DSR approach to P2P for Efficient Energy Trading

Description

Design Canvas

Problem Problem What is the problem for which a DSR project aims to deliver a possible solution? Problems ought to be defined by means of problem articulations and characterized by positioning the problem in a problem space. Previous research has identified the context, described by the domain, the stakeholder, time and place, and goodness criteria. a) Low efficiency of electricity distribution on local level b) Complex electricity market entry	Research Process Research Process What are the essential activities planned (or conducted) to make the intended contribution? When the intended contribution is design entities, the process includes building and evaluating activities. These activities specifically include anchoring the design through the execution of tasks like literature reviews and meta-analyses. It is recommended that the construction and assessment activities be planned and documented together in order to facilitate concurrent design and evaluation. A high-level list of research activities used to scope the DSR project in the process dimension can be enhanced by logs of the research process that are kept using DSR tools. These actions for theorizing on the design may also be included in the process described. Activities for theorizing can draw from a variety of research methodologies and strategies of inquiry, including qualitative and quantitative empirical research, whereas activities for processing the design can draw from DSR process models like the Peffers et al model. Iterative activities for processing the design using DSRM (Peffers et al model)	Solution Solution What is the solution to the problem that a DSR project is investigating? The solution description identifies the representation of the solution as a construct, a model, a method, an instantiation, or a design theory and expresses concisely the fundamental mechanisms of the solution and how the solution is situated in the solution space. Mechanism for better integration of renewable energy
Input Knowledge Input Knowledge What previous knowledge will be used in the DSR design? Design knowledge can be either descriptive, explicatory, prophetic (omega knowledge) or prescriptive (delta knowledge). Three different types of input — kernel theories, design theories, and design entities — can be differentiated for high-level communication about DSR projects. Descriptive knowledge about the structure of peer-to-peer electricity markets	Concepts Concepts What are the core concepts that were utilized in the DSR project's research? The concepts used to describe the process and input and output knowledge, as well as the words used to characterize the study, such as the problem and solution space that the DSR project focuses on, must be described precisely. To ensure a rigorous execution of the evaluation activities, it is especially crucial to have a precise definition of the key concepts. a) Peer-to-peer energy trading b) Blockchain technology c) Electricity and flexibility markets	Output Knowledge Output Knowledge What kind of knowledge does the DSR project produce? Naturally, DSR projects generate design knowledge, which is referred to as omega knowledge. However, unlike the solution description, the design knowledge produced by the project puts the problem and solution spaces in relation to one another. If a DSR project's goal is to create design entities rather than design theory, the descriptions of such entities do not represent design knowledge because only the outcomes of the design entity's evaluation in context do. When the project is explained, these results are subsequently documented as output knowledge. Architecture: high level structure for electricity market

More information about the DSR grid

Problem identification and motivation

Lack of Transparency, Traceability, and Trust
Low Distribution Efficiency on Local Level
Solely Relying on Centralized Market Design:
- difficult market entry due to lack of credibility
- not resilient in case of shutdown

Objectives of a solution

Provide Transparency, Traceability, and Trust
Increased Distribution Efficiency on Local Level
Better Integration of Renewable Energy
Reduce Energy Waste in Transmission System
Increase Reliance on Non-centralized Market Design
Reduce Energy Cost of Consumers and Increase Revenue of Producers

Provide Transparency, Traceability, and Trust
Increased Distribution Efficiency on Local Level

Design and development

Literature Review (see P2P Papers: "Peer-to-peer energy trading: A review of the literature", "A smart contract-based p2p energy trading system with dynamic pricing on ethereum blockchain")
- Identify opportunities, limitations and gaps
Get an Overview of Existing Projects (see Table)
How?
- Contact relevant stakeholders, major distributors and Grid Operators to understand needs and requirements to specify functionalities
- Look for the construct to develop the architecture accordingly
- Instantiation:
  - Set up blockchain nodes simulating relevant stakeholders
  - Create a P2P local market with smart contracts platform

Literature review on P2P electricity trading: study architecture designs
Design adapted peer-to-peer local energy market
Implement a computer simulation (the agent-based model in Python)

energy trading projects.docx A_Smart_Contract-Based_P2P_Energy_Trading_System_w.pdf 1-s2.0-S0306261920316585-main.pdf

Demonstration

Proof of utility by running simulations with a blockchain-based architecture
- Simulate different scenarios <> Compare against real-world data
- Performance
- Data consistency
- Reliability and network stability in terms of energy and prices
Go to deployment in case of simulations are successful
- Pilot phase with several local markets

Proof of utility by running simulations with a blockchain-based architecture

Simulate different scenarios <> Compare against real-world data

Go to deployment in case of simulations are successful

Pilot phase with several local markets

Demonstration in the context of expert interviews

Evaluation

Measure efficiency gains in simulations and possibly deployment
Get feedback: scientific community (blockchain + energy), and business

Measure efficiency gains in simulations and possibly deployment
- KPI: Interdependence performance index (IPI)
- Reduction in overall costs of peer-to-peer market participants
- Importing less power from the main electricity grid
- Reduction of electricity costs by increasing installed renewable generation
Evaluation by experts (blockchain + energy), and business

Communication

Structure a paper and publish (conferences, social media, scientific community)
Communicate to stakeholders:
- Energy companies
- Potential P2P participants
- Small industrial producers/consumers of electrical energy

DSR approach to P2P for Efficient Energy Trading

ivan.abellan@uni.lu

Gabriela Maestri

Renan Lima Baima

pouria.arfaiee-torkambour@ids

ramin.bahmani@uni.lu

timothee.hornek@uni.lu

Description

Design Canvas

Problem

Problem

Research Process

Research Process

Solution

Solution

Input Knowledge

Input Knowledge

Concepts

Concepts

Output Knowledge

Output Knowledge

Problem identification and motivation

Objectives of a solution

Design and development

Demonstration

Evaluation

Communication