5.2. Models

The models' layer integrates previously described methods for determine the consumers' profiles based on SOM, methods for short-term consumption forecasting based on autoregressive neural networks and in case of prosumers, short-term generation forecasting from small wind turbines and PV panels. Also the layer includes an optimization model based on two optimization functions as described in detailed in Ref. [35].

### 5.3. Interfaces

5. Informatics solutions for electricity consumption and generation

demand management must fulfill the following requirements: • describing and modeling consumer's electrical appliances;

• monitor and forecast generation in case of prosumers;

• offering advanced analysis for consumption and micro-generation and

• monitoring the costs of electricity consumption according to advanced tariffs systems.

Our proposed informatics solution is part of a research project and it is addressed mainly to household consumers, but it also contains a management consumption module for electricity supplier. The informatics solution contains the following modules: data acquisition from smart metering and smart appliances, models for consumption management and

Data acquisition module extract data from heterogeneous sources such as smart meters and appliances in .csv or .raw format, micro-generation equipment (small photovoltaic panels, wind turbines and electrical vehicles), manual reading done by electricity supplier' employees or via web interfaces. Data are loaded first into local databases (concentrators) via Wi-Fi or RF. From local concentrators, data are synchronized periodically and loaded into a central data stage for proper cleansing and validation. We also designed an extract, transform and load (ETL) patterns for different types of SM and also procedures for extracting data from heterogeneous appliances. After ETL process completes, data are loaded into a central relational database running Oracle Database 12c or MySQL for operational management and then into a data

The models' layer integrates previously described methods for determine the consumers' profiles based on SOM, methods for short-term consumption forecasting based on autoregressive neural networks and in case of prosumers, short-term generation forecasting from small wind turbines and PV panels. Also the layer includes an optimization model based on two optimi-

• real time consumption monitoring;

134 Advanced Applications for Artificial Neural Networks

• scheduling electrical appliances;

• optimizing the consumption;

user-friendly interfaces.

5.1. Data management

warehouse for advanced analytics.

zation functions as described in detailed in Ref. [35].

5.2. Models

In order to increase the consumer awareness toward energy efficiency, new informatics solutions must be developed and offered by the electricity supplier. An informatics solution for Our proposed solutions are integrated into a web-based application using business intelligence components that allow both electricity supplier and prosumers to interact with the proposed models. We set up a business intelligence server installed in a cloud computing using Software as a Service (SaaS) that offers access for prosumers/electricity supplier to services via internet connection for advanced analytics. The application includes the following consumers' facilities (Figure 8):


For electricity suppliers, the application will include an advanced analytics interface (Figure 9) that allow them to:


The informatics solution is developed on a scalable platform, using Java with Application Development Framework and Oracle Database 12c that enables Cloud management and services. Thus, the solution can be adopted by the energy suppliers without expensive investments in infrastructure. Also, it offers an user-friendly interfaces that can be easily understand and managed by end-users on personal computers and mobile devices.

Figure 8. Monitoring consumption and generation in case of prosumers.

Figure 9. Determine consumers' profiles through web interfaces in case of electricity suppliers.
