Energy Storage and Transport

Designed by Clemens Verhoosel and Elisa Bergkamp in The Brainport

Welcome to the challenge-based learning project Energy Storage and Transport! This project is part of the Mechanical Engineering program at Eindhoven University of Technology. Here you will find all information needed for the project.

Introduction

The energy transition: an engineering challenge

Realizing a more sustainable future with affordable and clean energy is one of the biggest societal challenges we face today. The process of making our energy system sustainable is referred to as the energy transition. Technological innovations across a wide range of disciplines are required to realize this transition.

The energy transition poses tremendous challenges for engineers, both from a technological perspective and from the vantage point of sustainability. As an engineer of the future, you will likely be developing technology that contributes to the energy transition. While you do this, you are expected to take into consideration the effects that this technology has on our lives.

A major technological challenge in the energy transition is to accommodate our energy system to deal with the more fluctuating nature of green energy sources compared to conventional (fossil fuel based) energy sources. Where conventional energy production can be controlled reliably, renewable energy production depends on external factors over which we have limited control. In the current energy system, where a substantial part of the energy still comes from fossil fuels, the fluctuations in renewable energy production are leveled out by conventional energy production. With the share of renewable energy production increasing substantially in the years to come, the development of technology to deal with its fluctuations is necessary.

In the western world, energy exchange markets (for example EPEX SPOT in the Netherlands) regulate the supply and demand of energy. To improve the competitiveness of green energy production, it is essential to make them less dependent on balancing by conventional energy sources. The ability to efficiently store green energy in situations when there is a surplus of production (for example, at night) and to deliver this stored energy when there is a surplus of demand (for example, during the day), is key to reducing the need for balancing. Currently, the storage capacity on the energy grid is limited, especially in countries without natural hydroelectric dams (such as the Netherlands). The development of innovative energy storage and transport technologies is essential to make green energy competitive, and, thereby, to enable the energy transition.

Challenge-based learning

Energy Storage and Transport is a challenge-based learning (CBL) project, set in the context of the energy transition:

Project goals

The overarching goal of this project is defined as:

In the process of accomplishing this overarching objective, the following learning goals will be achieved:

Assessment procedure

The table below summarizes all assessment components. Click on the assessment links to see details such as submission dates, templates, rubrics, etc.

Please note the following:

• The rubrics for the Go/No-go pitch, the poster, the standard operating procedure and the technical report will be evaluated purely based on the submitted product. Submitting a deliverable is a group responsibility. This includes reviewing a deliverable together and checking whether it is submitted properly.
• During the project, you will practice your presentation skills. Your tutor will evaluate this based on the rubric available here.

Learning activities

The table below presents an overview of all mandatory and scheduled project activities. Make sure to check the dates and locations with your official TU/e timetable and report discrepancies to your tutor or coach.

Mandatory trainings

To complete this project, you must complete the following trainings:

Information skills training

In the compulsory Finding and processing of (scientific) information training, you will get acquainted with scientific databases and you will learn how to create an efficient search process by formulating effective search queries in which relevant and alternative search terms are combined by using operators. Once you have found results, you will learn how to evaluate whether those results are relevant to your research. You will also understand what it means to conduct research with 'scientific integrity'.

This is a blended training for which you will have to attend an on-campus training and complete online modules and assignments. The assignments will be carried out by your project group. Instructions about the assignments will be provided during the on-campus training. The course will be graded as "good/pass/fail" and it is required to obtain at least a "pass" for this professional skill to complete 4CBLA30. In case of an unsatisfactory grade (a fail), the training needs to be re-taken.

N.B.: Attendance of this training is mandatory. Bring a fully charged laptop and earphones to the live session!
N.B.: For details about this training, see the Information Skills Canvas page.

Social safety training

In the Social Safety and Inclusive Collaboration training you will be introduced to the topic of social safety in education. This compulsory session will be organized in the form of a theatre play by the TIME OUT Foundation, called SAFE SPACE. The play is especially designed for students at their request. The play will cover the topic of transgressive behavior, sexual intimidation and power abuse. When do we call something transgressive? Who decides on that? And where do we encounter such behavior?

