Requirements on Dimensions for a Maturity Model for Smart Grids Based on Two Case Studies: Disciplined vs. Agile Approach

Requirements on Dimensions for a Maturity Model for Smart Grids Based on Two Case Studies: Disciplined vs. Agile Approach

Agnetha Flore (Oldenburger OFFIS, Germany) and Jorge Marx Goméz (Carl von Ossietzky Universität Oldenburg, Germany)
DOI: 10.4018/978-1-7998-4165-4.ch014
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Abstract

This contribution describes two different types of requirements engineering analysis of the necessary dimensions of a possible maturity model for Smart Grids to be implemented for utilities. For the first case study, the requirements engineering for necessary dimensions for a Smart Grid maturity model was elicited using a systematic literature research. On the contrary a more agile approach is used for the second requirements engineering. For this more agile approach, interviews with energy suppliers were conducted, taking into account the analysis of the literature research. Various energy suppliers from Germany took part in the survey. The results were used to develop the basic framework for a maturity model for Smart Grids, which can still be tailored if necessary. Finally, future research activities for the application and further development of maturity models for Smart Grids in the energy industry are explained as well as the different procedural variants in the requirements analysis.
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Introduction

At present, the issue of energy system transformation and climate targets is of crucial importance for politics and society. In order to be a successful utility in the future, it is important to move from a previously centrally controlled grid infrastructure to a decentralized, dominated structure. Only through a decentralized grid infrastructure is it possible to guarantee increasing feed-in from renewable energy into the grid (Appelrath, Mayer, & Rohjans, 2012).

This decentralization of the grid can be achieved through increased measurement, control and automation of the electricity flow, as well as regional high-resolution monitoring and control of the electricity grid. To achieve this, the electricity grid is to be modernized and made more intelligent through new information and communication technologies (ICT) (Projekt Green Access, 2019).

More and more research and development projects are dealing with the topics of the energy grid of the future, innovative technologies, the addition of storage facilities, etc. This shows that the subject is of great interest for practice and science.

In this contribution, a maturity model will be applied as an evaluation model for utilities. Through the use of evaluation models, the continuous improvement of a company is aimed at, whereby the focus is on comparison, i.e. “learning from the best” (Uebernickel, Stölzle, Lennerts, Lampe, & Hoffman, 2015). This maturity model should be specific to the energy domain in order to analyse the specific dimensions there. This analysis is necessary for a utility to know its status quo. Only when the status quo is known can the goal of making the own grid more modern and intelligent be pursued.

Due to the strong change in the energy domain that demands a high degree of change from utilities – in processes, procedures, methods and technologies – flexibility, adaptability, changeability and willingness to company-wide change processes play an increasingly important role.

A domain-specific maturity model has to be developed for two research projects in Germany, each of which uses different approaches and ideas to research and test new technological solutions for an intelligent power grid. Both case studies involve distribution system operators.

In this chapter we report on how the requirements for the dimensions of the maturity model to be developed were determined in these two research projects - case studies “utility 1” and “utility 2”.

Due to the increasing importance of agility in business, the approach of requirements elicitation will be conducted with two different methods: a disciplined and an agile approach.

The following research questions are to be answered:

  • RQ1: Is there already a suitable maturity model in the literature that can be used for this case studies?

  • RQ2: If a new maturity model is necessary, which dimensions of a utility have to be considered?

  • RQ3: Which approach is the better one for collecting the requirements for the dimensions, a disciplined or an agile one?

This contribution is structured as follows: The section “Introduction” briefly presents the motivation for dealing with the topic. Section “Background” represents the basic terminologies and section “Disciplined Maturity Models vs. agile Maturity Models” describes the differences between these kinds of maturity models. The research methodologies of the two case studies are presented in section “Research Methodology” and the results are presented and interpreted in section “Results”.

Based on the results, a maturity model for Smart Grids will be developed (section “Dimension for a European Smart Grid Maturity Model) and the chapter will be concluded with a summary in section “Conclusion” (Mehmann, Frehe, & Teuteberg, 2015).

Key Terms in this Chapter

Energy Sector: The energy sector is an umbrella term for companies that perform tasks in different economic sectors (such as the electricity or gas industries) for the provision of energy services. This includes various activities from extraction to transport to conversion into useful energy (heat, mechanical work, light, sound, etc.) for consumers.

Maturity Model: Maturity can be understood as an evolutionary process at the end of which there is evidence of a special ability or the fulfilment of a desired or normal target state. Therefore a maturity level model is a special competence model that defines different levels of maturity in order to be able to assess the extent to which a competence object fulfils a generally defined qualitative requirement for a class of competence objects.

User Story: From the user's perspective, the product owner formulates the requirements for a software product or a business solution (processes/methods) in user stories ( Schwaber & Sutherland, 2017 ).

Dimension: Dimensions include specific skills, process areas, and other design objects to structure an area of interest. Dimensions should be complete and well distinguishable. They are specified either by means of evaluation elements/measurement criteria (practices, objects, or activities) or qualitative descriptions.

Requirements Engineering: The term requirements management is used as a comprehensive term for all tasks in dealing with requirements and therefore includes requirements management and requirements engineering ( Schienmann, 2002 ; Leffingwell & Widrig, 1999 ). As a result, requirements management is understood on the one hand as a structured approach to the collection, organization, and documentation of requirements for a system. On the other hand, requirements management also includes the process of defining and ensuring the joint agreement of the customer and the project team regarding the changing requirements on the system.

Utility: A utility is responsible for the safe and reliable operation of the electrical grid in a given area and for connections to other grids. In this context, system services must be provided to ensure the reliability of supply.

Smart Grid: The term Smart Grid (also known as SmartGrid or Smart Grids [plural]) refers to the vision of an intelligent (electricity) grid. The various Smart Grid definitions are based on the integration of various generators, consumers and other systems and devices using IT to improve the control, management and monitoring of the grid ( Vázquez, 2012 ). The German “Bundesnetzagentur” says that conventional grids will become a Smart Grid if they are upgraded with communication, measurement, control and automation technology as well as IT components. According to the definition of the “Bundesnetzagentur”, a Smart Grid leads to better utilization of the existing grid, which dampens its expansion requirements or improves grid stability at the same capacity utilization.

Domain: In knowledge management, a domain is a specialist area, i.e. a subject area of content specialization. It can also be described as a field of knowledge.

Unbundling: Unbundling refers to the legal, organizational, and accounting separation of the functions of generation, transmission and distribution, trading and other activities of a utility in accordance with EnWG (2008) Part 2.

Requirements: According to the Institute of Electrical and Electronics Engineers - Glossary (1990), a requirement has two meanings. First, a condition or functionality that a user needs to solve a problem or achieve an objective. Second, a condition or functionality that an application system or application system components must address or fulfill in order to fulfill a contract, standard, specification or condition from other formal documents. For both cases, a documented description of the formulated conditions or functionality is required.

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