Proving the Exceedence financial module for floating PV systems

Key Takeaways

By using Exceedence FINANCE we were able to prove the following

  • The financial module in Exceedence FINANCE can be used for other energy sources once the yield is given.
  • LCOE is higher for sea deployment projects than lake deployments, but higher yields at sea can give similar LCOE.
  • Yield is the main key cost driver, with a decrease in yield having a much greater (negative) impact on LCOE than an increase.

Project Background

Solar PV with 760GW cumulative installed capacity in 2019 is a well-established technology. Floating PV with an estimated 2.6GW in 2020 is still considered a niche market. However, it is quickly gaining traction with drivers such as land scarcity and high costs in many places, as well as by design innovations that are helping to reduce costs, and this in spite of the additional challenges associated with currents, waves and salt water HelioRec is a floating solar PV company with a novel idea to use a circular economy approach. Their floating system can be deployed inland via lakes, or offshore in the sea. Through the Interreg programme the NWE Marine Energy Alliance, HelioRec received commercial services from Exceedence. Exceedence Ltd. provided services on levelised cost of energy (LCOE) and sensitivity analysis on the key cost drivers for the HelioRec technology. Exceedence Ltd. are using their techno-financial software to support and verify the targets set by HelioRec.

Our Role

Providing insights into the cost drivers of the HelioRec technology has given clearer understanding of their proposed business models and the product solutions they are offering to ensure a profitable and competitive technology. Specifically, Exceedence has investigated the HelioRec technology for Lake and Sea applications and two different business model approaches: providing a turnkey solution versus selling the floating system technology to a project developer. HelioRec provided the yield as the starting point for Exceedence FINANCE from which to conduct the financial modelling. The resulting LCOE and other key performance indicators were calculated based on this given yield. Sensitivity analysis in the form of key cost drivers was then conducted. To compare the HelioRec models, the publicly available data from the World Bank Group (2019) was used as the baseline model.

Results

Explore potential advances in energy generation and identify opportunities for cost reduction Detailed understanding Key insights into annual energy production, local power fluctuations, loads in structural members and fatigue life expectancy, based on detailed engineering simulation Clarity Complete transparency of both financial and engineering design processes Consistency Suitable for all stages in the design process, from concept development, to model scale prototypes, and right through to full scale versions Unlock investment Increase investor confidence by de-risking projects Recognised by industry Validated via industry case studies and technical papers Environmental and societal benefits Reduces entry barriers to new developers and facilitates growth of wave energy sector in general

  • Key benefits of Exceedence FINANCE: 

    • Accurate financial metrics Financial projections based on detailed engineering models and real-world wave resources Accelerated project development
    • Screen out weaker concepts earlier, and accelerate the development and refinement of innovative designs with genuine prospects
    • Design optimisation

Key benefits of Exceedence FINANCE: Accurate financial metrics Financial projections based on detailed engineering models and real-world wave resources Accelerated project development Screen out weaker concepts earlier, and accelerate the development and refinement of innovative designs with genuine prospects Design optimisation Explore potential advances in energy generation and identify opportunities for cost reduction Detailed understanding Key insights into annual energy production, local power fluctuations, loads in structural members and fatigue life expectancy, based on detailed engineering simulation Clarity Complete transparency of both financial and engineering design processes Consistency Suitable for all stages in the design process, from concept development, to model scale prototypes, and right through to full scale versions Unlock investment Increase investor confidence by de-risking projects Recognised by industry Validated via industry case studies and technical papers Environmental and societal benefits Reduces entry barriers to new developers and facilitates growth of wave energy sector in general

Year 2020 EY (in ‘000 EUR) Exfin (in EUR) 
Revenue 59,826.55020 59,826,550.20 
Operational Costs (OPEX) (36,893.03929) (36,893,039.29) 
EBITDA 22,933,510.91 22,933,510.91 
Depreciation (11,258.68141) (11,258,681.41) 
EBIT 11,674.82950 11,674,829,50 
Financing Costs  (6,571.19950) (6,571,199.50) 
Earnings before tax 5,103.63000 5,130,630.00 
Tax (deferred) (637.95375) (637,953.75) 
Earnings after tax 4,465.67625 4,465676.25 
Profit & Loss table for year 2020 showing EY and Exfin model results side-by-side  

Where EY and EXC used the same methodology the two models produced identical results.

YR EY Challenger exfin 
 Finance costs Tax Earnings after tax Finance costs   Tax Earnings after tax 
 (EUR ‘000) (EUR ‘000) (EUR ‘000)  (EUR)   (EUR)   (EUR)  
1 -6,571.19950  –  637.95375  4,465.67625  6,571,199.50  637,953.75  4,465,676.25  
2 -6,159.31207  –  689.43968  4,826.07775  6,159,312.07  689,439.68  4,826,077.75  
3 -5,730.64371  – 743.02322  5,201.16256  5,730,643.71  743,023.22  5,201,162.56  
4 -5,284.51074  –   798.78984  5,591.52891  5,284,510.74  798,789.84  5,591,528.91  
5 -4,820.20163  –  856.82848  5,997.79939   4,820,201.63  856,828.48  5,997,799.39  
6 -4,336.97584  –  917.23171  6,420.62195  4,336,975.84  917,231.71  6,420,621.95  
7 -3,834.06270  –  980.09585  6,860.67095  3,834,062.70  980,095.85  6,860,670.95  
8 -3,310.66009  – 1,045.52118  7,318.64823   3,310,660.09  1,045,521.18  7,318,648.23  
9 -2,765.93325  – 1,113.61203  7,795.28421   2,765,933.25  1,113,612.03  7,795,284.21  
10 -2,199.01341  – 1,184.47701  8,291.33908   2,199,013.41  1,184,477.01  8,291,339.08  
11 -1,608.99637  -1,258.22914  8,807.60399   1,608,996.37  1,258,229.14  8,807,603.99  
12 –   994.94113  -1,334.98605  9,344.90232       994,941.13  1,334,986.05  9,344,902.32  
13 –   355.86833  -1,414.87015  9,904.09102       355,868.33  1,414,870.15  9,904,091.02  
14 –          -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
15 –         -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
16 –         -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
17 –          -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
18 –    -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
19 –          -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
20 –          -1,459.35369  10,215.47581                        –    1,459,353.69  10,215,475.81  
Financing cost, tax, after tax earnings for EY and Exfin results for entire project