracts and procurement strategies are structured, whether such time price differences can actually be used, and what order of magnitude of savings is realistically achievable.
Initial situation
Many industrial companies no longer procure electricity at a single flat energy price, but use professional procurement strategies, for example:
structured procurement in tranches
portfolio procurement with a mix of forward and spot exposure
contracts closely linked to wholesale prices (day-ahead, intraday)
models with clearly separated high and low tariff periods
What all these models have in common:
There are clear differences between “cheap” and “expensive” hours. Behind-the-meter batteries can systematically exploit this price structure.
What the battery does
charges in low price hours, for example
when there is high wind or PV generation in the system
during contractually defined low-tariff or low-spot-price phases
discharges in high price hours to reduce expensive imports from the grid
coordinates this use with other use cases (peak shaving, self consumption, atypical grid usage) so that the effects reinforce each other
Illustrative example (simplified)
average price difference between “cheap” and “expensive” hours in the procurement portfolio: 8-12 ct/kWh
the battery shifts an average of 1.5 MWh/day from expensive to cheap hours
annual shifted volume: 1.5 MWh/day × 365 days = 547.5 MWh = 547,500 kWh
Annual effect:
at 8 ct/kWh: approx. 43,800 €/year
at 12 ct/kWh: approx. 65,700 €/year
In the analysis, FION checks how your existing contracts and procurement strategies are structured, whether such time price differences can actually be used, and what order of magnitude of savings is realistically achievable.
5. Arbitrage
5. Arbitrage
Principle
Arbitrage means actively using a battery in power and ancillary service markets to monetise price differences. The focus is typically on:
spot and day-ahead markets
intraday markets
selected ancillary service markets, where technically and regulatorily feasible
The battery is dispatched so that it charges in hours with very low prices and is used or marketed in hours with high prices or scarcity.
In practice, this is usually done via an energy trader or direct marketer who integrates the battery into defined market processes and generates a monthly or quarterly revenue stream for the customer.
Position in the overall picture
arbitrage is an additional revenue stream on top of site-specific savings
in many projects, peak shaving, atypical grid usage and self consumption form the core of the business case
arbitrage can significantly enhance this core economically, but must be structured cleanly from a regulatory, contractual and technical perspective
In FION’s modelling, arbitrage is therefore treated as an additional lever: first, the classic industrial use cases are calculated against your site data, then we assess whether and to what extent participation in spot, day-ahead, intraday and ancillary service markets is sensible and feasible.
Principle
Arbitrage means actively using a battery in power and ancillary service markets to monetise price differences. The focus is typically on:
spot and day-ahead markets
intraday markets
selected ancillary service markets, where technically and regulatorily feasible
The battery is dispatched so that it charges in hours with very low prices and is used or marketed in hours with high prices or scarcity.
In practice, this is usually done via an energy trader or direct marketer who integrates the battery into defined market processes and generates a monthly or quarterly revenue stream for the customer.
Position in the overall picture
arbitrage is an additional revenue stream on top of site-specific savings
in many projects, peak shaving, atypical grid usage and self consumption form the core of the business case
arbitrage can significantly enhance this core economically, but must be structured cleanly from a regulatory, contractual and technical perspective
In FION’s modelling, arbitrage is therefore treated as an additional lever: first, the classic industrial use cases are calculated against your site data, then we assess whether and to what extent participation in spot, day-ahead, intraday and ancillary service markets is sensible and feasible.
Principle
Arbitrage means actively using a battery in power and ancillary service markets to monetise price differences. The focus is typically on:
spot and day-ahead markets
intraday markets
selected ancillary service markets, where technically and regulatorily feasible
The battery is dispatched so that it charges in hours with very low prices and is used or marketed in hours with high prices or scarcity.
In practice, this is usually done via an energy trader or direct marketer who integrates the battery into defined market processes and generates a monthly or quarterly revenue stream for the customer.
Position in the overall picture
arbitrage is an additional revenue stream on top of site-specific savings
in many projects, peak shaving, atypical grid usage and self consumption form the core of the business case
arbitrage can significantly enhance this core economically, but must be structured cleanly from a regulatory, contractual and technical perspective
In FION’s modelling, arbitrage is therefore treated as an additional lever: first, the classic industrial use cases are calculated against your site data, then we assess whether and to what extent participation in spot, day-ahead, intraday and ancillary service markets is sensible and feasible.
Combination of use cases and impact on payback
Combination of use cases and impact on payback
In practice, these use cases rarely occur in isolation. A battery can, for example:
cut load peaks in certain hours
absorb PV surplus at the same time
and additionally react to price signals from your tariff
Studies and real world projects show that multi use strategies can significantly improve the economics of batteries, because the same hardware serves several revenue and savings streams.
Illustrative combined order of magnitude (for illustration only)
For a site with:
peak shaving effect: 60,000-80,000 €/year
self consumption optimisation: approx. 90,000-100,000 €/year
time-of-use optimisation: 40,000-60,000 €/year
you arrive at a combined order of magnitude of e.g. 150,000-220,000 €/year when synergies and overlaps are taken into account.
With an investment volume in the range of 600,000-900,000 €, this would roughly correspond to static payback periods of 3-6 years. The concrete calculation in FION’s analysis is based on your project data (investment, operating costs, tariffs, grid fees, utilisation).
How FION manages the use cases for you
How FION manages the use cases for you
The five use cases are not a configuration menu you have to manage yourself. They are the building blocks FION uses to optimise your battery economically.
In the analysis phase, FION determines on the basis of your load profiles, tariffs, grid fees and contracts:
which use cases are technically, contractually and regulatorily possible at your site
how strong these use cases are likely to be in your situation
which battery size and configuration unlocks these effects best
In ongoing operation, FION’s software takes over the control:
it continuously evaluates whether the battery should currently be used for peak shaving, atypical grid usage, self consumption, time-of-use optimisation or arbitrage
it considers technical limits (power, capacity, state of charge) and economic effects at the same time
it automatically adjusts the strategy when load profiles, generation or market conditions change
For your team this means:
FION determines and runs the best combination of use cases for you in the background. You do not have to define operating strategies yourself - you see in dashboards and reports which savings and effects the battery is actually delivering.
First understand the load profile,
then size the battery.
First understand the load profile,
then size the battery.