Generation planning and catchment management in Fiji

Client: Fiji Electricity Authority
Location: Viti Levu, Fiji
Date: 2000

Developing hydrological and system models to optimise hydropower operation, and exploring the potential impacts of logging on the catchment and yield

Background

Fiji’s Monasavu hydro scheme was commissioned in 1983 and provides around half the nation’s power. The remaining energy is produced from a number of diesel units. The hydro scheme includes a large dam and an 83 MW power station.

The Fiji Electricity Authority (FEA) engaged Entura to develop models for operating the Monasavu hydropower scheme optimally in the short, medium and long term, with the aim of minimising expensive diesel generation. The FEA also asked Entura to explore the potential impacts on the Monasavu hydro scheme of future logging in the catchment. Logging can impact on the hydropower scheme through increased sedimentation reducing the storage capacity and having the potential to damage turbines, and through changes in yields

Solution

Entura developed a suite of generation planning models for short-term and long-term optimisation of the Monasavu hydro scheme.  The models included aninflow forecast model predicting inflows for a short-term optimisation model, a stochastic dynamic programming model for medium-term and long-term optimisation, and a simulation model for evaluation of the optimum rule curves.

Entura also undertook a catchment management study to determine, quantify and cost the impact of future logging within the catchment on the performance of the Monasavu hydroelectric scheme. This included analysis of the impacts of logging on rainfall, evaporation, climate and weather patterns, sedimentation, ground stability and power station output.

Outcome

Entura’s development of generation planning models for the Monasavu power scheme offered the FEA the detailed information it needed to determine the optimal operation of the power station in the short term and into the future. These planning tools enabled the FEA to better estimate budgetary requirements for diesel, and to minimise the amount of diesel generation required to meet demand for power into the future.

The information provided through this study enabled FEA to better understand the impact of different logging scenarios on the catchment and the associated cost implications for hydro operation. The catchment management study recommended a method and rate of logging for the catchment that would minimise impacts on the lake and power station operation, which, enabled the catchment to be managed to ensure ongoing benefits from logging and sustainable power station operation.

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