N.B.: Attendance of this training is mandatory. Please bring your campus card for identification.

Measurement training

This training focuses on the application of hardware and software during experiments. Students can complete the mandatory practical part of this training during the scheduled hours in the PROTO/zone Hallway, where practical equipment is available. The theory assignment part of the training can be completed online. Detailed instructions and due dates are available on the Canvas page (practical, theory assignment).

Mandatory project meetings

Team meetings with coach

The team meetings in PROTO/zone are the moment to work together on your project as a team and to consult your teacher coach for advise. The team meetings are also the moment to work on your setup and to conduct the measurements. During the team meeting, your teacher coach will visit your group to provide feedback on the deliverables.

Tutor meetings

The tutor meeting is the place to discuss the organization of your project. As part of this discussion, your team discusses the progress on open action points, the planning (and possible adjustments thereof), the definition of new action points, the distribution of tasks, etc. In this discussion there should also be attention for individual learning goals. A standard agenda for these meetings is provided below:

Your tutor will systematically monitor and document the performance of the group and its members (the role of the tutor is detailed here). It is the joint responsibility of the tutor and the team to ensure that the tutor is well informed. In week 4, one of the tutor meetings will be dedicated to the midterm evaluation. The final assessment meeting is also completely dedicated to the evaluation.

Rules and responsibilities

Attendance rules

In CBL all group members are equally responsible for the project outcome. Therefore, it is required that each student attends all meetings connected to the project, i.e.: all group meetings, all project supporting lectures, training courses, building sessions, student meetings, etc. Absence is only excused when it concerns an acceptable reason, to be determined by the CBL coordinator. Requests for excused absence have to be submitted in advance to the CBL coordinator, by e-mail (see contact details) with subject 4CBLA30 - Group number - Student ID. The student will be notified whether the request has been approved as soon as possible. Attention: Arriving late to a group meeting and online attendance is also considered a no-show.

PROTO/zone

You can work in PROTO/zone (Traverse) during the hours scheduled for your group. Before entering PROTO/zone, please read the safety rules. If you don't follow the safety rules, the staff will (kindly) oblige you to leave. At the end of a session, you must tidy up your own workbench and bring back the tools you borrowed. When you leave without tidying up, you'll get a warning. After 2 warnings the staff will (kindly) oblige you to leave PROTO/zone.

Every group gets a storage box and locker in PROTO/zone (Traverse) in which assembled components can be stored in between meetings. You will receive your locker key at the first meeting in PROTO/zone. At the end of the final PROTO/zone session (week 8) you must hand in your storage box and the key to the locker. For a lost key €10 will be charged.

The available components cannot be modified irreversibly. If a component malfunctions, please report this to the teachers.

Use of internet tools and referencing

Internet tools can broadly be divided in Large Language Models (ChatGPT, Gemini, Copilot, etc.) and Information tools (search engines, online databases, etc.). Such tools may provide a wealth of information to enhance design and/or research activities, especially in exploration and comparative phases. Therefore, you are encouraged to use these internet tools to enhance your learning process. However, such tools should never be used to generate content (text, source code or images) and it should be unambiguously clear to what extent such tools aided in the conception of new ideas. Moreover, you should always be critical about the quality of your information sources and make sure to properly reference them.

To address concerns regarding potential misuse of internet tools. It is essential that you adhere to the following guidelines¹:

1. Provide precise references for the parts of your work where internet tools are used.
2. Provide an explanation for why you opted to use specific tools and evaluate their usefulness.
3. Do not use Large Language Models to generate report text, source code or images.

