This paper will analyse Demand Side Management (DSM), an approach to include the demand side in the electricity system and consequently increase flexibility. The demand side should be regarded as a variable and not as fixed, as Gellings put it beautifully. With renewable energy, energy production becomes a variable source, and the demand has to adapt accordingly. The concept of DSM has been used in the USA since the 1980s but remains a novel subject in the European Union (EU). In 2009, the European Commission set the target to increase the capacities of DSM because only a tenth of the actual potential was used within the EU in 2014.
A significant obstacle regarding DSM is the deviating estimation of DSM Potentials. There exist multiple studies, which estimate the potential in Germany, but due to the high deviations that exist between them, making it is dicult to estimate the real potential. For investments, this is an important measure, and it should have high accuracy. These deviations potentially come from a missing definition for DSM, which is often entangled with Demand Response (DR), sector coupling and load management. As no clear definition or distinction to other terms is visible, it seems necessary to define the term DSM. For that, chapter 2 analyses the initial objective, modern approach and relative terms of DSM. Eventually, this leads to a more precise distinction, which helps to calculate the DSM potential from Germany with a broad analysis of multiple studies. These studies are typically based on different assumptions and were conducted in different years, therefore having different annual electricity consumption and consequently di↵erent potentials (Ladwig, 2018). A normalisation with regard to the annual electricity consumption will be performed and followed by a distinction of the assumed restrictions. Here, it helps to look at the DSM groups, which can implement DSM measures and point out their individual restrictions and challenges that would limit their potential or increase the complexity of integration. Scientific modelling helps to estimate the effects of novel approaches on the electricity system. As DSM has many interdependencies and is very decentralised through many individual participants, different approaches for a framework of DSM will be analysed.
Table of Contents
1 Fundamentals of the Electricity System
2 Definition of Demand Side Management
2.1 History
2.2 Modern Approach
2.2.1 Current Debates
2.2.2 Analysis of Demand Side Management Concepts & Activities
2.2.2.1 Demand Response
2.2.2.2 Strategic Energy Efficiency
2.2.2.3 Strategic Energy Conservation
2.2.2.4 Strategic Load Growth
2.2.3 Discussion and Result Analysis
2.3 Proposed Definition
3 Classification of Demand Side Management Potentials in Germany
3.1 Categorisation by Demand Side Management Groups
3.1.1 Industrial Processes
3.1.1.1 Normalisation of Impact Parameters
3.1.1.2 Restrictions for Industrial Processes
3.1.2 Commercial
3.1.3 Residential
3.2 Challenges of Implementation
3.3 Analysis of Potentials
4 Modeling Approaches
4.1 dsmlib - region4FLEX
4.1.1 Mathematical Framework
4.1.2 Methodology of dsmlib
4.1.3 Discussion of dsmlib
4.2 REMix
4.2.1 Methodology of REMix
4.2.2 Discussion of REMix
4.3 Conclusion of Modelling Approaches
5 Outlook
Research Objectives and Key Topics
This thesis examines the role of Demand Side Management (DSM) as a flexibility resource within the German electricity system, specifically addressing the challenges posed by the increasing integration of renewable energy sources. The primary goal is to establish a clear, universally applicable definition of DSM and to conduct a comparative analysis of existing studies that quantify DSM potentials in Germany, identifying the causes for wide discrepancies in technical and economic estimations.
- The historical development and theoretical foundations of DSM concepts.
- A critical review and standardisation of methodologies used to estimate DSM potentials in industrial, commercial, and residential sectors.
- Evaluation of barriers to DSM implementation, including regulatory and market-related constraints.
- Analysis of advanced modelling approaches for simulating DSM flexibility in regionalized energy systems.
- Normalisation of divergent study data to improve comparability of potential estimations.
Excerpt from the Book
3.1.1 Industrial Processes
Raw material industries are very energy-intensive with their material-converting processes. In 2018, they required over 50% of total industrial energy demand in Germany (Ausfelder et al., 2018). Therefore the highest leverage for flexibility within the industry. Here, for each sector, one process is selected and analysed to offer a view of potential setbacks within the industry. Most studies do this as it offers the benefit of looking at economical and practical constraints within the branch that are otherwise disregarded (Jetter et al., 2021; Ausfelder et al., 2018; Buber et al., 2013; Paulus and Borggrefe, 2011; Winter et al., 2011). Energy-intensive processes that could be found almost universally are steel, aluminium, cement, glass, chemical and paper production.
