H3P PROJECT - Modular Peak Power Plant
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    • Project Introduction >
      • Background
      • Concept & Definition
      • Individual components
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      • Electrochemistry
      • System Losses
      • Assumptions & Symbols
    • Fuel Cell Measurements
  • Model
    • Approach
    • Parameters Definition
    • MATLAB Model
  • Results & Conclusions
    • H3P - Results
    • Discussion
    • Conclusions
  • Additional Information
    • Further Developments
    • Other Considerations
    • Alternative Applications
    • Acknowledgments
    • Bibliography
  • Team
  • Home
  • Context
  • Project
    • Project Introduction >
      • Background
      • Concept & Definition
      • Individual components
    • Theory >
      • Electrochemistry
      • System Losses
      • Assumptions & Symbols
    • Fuel Cell Measurements
  • Model
    • Approach
    • Parameters Definition
    • MATLAB Model
  • Results & Conclusions
    • H3P - Results
    • Discussion
    • Conclusions
  • Additional Information
    • Further Developments
    • Other Considerations
    • Alternative Applications
    • Acknowledgments
    • Bibliography
  • Team

MODEL

Approach
Parameters Definition
MATLAB Model

Approach

Scope

        Let's remind that this project aims to assess the cost-effectiveness of a novel type of peak power plant using hydrogen as a means of storage, whose the principle has been described before. We chose to align our module size on the National Grid STOR (Short Term Operation Reserves) requirements.
        Therefore, we are investigating the  viability of a module able to deliver 3 MW for 2 hours windows.
        In order to be as realistic as possible in this study, a lot of different parameters were to consider. Here are the three kind of elements we had to take into account:
  • Technical parameters
    Characterising the physical behaviour of the module itself.

  • UK electricity grid data
    Giving information on the demand and pricing patterns of electricity within the UK.

  • Financial parameters
    Materialising the money going back and forth, concerning both the installation and the operation of the plant.
Picture
Main parameters embeded into the model.
        As all these parameters are all interacting with each other and are likely to impact the cost-effectiveness of our system, they had to be embedded into the model we developed. More details about how they have been defined are given in the next page [Parameters Definition].

How to assess the cost-effectiveness of our system?

         To evaluate the viability of our module, we chose to address the problem backward. Here are described the different steps of the process (these crucial steps are shown on the following diagram):
  • Determine how big our module and its components would have to be in order to supply enough electricity.  (1)
  • Estimate what would be the required capital cost of such a system if we wanted to go out, buy it and install it.  (2)
  • Simulate the operation of the peak power plant over a year (considering incomes and expenditures) and calculate the annual running cost surplus.  (3)
  • Based on this surplus and on typical financial parameters (loan repayment period, rate of interest), determine how much money one could have been able to borrow to the bank.  (4)
  • Does this possible capital investment enough to cover the actual required capital cost of the system (calculated at the second step) ?  (5)
Picture
Viability assessment - Overall Approach

        Thus, we will be able to claim that our system is cost-effective if in the given circumstances: the money we can make from the operation of our module is enough to cover its purchase cost, its installation cost, and its Operation & Maintenance costs.

        The elements appearing in blue on the Fig. 2 are the main inputs of our model. All together, they represent what we will call a scenario. In the next section, we explain how we defined some of these parameters and how they impact the viability of the system.
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