Big Data for Innovative and Sustainable Energy Solutions

Written by Ramon Gallart Fernandez and Chloé Coral

The BD4OPEM (BD4OPEM) project aims to design, develop and deploy a marketplace to provide innovative energy services for the reliable operation of the smart grid. These energy services will be provided through an open, modular data analysis toolbox and deployment of a generic data format for a data lake. In this project, the data coming from the diverse energy domain sources will be put at the disposal of advance energy service developers through the marketplace and, on the other hand, new services will be offered through the marketplace to the different energy actors. The architecture of BD4OPEM is based on the Smart Grid Architectural Model (SGAM), a reference for development, model and tools for Smart Grid Information Security, created by the Smart Grid - Coordination Group (SG-CG)¹. [1].

SGAM Architecture

The SGAM architecture provides the structured way for the requirement engineering by defining a framework for designing the use cases in the solution and technology-neutral manner. To aid the clear presentation and simple handling, SGAM architecture is presented into three dimensions: domain, zone and interoperability layers.

Domain: Dimension divided in five segments, namely generation, transmission, distribution, distributed energy resources (DER) and Customer premises.

Zones: Divided into process, field, station, operation, enterprise, and market segments. In addition, five abstract interoperability layers are defined: Business layer, function layer, information layer, communication layer and component layer.

Business: It is a layer that represents the business view on the information to design business models, market structures, etc. The functions and services are specified in the function layer. Information and communication layers represent the data model and communication technology, respectively. The component layer describes the hardware, humans or systems that take part in the overall system design.

The SGAM architecture helps different stakeholders to have a common and unified perception of smart grid. It will assist the experts in the detection of missing use case description, by mapping each individual use case to the different interoperability layers. An empty layer in the mapping process will corresponds to the missing use case description.

Use Cases Architectural Scope

The challenge is to capture requirements of the system designed to be described without a pressure of intended architecture and services design which will follow the use cases, but the use cases should not be captured in an architectural void. The first architectural scope has been defined by adopting SGAM, and additional information is based on an architectural sketch from the project proposal as shown in the following Figure 1.

Figure 1 IT Architecture (compliant with SGAM)

 

The project sketch extends the SGAM with the project foreseen components and their relations. The architecture is divided in three layers, namely data, analytics, and market layer. The data layer maps to component, communication, and information layer of the SGAM architecture as denoted on the left side of the figure. The analytics layer maps to functions layer and marketplace layer to business layer.

The architecture includes the main interfaces of the system, between data sources and data storage, data storage and analytics layer, analytics layer and marketplace, marketplace and end users, and in vertical direction between security and privacy services and the rest of the system.

From the use cases point of view, it is important to capture functionality from all denoted segments and in relation to initially indicated components. Not covered component or layer indicates either a need for additional use case or excessiveness of the component in initial design. Use cases not fitting into the scope clearly could indicate either too narrow scope of the initial architecture or a use case outside its scope. The use cases should be focused on a single segment and its neighboring segments bearing in mind that the functionality of these segments will be accessed through an indicated API. Inability to limit the use case to a segment could indicate that the use case is too general and should be split in multiple use cases. The security and privacy segment are common to all other segments and the use cases in this scope should be defined in a way to fit all the other segments, if possible. [2]

Concepts

The project aims at bridging between data providers and data analysts to enable the provision of novel services in the energy domain. This bridge will enable a data flow needed for the application of big data technologies in the energy sector and the development of energy services market with new opportunities for all stakeholders.

An analytics toolbox bridges between the data provider and the data analyst. The project will support several data providers and sources of data. The toolbox contains everything needed for an energy services marketplace boost: the data lake as the data bridge, the marketplace as service provisioning facilitator and open innovation mechanisms based on either confidential or open data.

The marketplace services and toolbox will be tested and evaluated in the project pilot environment. Both the data provider and analytic services are tightly related to the pilot users and in the future potential marketplace customer. An important part of project work is focused on the marketplace energy services, which heavily influences the use cases.

Energy Services

In order to test the Marketplace concept, various technologies and services have been identified to provide diverse technologies and services that serve DSO² and other energy sector stakeholders for a better management of their networks.

These services will extract more value from the available data providing new big data solutions for the operation, planning and maintenance of highly complex networks, including services like grid topology identification, observability, predictive maintenance, fraud detection, houses, buildings and industries energy management, blockchain transactions and flexibility aggregation for demand-response.

The services that will be covered are:

Operation & Maintenance: Topology, observability, predictive maintenance in electrical power systems, measurement errors detection, impact study PV, EV & new loads and Grid disturbance simulations.

Fraud Detection: Inconsistences in energy balance and power-voltage and fraud patterns detection.

Flexibility and Demand Response: Flexibility forecast, flexibility aggregated services for BRP³ , flexibility aggregated services for DSO and EV to grid.

Smart Houses, Buildings, and Industries: Energy management at household or at community level and energy forecasting.

Trading: P2P trading.

Planning: Asset and investment planning and asset estimation optimization for microgrids.

Monitoring: Grid KPI.

BD4OPEM Project, has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 872525. The information contained in this article reflects only the authors’ view. EC is not responsible for any use that may be made of this information.

 

References

1. CEN-CENELEC-ETSI Smart Grid Coordination Group . SG-CG/ M490/F_ Overview of SG-CG Methodologies. Version 3.0. 2014.
2. Gabrijelčič, D., Kaur, R. (2020/06/30). Concept design and use cases. Big Data for OPen innovation Energy Marketplace.

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Annotations

¹ See standardization mandates at European Commission web page on European standards: https://ec.europa.eu/growth/tools-databases/mandates/index.cfm?fuseaction=search.detail&id=475
² Distribution System Operator
³ Balance Responsible Party

 

This article edited by Mehdi Moghadasi

For a downloadable copy of the May 2021 eNewsletter which includes this article, please visit the IEEE Smart Grid Resource Center.