Reliable and affordable electricity supply within remote and isolated power systems presents both unique opportunities and challenges. In part, the challenges result from a lack of central network infrastructure and a reliance on diesel fired generation. Unfortunately, the cost of supplying diesel to these communities is high and rising. Opportunities within remote and isolated systems include renewable energy integration, with renewable energy one technology able to reduce both the cost and pollution of diesel generation. To successfully integrate renewable energy technologies, both the stochastic nature of the renewable energy resource, and the operating characteristics of diesel generation require consideration. Typically, diesel generation is configured to run at fixed speed and load, achieving peak efficiencies within 70-80% of rated capacity. Diesel generation is also commonly sized to peak demand, reducing system flexibility. In order to successfully integrate renewable energy, the system requires flexibility. While energy storage is conventionally integrated to improve system flexibility, this step adds cost and complexity to the system. An alternative approach exists in redefining the low-load capability of diesel generation. Low-load diesel allows a diesel engine to operate across its full capacity in support of improved renewable energy utilisation. As low-load diesel applications rely entirely on the capabilities of existing diesel assets, they promise a low cost, low complexity substitute. This thesis explores low-load diesel application, identifying a substantial role for the approach in addressing many of the barriers currently observed to high renewable energy penetration architectures. In recommending low-load diesel application as a precursor to energy storage integration, the system, economic and environmental impacts of low-load diesel application are quantified. The results identify a novel pathway for consumers to transition from low to medium levels of RE penetration, without additional cost or system complexity.