A new approach to the identification of a suitable energy mix for projects is required to ensure that sustainable, economically viable generation results are achieved, Deloitte power solutions strategy and innovation lead Gareth Gregory has asserted.

He held that the selection of energy technology should be the result of the output of an energy model, in which all operational variables are considered, thereby avoiding a situation in which the technology itself became the catalyst of the investment decision.

“Understanding the all-inclusive approach offered by energy modelling and only then committing to a generation technology, ensures that the decision to implement a particular generation technology meets the fundamentals required to produce a sustainable net effect,” he commented.

Gregory said the fundamentals that had to be dealt with in the selection of a technology were vast and included issues relating to energy security, policy, energy economics, cost, access to the power grid, the capacity of the grid and mitigation strategies for the control of greenhouse-gas emissions.

In addition, scenarios for capital efficiency should be built and analysed.

“Consideration given to energy efficiency as a standalone focus is simply not enough when outlining the critical role of energy modelling and planning on energy investment decisions,” he held.

Gregory believed the modelling process ensured that energy investment decisions were based on an accurate energy model and that generation and supply decisions developed based on future scenarios did not rely solely on raw historical data, which may not be applicable to the mitigation of future risk.

It further ensured the development of an energy model that “spoke directly to" the elaboration of a business case based on an all-inclusive model, as well as the development of scenario planning that offered a platform to accurately test options without incurring capital risk.

“In addition, modelling provides substantiated integrated reporting based on fact and not merely operational efficiency assumptions, subsequently freeing up cash flow for other activities directly related to revenue generation,” Gregory commented.

He added that the outcome of the modelling process were dependent on core objectives, but could cover outputs that included energy demand itemised by a demand centre; the effect of particular measures on energy demand by category or centre; an optimised implementation path of the measures over the time horizon of the analysis; technology and fuel mix by period over the time horizon; total emissions by period over the time horizon; and an integrated energy model.

“The energy modelling and planning plug-in has the depth to effectively mitigate against the level of guesswork used in making decisions. For example, it can drive a sustainable value-add and increase the certainty of project outcomes,” he said.

Deloitte further noted that, from an energy perspective, optimal project value was secured by evaluating the business case from an all-inclusive energy perspective, testing and validating assumptions, while also framing risks and modelling key drivers.

“For companies to increase their level of confidence in energy supply and energy demand improvement projects, a drive to all-inclusive energy models must be undertaken by the leadership teams of the respective companies involved,” Gregory averred.