Examples for proper use of external source material are given below. When in doubt, always contact the responsible lecturer or project coach for consultation:

1. Compulsory when using Large Language Models
   • ChatGPT was used to optimize a Matlab script: In the main text of your report clearly indicate when and how you used ChatGPT for this purpose, for example: “The Matlab script has been optimized using ChatGPT as explained in Appendix #”. In the appendix you should then explain the prompts used to obtain the optimized code.
   • ChatGPT was used to improve the writing style of the introduction: Clearly indicate which sections were improved using ChatGPT. This may be done by adding a footnote: “The text in the introduction has been improved using ChatGPT using the prompt: “Hi ChatGPT, I have written this paragraph: [included in Appendix #], can you please make it more formal?””. This means that the original text must be included in the appendix, where also a reflection on the usefulness of the ChatGPT-based improvement should be provided.
2. Compulsory when using internet sources
   • You can use common referencing methods or footnotes for the use of internet sources and information encyclopedia tools (e.g., Wikipedia), for example through their URL. However, since these tools are volatile, always indicate the date on which you consulted them. This volatility also indicates the added value of trying to find references in books and/or academic journals instead.
3. Recommended when using information tools to explore internet databases
   • Bing was used to explore benchmarks: In the relevant part of the report, add a footnote indicating its usage: “This benchmark analysis was performed using “Bing” with keywords “keyword 1, keyword2, etc.”, after which the first 20 results were selected for further analysis.”.
   • Google scholar was used to find articles to be included in a literature survey: Indicate the usage of the tool In the report: “For this literature survey “Google scholar” was used with keywords “keyword 1, keyword 2, etc.“, after which the 15 most cited papers were selected”.

¹ These guidelines have been carefully formulated with all the necessary information. Should differences occur between these guidelines and the rules and regulations as given in the Program and Examination Regulations (PER) and/or the Examination Regulations (ER), the PER/ER are always leading.

Project tracks

The overarching project goal is to propose an Energy Storage and Transport (EST) system based on a validated model. The proposed EST system should be designed for your team's supply and demand:

The project is organized in four parallel, interconnected, tracks:

Track 1: Defining your EST system

The starting point for defining your EST system is to analyze your team's energy supply and demand, for which you can make use of the provided baseline Simulink model. In this analysis you will quantify energy surpluses and deficits, identifying the relevant time and volume scales, that is: How much energy do you need to store and for what periods? Typically, multiple time and volume scales can be identified. Developing an EST system that is able to completely cover all scales is unrealistic. For example, an EST system for a daily storage cycle will not be effective for seasonal storage. Therefore, an EST system is typically designed for one of the relevant scales and not for all. Although such an EST system will not cover all deficits, it may still be very effective if it covers a substantial part of the deficits.

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First prize in the 2023 infographic competition.

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Second prize in the 2023 infographic competition.

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Third prize in the 2023 infographic competition.

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Fourth prize in the 2023 infographic competition.

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Fifth prize (ex aequo) in the 2023 infographic competition.

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Fifth prize (ex aequo) in the 2023 infographic competition.

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Fifth prize (ex aequo) in the 2023 infographic competition.

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Based on the requirements derived from the analysis of the supply and demand, your group will define an EST system in the real-world setting. All essential components of the EST system should be defined, with a clear notion of the size of the system and the time scales of the storage process. You should also think about how storage bypass (direct delivery without intermediate storage) and load balancing (nullifying the mismatch between the energy supply/demand and the energy injected by/extracted from the storage) work in your system. As part of the definition of your EST system you will identify the system parameters that are essential to its performance. These essential system parameters should relate directly to the physical properties (e.g., dimensions, material properties) of the EST system. Through the specification of the values of all system parameters, your group will define a reference EST system.

With the system fully specified, your group will use the developed model to assess the performance of your EST system. Throughout the project the capabilities of the model will be increased, resulting in detailed simulation results for a reference setting. Your group should think about which quantities/graphs are needed - in addition to the standard results generated by the baseline model - to assess the performance of the EST system. You will then perform a model-based design-variation study, demonstrating how variations to the reference setting of the system will alter its performance. Based on this design-variation study you will draw conclusions regarding how the system can be altered to optimize its performance.

