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Open_Plan

Description

 

The open_plan_tool is a powerful open-source tool specifically designed for designing and optimizing multi-energy carriers energy systems and operational strategies. It is primarily intended for the supply of neighborhoods, industrial parks, and industries. This tool offers great versatility, allowing users to create various projects and scenarios. With just a few clicks, users can evaluate different cases and compare results across scenarios. Additionally, the open_plan_tool provides a range of use cases that serve as valuable references for users' own projects. One of the key strengths of the open_plan_tool is its user-friendly interface, making energy system modeling easier than ever before. It eliminates the need for programming language expertise, enabling users to configure their energy systems using modular components.

To begin using the open_plan_tool, users are prompted to provide the necessary data. This can be done through individual data input, a collection of CSV files, or a unique JSON file with a specific format. The input data is categorized into several sections, including the project description (which includes general project information and economic data), system configuration (where users specify technical and financial data for each asset), and constraints (which define the degree of autonomy and the share of renewable energies). The input data is then translated into a linear programming problem, also known as a constrained optimization problem. The open_plan_tool leverages the multi-vector simulator (MVS) and the oemof-solph python library to describe the problem, define an objective function to minimize annual energy supply costs, and set decision variables, limits, and constraints.

Once the simulation is run, the open_plan_tool provides outputs categorized into key performance indicators (KPIs), economic results, and technical results. These outputs include optimized capacities and dispatch information for each asset in the energy system, offering valuable insights into the system's performance.

In summary, the open_plan_tool is a comprehensive and user-friendly tool that empowers users to design and optimize complex multi-energy carriers energy systems. With its flexible scenario analysis capabilities and intuitive interface, users can make informed decisions and generate valuable insights for their energy planning projects.

 

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Classifications

 

Scale of implementation

The tool is designed to be used at various scales, including neighborhoods, industrial parks, and industries. It can accommodate energy system designs and optimizations for different sizes and complexities of projects.

 

Type

The Open_plan tool is a software tool, specifically an open-source tool, used for designing and optimizing multi-energy carriers energy systems and operational strategies.

 

Phase of solution

 The Open_plan tool is a solution that primarily focuses on the design and optimization phase of energy systems. It helps users in the initial planning and decision-making stages, allowing them to assess different scenarios and evaluate the performance of energy system configurations

 

Target audience

 he target audience of the Open_plan tool includes energy professionals, engineers, researchers, and decision-makers involved in the design, planning, and optimization of energy systems. The tool is valuable for both beginners and experienced professionals in the field, providing them with a user-friendly platform to model and optimize complex energy systems.

Key features-functionality

 

The key features and functionality of Open_plan tool include:

  1. Energy System Design and Optimization: The Open_plan tool enables users to design and optimize multi-energy carriers energy systems for neighborhoods, industrial parks, and industries. It allows users to configure their energy systems using modular components and provides a user-friendly interface for easy system design.
  2. Scenario Evaluation: Users can create and evaluate different scenarios within the Open_plan tool. This functionality allows for the comparison of results between scenarios, helping users make informed decisions and identify the most optimal energy system configurations.
  3. Use Cases and References: The Open_plan tool provides users with a range of use cases and references that serve as valuable resources for their own projects. These use cases offer insights and examples of successful energy system designs and optimizations.
  4. Data Input and Categorization: The tool allows users to input the required data for their energy system models. Data can be provided through individual inputs, a collection of CSV files, or a unique JSON file with a specific format. The data is categorized into project description, system configuration, and constraints.
  5. Linear Programming and Optimization: The Open_plan tool translates the input data into a linear programming problem, also known as a constrained optimization problem. It utilizes the multi-vector simulator (MVS) and the oemof-solph python library to describe the problem, define the objective function, and set decision variables, limits, and constraints.
  6. Simulation Outputs: After running the simulation, the Open_plan tool provides users with various outputs. These outputs include key performance indicators (KPIs), economic results, and technical results. Users can analyze the optimized capacities and dispatch of each asset in the energy system to gain insights into its performance.

References & Sources for Further Reading

 

  • Open_plan tool,  https://open-plantool.org/index_en.html
  • The open_plan project consortium is composed of the Reiner Lemoine Institute (RLI), German Solar Energy Society [Deutsche Gesellschaft für Sonnenenergie (DGS)] and the Potsdam Institute for Climate Impact Research. It is funded within the framework of the “Technology-oriented systems analysis” funding area of the BMWi’s 7th Energy Research Programme “Innovation for the energy transition”.
  • The open-plan-tool is currently maintained by staff from the Reiner Lemoine Institute the Potsdam Institute for Climate Impact Research and the German Solar Energy Society.