Operational expenditure costs for wave energy projects and impacts on financial returns

This paper examines 'availability' and the input metrics of operational expenditure (OPEX) for wave energy projects and reports on a case study which assesses the impact of these inputs on project profit returns. Case study simulations modelled a 75 MW wave energy project at two locations; the west coast of Ireland and the north coast of Portugal. Access and availability with respect to weather windows at both locations are discussed and their impact on energy output and wave farm operations is quantified. The input metrics used to calculate OPEX of wave energy projects are defined as well as the impact of OPEX on project net present value (NPV) and internal rate of return (IRR). Results indicate that access and resultant availability factors have a significant impact on case study results by reducing energy output and correspondingly financial returns. Furthermore, the technology maturity level designated for a project also impacts on availability factors and consequently energy output and NPV. Case study profits proved to be very sensitive to annual OPEX, especially if overhaul and replacement costs were accounted for. As a result of the impact of 'availability' on project profit returns. Feed-in tariffs will need to be tailored to the location in question as well as the device technology maturity level, with case study simulations indicating that high FIT will be required to support early stage WEC projects. (C) 2012 Elsevier Ltd. All rights reserved.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.