Battery energy storage systems (BESS) store electricity and release it when it is needed, which helps grids use more renewable generation. In our webinar on 23 July 2024, Ben Kwan, Ashima Khandelwal and Hitansh Doda of Forvis Mazars compared financial modelling approaches for battery projects, with their advantages and limitations. They also covered common errors in battery financial models and how to avoid them. This article summarises the session.
You can watch the BESS financial models webinar in full.
What a battery energy storage system (BESS) is
A BESS has three main components: the battery system, the energy management system and the power conversion system. The battery system holds rechargeable cells wired together into modules, which are stacked into racks and housed in containers. The energy management system is the software that controls charging and discharging. The power conversion system converts direct current from the battery to alternating current for the grid.
Benefits and types of battery system
BESS bring better use of renewable energy, backup power, less dependence on the grid, a smaller carbon footprint and long-term cost savings. There are two types: standalone batteries, which operate on their own, and co-located batteries, which sit alongside solar or wind generation. Lithium-ion batteries are preferred for their cost, high energy density, short response time, lower environmental impact and long life.
How a BESS financial model is structured
Battery projects are usually modelled with input sheets, calculation sheets and output sheets, plus an output sheet or dashboard for the main results. The process starts with the input sheet, followed by:
- Timing: the project timeframe and the timing flags and counters
- Construction: equity and debt drawdowns, upfront fees and interest during construction
- Operations: revenue and costs during the operations phase
- Debt: debt repayments and banking ratios
- Returns: distributions and equity returns
Depreciation and tax follow, before the three financial statements come together: the cash flow waterfall, the P&L and the balance sheet.
Best practice modelling for battery projects
Forvis Mazars works to six themes for best practice financial modelling: accessibility, responsiveness, tailoring to the end user, simplicity, accuracy and adaptability. The session stressed simplicity: avoid unnecessary complexity and long formulas. Binary flags can replace nested IF statements, and simplifying assumptions can shorten formulas and make them easier to follow.
Ben Kwan, a Partner at Forvis Mazars, put it this way:
“To keep it simple, don’t model things which are not needed. If there is no need to have something like a cash sweep in your model, then don’t model it.”
Revenue stacking in battery projects
Revenue stacking means earning revenue from several sources using the same capacity. Battery projects have four main sources:
- Capacity payments, earned for having capacity available to the grid, whether or not it is used
- Arbitrage revenue, from price differences in the electricity market
- Frequency control ancillary services (FCAS), paid for keeping the grid’s frequency stable
- Event-based revenue, earned from specific events such as floods or storms
How each revenue stream is modelled
Capacity payments are modelled with binary flags calculated from the start and end dates of the payment period. Periodic payments come from the annual payment and the percentage of capacity contracted. Arbitrage revenue is the difference between the sale price and the spot price, allowing for storage costs. FCAS revenue uses the degradation index, capacity, escalation and price: the megawatts enabled for each service multiplied by the clearing price. Event-based revenue uses input revenues for major and minor events from market consultants.
Ashima Khandelwal, a Manager at Forvis Mazars, explained why capacity payments matter:
“Capacity payment is a very popular arrangement for storage projects. It acts as a safety net and ensures a steady flow of income, making it easier for developers to secure financing.”
Cost modelling in battery projects
Construction costs depend on capacity, technology, location and the type of project. The largest cost is the battery system itself. Operating costs include charging costs, operations and maintenance, land lease, rates, insurance and other fees, usually modelled as fixed costs escalated at an escalation rate. Capacity expansion costs, or repowering capex, increase the capacity and life of a battery and are funded through a capex reserve account.
BESS modelling challenges, the DSCR and debt sizing
Common modelling challenges in BESS projects include setting project capacity, integration with renewables, cost and economics, lifecycle management and performance. The debt service coverage ratio (DSCR) and debt sizing sit at the centre of any project finance model. The DSCR measures cash available against debt service, and debt sizing sets the most debt the project’s cash flows can support. Scenario analysis runs different cases and compares the outputs to show the range of returns.
Hitansh Doda, a Director at Forvis Mazars, explained the role of the DSCR:
“DSCR is used to determine the size of the loan that lenders will make available and to match the size of each repayment to cash generated in each period.”
What this means for battery project models
Battery storage will play a large part in the growth of renewable energy. Understanding the modelling approaches, best practices and common errors helps sponsors, lenders and advisors build better models for battery projects. Forvis Mazars audits and builds these models, and the webinar draws on that work.
For more on storage projects, watch our recorded webinar on co-located BESS and long-duration energy storage.
Project finance and Excel tutorials to read next
- Excel shortcuts: the keyboard shortcuts that save the most time in financial modelling
- Loan life coverage ratio (LLCR): what the LLCR measures and why it matters in project finance
- Copy-paste macros in financial models: a best practice approach to building them
- Average DSCR in financial modelling: the ways to calculate the average DSCR and their limits
- Cash sweep analysis in project finance: how cash sweep calculations are modelled and used