## 6 Open Source Smart Grid Solutions  
As we stated previously in this work, ICT and advanced software technologies are key enablers for the smart grid paradigm. Open Source smart grid software would present many advantages in terms of interoperability, initial investments and technological development. For this reason, we decided to dedicate this section of our work to review the open source software solutions for smart grid management, available at the time of writing this article. A first example is provided by [PERSON] _et al_. [52]. In their work, they propose a distributed automation system for controlling electrical power systems with DG, using a framework of open source software and standards. More in detail, their system is based on:  
Figure 15: GA with varying penalties added: average progress of the best chromosome’s quality over 20 runs [50]. * IEC 61499 [53]: Open Standard for Distributed Control, it provides a standard methodology to distribute control applications through different devices, thanks to a modular approach based on \"Function Blocks\";
* IEC 61850 [54]: Open Standard for Power System Automation, it defines an information model for power utility systems, and also the different communication services available between compliant devices;  
The aim of the work is to prove the interoperability between these two standards and the following open source software applications:  
* 4 DIAC Framework for Distributed Industrial Automation and Control [55]: an open 61499-compliant framework, which can be considered a reference implementation of the standard. It provides a runtime environment for embedded devices and a modelling IDE for engineering purposes;
* GNU Octave [56]: an open source computational environment, compatible with MATLAB(r). * PSAT (Power Systems Analysis Toolbox): a MATLAB(r)-Octave toolbox, developed for the analysis of electric power systems. It provides several features like power flow analysis and computation, time domain simulations and support for DG. In Figure 16 an architectural view of the complete solution is given. As we stated several times throughout this work, one of the key aspects for smart grid implementation is data management, in terms of acquisition (metering), storage, and analysis. In this sense, a relevant solution has been presented by [PERSON] and [PERSON] [57] where they introduce WattDepot, an open source framework for energy data collection, storage, and visualization. WattDepot consists of three kinds of services: software _sensors_, which retrieve power consumption/generation data from different  
Figure 16: Power Systems Simulator on PC-based and Controller Execution on Embedded Hardware [52]. classes of devices, _servers_, which collect data from sensors, store them in a relational database and provide them publicly through RESTful APIs, and _clients_, which either present data to the final user using different visualization techniques or provide input data for analysis tools. In Figure 17 the architecture of WattDepot is presented. The system provides device independence at server level, although software sensors must be specifically developed for a particular power meter. Actually only a few brands of meters are supported. One of the most interesting features of this system is the decoupling of data from particular representations, a benefit deriving from the RESTful approach. Servers may provide power data in different formats (currently JSON, XML, CSV) through simple Web Service technologies. Servers also perform an interpolation of time series data, because there is no guaranteed matching between the timestamps of data provided by the different sensors. An open issue regards data privacy. The system has indeed a very simple privacy model, based on a common username/password system with only two levels of access (public/private). This issue has been addressed by authors as one of the future development directions for the work. In Section 5 we introduced software agents as a suitable technology for smart grid systems.