For decision makers, the assessment of the number of jobs related to the development of the Ocean Energy sector is of utmost importance. This information would help to motivate governments, corporations and agencies to further support the sector by providing them with credible and unbiased information on the sensitive issue of job creation. Various roadmaps have advanced figures for the 2025, 2030 and even 2050 horizons, but in the time since, numerous Ocean Energy technologies have been designed and tested, and even implemented in pilot farms, and it is now time to assess an accurate total number of existing jobs directly related to the sector. It is also time to validate an approach to assess jobs creation in the sector and update projections for the 2030/2050 horizons.
An attempt to estimate job creation in OES member countries will then be based on a combination of both approaches exploiting finely tuned models based on the necessary preliminary field data collected from polling. Although all countries should feel involved in this study, it is pragmatic to involve only a few of them at the beginning of the process (e.g. comparison of field data and models), and namely those countries in which OE activities have begun to be significative through the implementation of several technology demonstrators and of the first pilot plants.
A direct added value stemming from the use of models in the present job creation assessment will be the increased credibility afforded extrapolations: job creation values at the 2030 and 2050 horizons will then be estimated using the validated modelling approach.
Under this project, a methodology and actual figures of job creations was developed.
Task 1: Preparation of a state of the art of the available models, assess their respective advantages and limitations, and especially designate the required input data that could differ from one country to another. A maximum of 2 better fitting models should be selected for implementation.
Task 2: Collection of field data (sometimes over a whole country, or restricted to a region by local economic development agencies, or spanning over a set of countries like the European Union). The model(s) selected in Task1 should be run in order to allow a thorough comparison between the individual outputs and to form conclusions on the minimum set of necessary field data. Work will also be directed at designing a methodology to restrict questionnaires to only a few questions and to target the most important respondents.
Task 3: Increase of the number of volunteering countries, the model would be fine-tuned and run on the basis of the necessary input parameters collected locally, thereby producing a global statistic. Extrapolations are also enabled by forecasting a portion of the model input parameters for the 2030 (#1 priority) and 2050 horizons, clearly explaining all economical hypotheses adopted in the modelling in order to produce such an extrapolation. Before running the model, the scenarios for deployment should be approved by the Executive Committee of the OES TCP. The model would then be run to produce future job creation counts at the global scale.
In 2019, a state of the art of socio-economic methodologies used to assess the number of jobs created or maintained with the commercial deployment of Ocean Energy Systems has been prepared. The identification of economic activities related to Ocean Energy Systems is complex. In addition to capturing the existing economic contribution of renewable energy activities, there is also interest in quantifying the future impacts. Projections or forecasts are widely undertaken and used to inform policy decisions, so their accuracy is important.
There are different approaches used in the calculation of projected impacts, and so it is critical to review existing approaches before producing further quantitative estimates. It should be noted that the methodology developed will provide a result which relies on the approach used. Different methods would be likely to provide alternative results, which is why it is important that the choice of method is the most robust, transparent for users, and that policymakers and analysts are jointly aware of its limitations. From this, decisions on ocean energy can be informed by the most robust evidence base.