Track 2: Developing your EST model

The development of a model is a key aspect of your project. It is therefore important to clarify the terminology related to modeling. The interactive modeling chart below defines the most prominent modeling concepts and the relations between them.

Your computer model will be developed in Simulink, based on the baseline implementation available on Github:

The provided baseline implementation models the flow of energy between the different components for an abstract EST system. In this abstract system, the components are modeled using simplified models (see documentation). These simplified models are parametrized by effective properties, meaning that the model parameters represent the overall behavior of the components (black box efficiencies) and do not represent their physical attributes (dimensions, materials, etc.). Since it is not clear how to find the effective properties for your team's EST system, the applicability of the baseline implementation for studying (the design of) your team's EST system is limited. To make the computer model applicable to your EST system, the simplified models must be replaced by appropriately selected mathematical models describing the physics of your EST system. In contrast to the baseline implementation, the model developed by your team will be parametrized by physical attributes of your EST system (dimensions, materials, etc.). This will empower the model with capabilities to predict the performance of your EST system and to study design variations.

• Modeling objective: The first step is to define the goal of the model, that is: What quantities of interest should the model be able to predict and with what accuracy? The provided baseline Simulink model can be used to develop intuition. When you load your team's supply and demand signals into the Simulink model and estimate the effective properties in the baseline implementation for your EST concept, you can use it to get a first impression of the performance of your EST system and of the capabilities and limitations of the baseline computer model. Typically, the standard output of the baseline implementation should be tailored and extended depending on your team's scenario.
• Physical phenomena: The second step is to identify the physical phenomena in your EST system. Since you model the time-dependent flow of energy in your EST system, you should ask the question: What are the physical mechanisms involved in storing the energy, and what physical phenomena cause the major losses? It is important not to leave out essential physical phenomena, but also not to include aspects that are irrelevant (or too detailed) given the goal of your model. When you identify relevant physical phenomena, you should also think about which physical attributes of of your EST system have a profound effect on them, as these attributes should become parameters of your model.
• Model selection: The third step is to select which physical phenomena you want to include in your model, deciding on which simplification can be made. You should find mathematical-physical relations that can describe the selected phenomena depending on the physical attributes of your EST system. You should understand the assumptions behind these relations, as these are essential to answering the question: Given the purpose of the model, can the selected mathematical-physical relations describe the relevant physical phenomena with sufficient accuracy and are they sensitive to the physical attributes of the system? It is important that the selected mathematical-physical relations are not unnecessarily complex ("Everything should be made as simple as possible, but no simpler."). At this point you should have a thorough understanding of the Simulink model (see documentation), as you need to assess whether a mathematical-physical relation is suitable for implementation.
• Mathematical elaboration: The fourth step is to elaborate the mathematical models for all system components. Typically, the selected mathematical relations do not seamlessly fit in the energy flow structure of the Simulink model. The inputs and outputs of the energy flow models of the components (the blocks in Simulink) are specified in terms of powers (rates of energy). Often, this is not immediately the case for the mathematical relations describing the phenomena and hence these require reformulation. It is also common that multiple mathematical relations for physical phenomena are combined into the model for one of the components. For example, a component may be subject to multiple significant energy losses, each requiring its own mathematical relation. Also, additional relations may be required to connect the parameters of the mathematical relations to the physical attributes of your EST system. In summary, the key question in this step is: Are the mathematical models for all components compatible with the energy flow structure of the Simulink computer model? An important part of this step is to elaborate the energy flow diagrams for each of the components. Such diagrams aid in the formulation of well-posed formulations, without the need for a detailed and fundamental mathematical understanding.
• Implementation: The fifth step is to implement the mathematical models in Simulink. The implementation can have different levels of complexity: (1) In its easiest form, the effective properties in the custom MATLAB blocks can be expressed in terms of the physical attributes of your EST system; (2) When this is not possible, the mathematical model for a component should be implemented in a custom MATLAB block; (3) It may be required to make changes to the flow structure in the Simulink model, that is, to create additional connections between the blocks, or even to create new blocks. For each component you should keep the implementation as simple as possible, but not any simpler.
  
