Econometric Forecasting
Solar energy production in the USA Econometric forecasting and analysis for photovoltaic hardware failure rates Word count 1000-1100 plus SPSS graphs(provided) Method: Survival Analysis in order to forecast the time to failure of PV components, region USA 1) Introduction Introduction to the report project and identification what the data is aiming to illustrate investigating hardware?related problems such as modules, inverters, and other BOS components. Using the knowledge from the survival analysis, one would be ultimately able to reduce the risk of interrupted energy production (data used for and aim to illustrate outcome). Key notion: Reliability plays a central role in PV being cost competitive with traditional energy sources; therefore, it is important to rapidly assess whether any quality deficits exist in the equipment or installation practices, in order to enable timely continuous improvement Support work with academic texts. (!!!) Target market USA (!!!) 2) Methodology Overview/explaining survival analysis why better suited than other techniques for time series analysis What does survival analysis provide in terms of outputs? Discuss survival time/ time to failure of solar equipment This needs to be quite detailed so ensure that all aspects of the model are c0vered, such as strengths/ weaknesses/ effectiveness etc. Support work with academic texts. (!!!) 3) Illustration Survival Analysis using SPSS data (provided) with explanation and analysis a) illustrate numerical analysis b) explain and analyse outputs appropriately given the provided SPSS data and graph, explain what the graph is showing and be analytical in the discussion c) Support work with academic texts. 4) Prediction of the future trends/ Conclusion Utilise above SPSS data & graph to ultimately forecast future trends for solar component reliability in line with what is illustrated The forecast should enable to estimate how often solar equipment will need replacement to ensure continued energy production.