In steel production, the electric arc furnace offers flexibility potential. Through the electric arc furnace, one-third of steel is produced in Germany, while the rest is mainly produced through blast furnaces, which do not use electricity as a power source, and can consequently not be used for DSM (Ausfelder et al., 2018; Jetter et al., 2021). The process of the electric arc furnace starts with charging raw materials, scrap steel and iron, and melting them so they can be refined and slagged in the next step. After that, it is tapped into blocks or raw steel. Production output of the electric arc furnace cannot usually be increased as it operates on maximum capacity and is a batch process, which means that flexibility by increasing or decreasing production is not an option (Ausfelder et al., 2018; Buber et al., 2013). According to Jetter et al. (2021), the flexibility potential exists only by disrupting the production process and deactivating the system, relating to peak clipping; a production loss cannot be made up for. The disruption of the process can only happen in the melting phase, but even here, it can result in material contamination (Ausfelder et al., 2018).
Summary of Chapters
Fundamentals of the Electricity System: Provides an overview of the technical requirements for balancing electricity supply and demand, particularly under the influence of fluctuating renewable energy.
Definition of Demand Side Management: Traces the history of DSM and examines various theoretical approaches to establish a comprehensive definition capable of addressing modern flexibility needs.
Classification of Demand Side Management Potentials in Germany: Categorizes DSM potentials by sector and explores the underlying reasons for the high variance in existing estimation studies through data normalisation.
Modeling Approaches: Analyzes the mathematical frameworks of current modeling tools like dsmlib and REMix to understand how DSM techniques can be represented in grid simulations.
Outlook: Discusses the current state of DSM implementation in Germany, emphasizing the need for regulatory reform to incentivize participation from various consumer groups.
Keywords
Demand Side Management, DSM, Renewable Energy Sources, Flexibility, Demand Response, Energy Efficiency, Load Shifting, Industrial Processes, Germany, Potential Estimation, Energy System, Modeling, Grid Stability, Electricity Markets, Sector Coupling.
Frequently Asked Questions
What is the core focus of this thesis?
The thesis focuses on defining Demand Side Management (DSM) and classifying its potentials within the German electricity market, especially in the context of high renewable energy penetration.
What are the central themes discussed in this work?
The work covers theoretical definitions, the standardisation of potential estimation studies, classification of flexibility by sector, and computational modelling methods for DSM integration.
What is the primary goal of the author's research?
The primary goal is to reduce ambiguity in DSM definitions to allow for a better comparison of potential estimations and to provide a basis for more effective integration of DSM measures in the energy grid.
Which scientific methods are employed in this analysis?
The author uses literature review for comparative analysis, data normalisation techniques to handle discrepancies between different studies, and meta-analysis of existing dispatch modelling approaches.
What aspects of DSM are covered in the main body?
The main body examines industrial, commercial, and residential flexibility sources, discusses technical and economic constraints, and evaluates specific modelling frameworks such as dsmlib and REMix.
Which keywords best describe this research?
Key terms include Demand Side Management, Flexibility, Renewable Energy, Load Shifting, Potential Estimation, Grid Integration, and German Electricity System.
Why is a new definition of DSM necessary according to the author?
The author argues that a clear definition is essential because missing or conflicting definitions in existing studies lead to "deviating estimation of DSM Potentials" and complicate investment decisions.
How are industrial processes analyzed regarding DSM flexibility?
The author categorizes industrial processes by their specific technical capabilities, such as melting phases in steel production or cooling in the food industry, and assesses them against practical and economic constraints.
- Citar trabajo
- Lukas Schirren (Autor), 2022, A Classification of Demand Side Management Concepts. Their Potentials for a Renewable Energy System in Germany, Múnich, GRIN Verlag, https://www.grin.com/document/1342677
