Service-Oriented Architecture based Cloud Computing Framework For Renewable Energy Forecasting

Abstract

Forecasting has its application in various domains as the decision-makers are provided with a more predictable and reliable estimate of events that are yet to occur. Typically, a user would invest in licensed software or subscribe to a monthly or yearly plan in order to make such forecasts. The framework presented here differs from conventional software in forecasting, as it allows any interested party to use the proposed services on a pay-per-use basis so that they can avoid investing heavily in the required infrastructure. The Framework-as-a-Service (FaaS) presented here uses Windows Communication Foundation (WCF) to implement Service-Oriented Architecture (SOA). For forecasting, collection of data, its analysis and forecasting responsibilities lies with users, who have to put together other tools or software in order to produce a forecast. FaaS offers each of these responsibilities as a service, namely, External Data Collection Framework (EDCF), Internal Data Retrieval Framework (IDRF) and Forecast Generation Framework (FGF). FaaS Controller, being a composite service based on the above three, is responsible for coordinating activities between them. These services are accessible through Economic Endpoint (EE) or Technical Endpoint (TE) that can be used by a remote client in order to obtain cost or perform a forecast, respectively. The use of Cloud Computing makes these services available over the network to be used as software to forecast energy for solar or wind resources. These services can also be used as a platform to create new services by merging existing functionality with new service features for forecasting. Eventually, this can lead to faster development of newer services where a user can choose which services to use and pay for, presenting the use of FaaS as Platform-as-a-Service (PaaS) in forecasting.