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The difference in electricity pricing based on the time of power use has led to load shifting from peak to off-peak hours in hybrid power systems (HPS). Apart from optimising electricity cost, shifting of the load may also change the capacity of storage in the system. Power Pinch Analysis has been recently applied to guide load shifting aiming to minimise the cost of electricity, considering the peak and off-peak electricity pricing. The HPS was assumed to be ideal with 100% efficiency, which is not achievable in actual operational condition. This work extends the study by scrutinising the effects of peak-off-peak load shifting on the capacity of storage in HPS. The effects of energy losses due to the inefficiency during power conversion, transfer and storage in the HPS are considered in developing shifting heuristics to ensure optimal storage size is achieved. Implementation of the proposed load shifting strategy on a case study demonstrates that a reduction of up to 30% in the storage size can be achieved, which led to a minimum storage cost. The distribution of peak hours' demand to off-peak hours also successfully provide significant savings in the electricity bill. [ABSTRACT FROM AUTHOR]

The hybrid power system (HPS) that integrates diesel/biodiesel plant with renewable energy (RE) technologies has become increasingly popular to alleviate greenhouse gases emissions issue of the sole diesel/biodiesel power system. Integrated diesel-RE power system offers cleaner power supply while minimising cost of diesel fuel and diesel system maintenance. The use of Power Pinch Analysis (PoPA) method for the integration of diesel plants and RE systems into HPS with the objective to minimise fuel requirement and operational time of diesel generator has been presented. This work aims to achieve the same objective via probability theory utilisation, to simplify the PoPA procedure involving the matching of various routes for power flows. The extended technique called the Probability-Power Pinch Analysis (P-PoPA) can give accurate results as those established from the PoPA method within a shorter analysis time because it replaces the tedious manual matching step with correction factors. All probable routes of power from RE and diesel generators to demands are considered in computing the correction factors, in order to target the minimum diesel power in the integrated system. The result of a Case Study demonstrates that 19% saving in diesel fuel consumption can be realised if the present diesel station is supported with renewable solar power in an HPS. The result of the P-PoPA method is accurate with a very minor deviation to that from the conventional PoPA technique. [ABSTRACT FROM AUTHOR]