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Neil Walbran Consulting was formed in 1995 to offer a range of consulting services to the Electrical Power industry. The company consists of Neil Walbran and a range of associates. We specialise in project management and advice to those designing or operating wholesale power markets. Areas of expertise include:

  • Project management of regulatory and market design change projects;
  • Modelling of power system operation in a wholesale market environment;
  • Analysis of the value of generation and transmission investments;
  • Design of market trading arrangements;
  • Provision of training in market operations; and
  • IT systems design and implementation for wholesale market operation.

As part of our services we provide analysis of generator and transmission investments based on historic and future market prices. To do this we have developed a number of analytical models. As an introduction to this modelling service we have provided a few sample, simplified, models and data sets below:

This data has been derived from the centralised data set provided by the Electricity Commission and contains the same limitations as that data set.

One of the reasons for having an electricity market is to send signals for the need for new investment and avoid the need for central planning of generation investment.  So I thought it might be interesting to have a quick look at whether the NZ electricity market has been sending adequate investment signals and what the trends in these signals might be.  Click the link below to download a spreadsheet showing trends in spot and contract prices and then analysis of profitability of different types of new entrant generators based on these prices and some assumptions about the cost of new entrant generators.  I would welcome feedback on these graphs and the assumptions behind them.  If you would like a copy of the full spreadsheet, where you can adjust the input assumptions and see the impact on the generator earnings, then email me via the contact us link at the top of this page.


Click here to download spreadsheet


Managed load, or embedded peaking generation, has value in terms of avoiding peak transmission charges, delaying the need for construction of new transmission, avoiding voltage support charges, and reducing overall energy purchase charges. Significant blocks of managed load can also participate in the interruptible reserves market if the response time and level of guaranteed interruption is adequate. The spreadsheet below calculates the value the energy market value of managed load or embedded peaking generation. On top of this energy market value there would be potential value in avoided transmission costs, avoided distribution costs, and avoided ancillary service costs. These are relatively easy to calculate and are not directly included in this spreadsheet.

Energy Optimisation - ManagedLoad or Peaking Generation


The NZ market is a mixed hydro and thermal market exposed to risk of energy shortages in a dry year.  The market manages this risk via price signals rather centralised co-ordination of water storage.  The centralised data set from the Electricity Commission contains data on historic inflows and storage, as well as prices.  The spreadsheet below shows how the market has evolved to better manage this risk over time as participants learn about hydro risk management.  It plots the variability of inflow sequences (3 month cumulative inflows) against hydro risk (storage margin above a given risk profile).  It shows how the market got more conservative in managing hydro risk as each new dry year emerged.  Noting that this more conservative water management was achieved via price signals that got sharper over time.

Hydro inflow storage and price data


The Centralised Data Set also provides historical information on generator and load metered quantities (in kW for each half hour trading period). The following files provide a reasonable picture of average generation and load by month and trading period.

Average Load by Month and Trading Period

Monthly Total Generation by Fuel Type

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