Least Cost Network Expansion and Loss Reduction Model

We have developed a modelling approach to least cost network expansion that may be more appropriate in the many developing or emerging economies than conventional network modelling tools. The model was inspired by our hands on experience supporting Nigerian distribution companies, due to:

  • - Lack of robust data: distribution companies have data on loads, but in developing countries little reliable data is available on voltage drops, reactive loads and power factors. Similarly, for suppressed loads since the network typically does not meet customer demand. In many cases, network equipment is operating outside its original design life or operating parameters. The future amount of available generation is also uncertain, with plans for new generation often delayed or dependent on factors beyond the utility’s control.
  • - Simple network: the network is largely radial in nature thus simplifying the load flows across the network, meaning that detailed load flow analysis is often not required.
  • - Limited capital: In a cash-constrained environment, utilities cannot invest in all the required upgrades immediately. It is important to identify the most cost-effective overall investment plan.
  • - Appropriate level of complexity for the problem: given that the uncertainty in the input data, we believe it is possible to achieve nearly as great an accuracy with a far simpler modelling approach. A secondary benefit is that the model can be more accessible and easier to interpret for utility staff. Our spreadsheet-based model consists of a Network Constraints Model and Loss Reduction Model and provides an integrated solution to the network and loss reduction challenges.

Our Least Cost Network Expansion and Loss Reduction Model will produce a least cost investment plan. This can be used to update a utility’s investment plan by identifying the network upgrades, meter roll out and other investment that will provide the utility with the most rapid payback and financial returns.