The Economics of Integrating Alternative Energy: A Farm Case Study at Emerald, Queensland

National environmental objectives have led to the development of government policies that create incentives for businesses to invest in renewable energy. These policies, increasingly affordable renewable energy and storage technology have aligned to deliver both economic benefits to farmers and co-benefits to the environment in on- and off-grid scenarios. This analysis aims to determine the economic feasibility of renewable and innovative energy systems to assist in reducing grid electricity cost for irrigation pumps and small industrial applications. Using a case study approach, optimal engineering and economic assessment are applied on a farm characterised by energy consumption in three different scales and usage patterns; sporadic large seasonal use, uniform industrial use and small-scale industrial use. The case study farm’s electricity demand and pricing agreements were assessed and entered into the Hybrid Optimisation of Multiple Energy Resources design software to analyse a range of hypothetical microgrid installations. A major aspect of the study is the connectivity between Government incentives, tariff uncertainty and the electricity retailers’ rules regarding feed-in-tariffs and network connection criteria. While the challenge of aligning seasonal demand with renewable energy supply remains, the cost competitiveness of solar energy proves a realistic supplementary source for grid-connected agricultural loads where year-round utilisation rates are high. Of each of the case study sites evaluated in this paper, the highest returning economic and environmental business case occurred where the modelled micro-grid included photovoltaic (PV) and remained eligible for a Feed-in-tariff – enabling revenue creation out-of-season. Those larger PV systems exceeding the export limit of 30kW still showed a lower cost of energy than the grid, however, where a diesel genset was included to avoid peak tariffs, carbon emission abatement was negligible. Designing optimal engineering solutions to reduce on-farm energy costs is heavily dependent on awareness of current carbon and energy policy incentives, as well as the changing landscape of connection rules and feed-in-tariffs.