- This paper uses Social Network Analysis (SNA) to provide insight into the future of the Dutch Local Energy Market which utilizes blockchain technology.
- The influence of blockchain technology on the functions within an existing system can be significant, yet it is not likely to be as disruptive and decentralizing as the mass media suggests.
- Blockchain should be considered a technology that opens opportunities for all actors to reconsider their existing roles rather than a technology that threatens them.
How could the introduction of blockchain in the Dutch electricity system influence its actor configuration?
Buth, M. A., Wieczorek, A. A., & Verbong, G. G. (2019). The promise of peer-to-peer trading? The potential impact of blockchain on the actor configuration in the Dutch electricity system. Energy Research & Social Science, 53, 194-205. The promise of peer-to-peer trading? The potential impact of blockchain on the actor configuration in the Dutch electricity system - ScienceDirect
- Social Network Analysis (SNA): A method that investigates social structures via networks and graph theory. The paper uses social network analysis techniques to: (1) define the P2P Electricity Markets’ internal development status of innovation niches and (2) investigate how it evolves over time.
- Quantitative SNA: Big data-oriented analysis, often using simple SNA surveys with massive participants.
- Qualitative SNA: Conducting interviews to collect and analyze data.
- Local Energy Markets (LEM): Markets that enable consumers and prosumers to trade energy within their community, facilitate (near) real-time pricing and assist the process of a local balance of supply and demand.
- How does blockchain help Dutch Local Energy Market (LEM)? LEM requires advanced information and communication technology that facilitates local energy generation, trading, near real-time pricing, and balancing and provides a secure way to do so. Blockchain is a technology that promises to do all of this.
- This paper considers the potential of blockchain technology to empower distributed and decentralized local electricity markets. Through social network analysis, this paper compares the existing system with the potential actor’s configuration and the corresponding expected shifts in functions and network position of the actors.
- First, the authors of the paper define 13 actors in LEM based on a literature study.
- Then, the authors perform Quantitative and Qualitative SNA with 11 participants, who are managers or executives of LEM actors. During the Quantitative SNA survey, participants filled in two social network surveys where they were asked to attribute values to the degree of frequency of interaction with other actors in the network for the existing and the future electricity system.
- The qualitative SNA’s data was gathered and analyzed through network drawing exercises, where participants were required to draw lines representing the relationships between the actors on paper.
- After that, the authors analyzed the data, comparing several SNA metrics.
- Below are the actors and definitions from the Literature study find:
- Consumers: general energy users.
- Prosumers: consumers can produce some energy on their own and resell it to the market, like having a solar power panel.
- Electricity producers: generate power.
- Market Operators: sell the power to the grid.
- Transmission System Operator: maintaining the high-voltage grids.
- Distribution System Operator: maintaining the low-voltage grids.
- Balance Responsible Party/Trader: anticipate electricity usage of each party on the grid.
- Data facilitator: Sharing data between network parties.
- Metering company: Collect data and send it to the data facilitator.
- Aggregators: manage demand response and offer technical or economic services to electricity actors
- Charge Point Operators and Mobility Service Providers: electric car charger maintainers.
- Authoriteit Consument en Markt (ACM): supervise and regulate the market
- The paper’s authors chose a total of 11 participants from each of the actors above except Consumers and Prosumers.
- Quantitative SNA
The authors provided several metrics and pictures about the current and future networks.
Figure 1: The social network for current configurators. The thickness of the line represents the strength of the actors.
Figure 2: The social network for current configurators. The thickness of the line represents the strength of the actors.
Metrics comparison of current and future networks
Table 1: The SNA metrics for different actors in current and future SNA.
The authors also show the function change for each actor on current and future LEM network, and the function change for each actor on current and future LEM network.
Table 2: The function change for each actor in current and future LEM.
Actors in the existing electricity system and the potential evolution of the system in a blockchain-based electricity system.
- Figure 3: the involvement of the network. The more the middle, the more important the role is
- A new or existing actor would arise to be the blockchain operator overseeing the generation and optimization of the algorithms on the blockchain.
- Since there are many actors, the implementation of blockchain is likely to have a difficult time being translated to practices in the electricity system.
- The influence of blockchain technology on the functions within an existing system can be significant, yet it is not likely to be as disruptive and decentralizing as may be suggested in the mass media.
- Blockchain should be considered a technology that can open opportunities for all actors to reconsider their existing roles rather than a technology that threatens them.
- To perform a meaningful Social Network Analysis, one not only needs a detailed literature study to define the scope of the research but also needs to select domain-specific research participants.
- This paper is a stepping stone for the potential future of LEM in various ways, such as exploring the nature of the impact of blockchain technology under this context or the potential actor role setup. It is widely cited and has accumulated 38 citations within two years.
- The results of this paper also inspired other proposed energy management system models to understand peer-to-peer energy trading further or managing electricity grids with distributed assets.
- This paper performs an outstanding Market Potential Analysis via Social Network Analysis with only 11 research participants’ interviews. This is possible because the paper only considers the view of influential executives which is applicable to other industries so researchers can define the scope of their research.
- The research is a helpful guide for Blockchain researchers who want to do their own Market Potential Analysis. By interviewing key actors and using SNA, they can know the potential impact on relative stakeholders and know how to design their product to fit the need.