  You will realized that, even if you worked out the model very well, coding forces you to think about the nitty gritty details, as otherwise the computer model will be buggy. It is therefore important to follow good programming practices, such as code (unit) testing, documentation and version management. If you run into a bug - and you will - you should systematically debug the code. A very important aspect of this is that you make gradual changes to your code, making sure that it keeps on working after every change made. When you make a change that leads to a bug, you should revert to the version that worked and then step-by-step re-introduce the changes. In the process of doing so, you should discover what caused the bug, from which the resolution to the problem will typically become apparent. Debugging the code is an important part of the learning process and the responsibility of your team. The teachers can give you general tips for debugging, like "step-by-step modifications", but will not help with the detailed debugging process. When debugging code, you will realize that the smaller the bug is, the harder it is to find. Although this may be frustrating at points, you should realize that when the bugs get smaller you are moving closer to obtaining a bug-free code.
• Validation & Verification: When developing a computer model, the key question is: Can the computer model predict the quantities of interest of the real-world system? For a computer model, this question can be split up in two parts. The first part is to consider whether the selected mathematical-physical relations are capable of describing reality with sufficient detail, which is called validation. The second part is to consider whether the computer model solves the mathematical-physical relations correctly, which is called verification. Both validation and verification are essential when developing a computer model and should be considered throughout the model development process.
• Reflection: The final step in the model cycle is to reflect on the question: Does the developed model meet the intended objective? In this reflection you will identify the uses and limitations of the developed model. You will also specify directions for improvement.

To help you in getting a better understanding of the model development cycle, we have elaborated a transmission line model as an example. We encourage you to study this example to understand the steps to be taken. You are allowed to use the model in this example, but you will not be graded on it. That is, you must develop your own model for a different component and report on that in the deliverables .

Track 3: Validating the EST model

Testing a complex system - such as your real-world EST system - and validating a model for it is a challenging endeavor, especially when that system still needs to be developed. Simply building the complete system for testing is not possible until its detailed design is complete. That is, only in the phase just before taking such a system in production, performing full scale tests is possible. And even then the number of tests that can be done is limited because of the costs involved. So, if you cannot test the full system during the development process, how do you test your system and how do you validate your model? Instead of testing the system in full, you can perform a testing and validation procedure composed of a large number of smaller scale tests, which together form a testing or validation pyramid:

In the development process of a complex system you will build the testing and validation pyramid from the bottom up. The higher you get in the pyramid, the closer you get to testing the system in full. In fact, the full-scale test is at the top of the pyramid. At this level of testing, the width of the pyramid is very narrow, indicating that only a limited number of tests is performed. The level below the full-scale tests considers the subsystems and the level below that the components of the subsystems. As you descend, the pyramid broadens and the number of tests increases. As you approach the bottom of the pyramid, you will consider a large number of tests for parts, physical processes, materials, etc. These tests are in general not specific to the full-scale system, but do play an important role in forming the basis of the pyramid, and are therefore essential in the overall validation procedure.

Clearly, building the complete testing and validation pyramid for your EST system is not possible in eight weeks. But that does not mean that you cannot contribute to the validation process. Your group will select one of the physical laws used in your model for experimental validation. The selected physical law should be as relevant as possible in view of the overall validation procedure. You should be able to explain its position in the validation pyramid and it should be clear what aspect(s) of the EST system (model) can be validated by the experiment. In the choice of your validation experiment, you should consider whether the required setup can be constructed using one of the experimental toolboxes (inventory and spec sheets are available here):

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The pneumatic energy toolbox contains components to construct a pressurize air setup, such as pressure vessels, air pumps, pressure sensors, and flow sensors.

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The mechanical energy toolbox contains components to construct a setup that, for example, stores energy by lifting weights. It contains a motor, gears, rotation speed sensors and accelerometers, amongst others.

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The hydraulic energy toolbox contains components to construct a setup that, for example, transports water between basins. It contains water containers, pumps, pressure sensors, and flow sensors, amongst others.

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The thermal energy toolbox contains components for a setup storing energy in the form of heat. Amongst others, it contains a vessel to store a heated liquid, insulation materials, and temperature sensors.

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Throughout the project you will develop the experimental setup for you validation experiment, along with a standard operating procedure (SOP) which describes the setup and all the steps in the experimental procedure. While developing the validation experiment, it is important to carefully consider which type of measurement results are needed to successfully validate the selected physical. Using the components in the toolbox of your choice, your team is free in designing its own experiment.

An essential part of the design of your setup is the integration of sensors that automatically gather data using an Arduino. To get you acquainted with the use of sensors and Arduino-based data gathering, early in the project you will participate in a measurement practical with an accompanying theory assignment. For the sensors in your validation experiment you need to study how they should be wired electronically. You should also develop the Arduino code to gather the data and, if applicable, you should develop calibration procedures.

Using the developed setup, you will perform the validation experiments. Your validation experiment should be documented in a measurement plan (part of the SOP), in which the experimental steps are described in detail. Based on the measurement plan, someone else should be able to reproduce the results. To attain statistically meaningful experimental results, your group should execute the experiment multiple times, strictly following the measurement plan. You should also create post-processing scripts which convert the raw data of all experiments into interpretable output, for example in the form of graphs. In these results, the uncertainties in the measurements should be visualized, for example using error bars. Once you have collected the output of the experiments, you can assess the validity of the considered physical law. The best way to do this is by plotting the experimental results and theoretical results in one graph. This makes it straightforward to observe and interpret the differences and similarities between the model result and the experimental data.

Track 4: Managing the learning process

To be successful in the project it is important that your team collaborates smoothly and that all team members get the space to function optimally. To make a good start with this, during the kick-off meeting on the opening day of the project, together with your tutor, you will set working agreements. By discussing strengths and weaknesses of the team and its members, you will also identify knowledge/skill gaps. Based on this you will define learning objectives for the team and for the members.

To make sure that your team functions well, it is important that all members feel confident regarding the tools to be used in the project. It is therefore mandatory for each member to complete the measurement practical and accompanying theory assignment, as well as a Simulink training. Besides these mandatory personal development tasks it may also be useful to boost your MATLAB and Arduino skills. If you are not yet comfortable with software to make professional and technical graphics (for example, Inkscape, IPE drawing editor, Powerpoint), you can work on this in the project.

Throughout the project your team will meet twice a week with your tutor. In these tutor meetings you will discuss the work performed by the members, including its documentation, giving each other constructive feedback. In these meetings you will also identify tasks/actions and divide these fairly over the team. It is important that the allocated tasks are in line with the expressed individual learning objectives of the team members, and that all members conduct work in all tracks. In week 4, together with your tutor, you will perform a (formative) mid-term evaluation. Based on the feedback in this mid-term evaluation you can improve toward the final evaluation in week 9.

Project study guide

This study guide outlines the steps to be taken in the project, helping your team to plan the activities. In the week tables below, the main tasks to be completed in the project are categorized per track:

For each task it is indicated what other tasks it depends on, and for which follow-up tasks it is required. Note that the scheduled sessions - for which attendance is mandatory - are not included in the weekly task tables.

Your group is responsible for planning the activities leading to the project goals and deliverables. In the weekly tutor meetings you will define self-study assignments. The defined self-study assignments should cover all tasks to be completed. A self-study assignment should reflect two hours of work. Many of the tasks are bigger than a single self-study assignment. You should then specify the self-study assignment in detail and indicate to which task it contributes. A team member should contribute to multiple tasks if a specific tasks costs less than two hours.

Your tutor will monitor the contributions of all members to the project tasks. To ensure that everyone is involved in all aspects of the project, the following rules apply:

• The individual tasks are to be completed by all team members.
• Each team member should contribute at least two self-study assignments to each task category/track.
• When multiple team members contribute to a single task, the specific activities for each team member should be clarified and noted down by the tutor.

Week 1

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8