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1D2.1. Definition of common scenario framework, data/modelling requirements and use cases

This deliverable outlines the general scenario framework, which will be used for the investigations within PlaMES. Therefore, use cases are identified on which the project will be based on. Modelling requirements are derived from the use cases. Furthermore, necessary data to model the use cases is described and potential scenario assumptions are listed.
PlaMES will focus on two use cases, one Central and one Decentral use case. The output of the use cases will be an optimised energy system achieving the climate goals, while including integrated system costs for planning and operation of generation technologies, electricity grid infrastructure and coupled multi-energy sectors.

The Central use case aims to plan the Central Energy System, considering the commodities electricity, gas, heat and mobility. In an integrated expansion approach, generation capacity expansion will be combined with grid expansion. The main target of this optimisation problem is to generate a cost efficient energy system which is compliant with GHG emission (GHG) targets. Results of the first use case will be the planned expansion capacities per grid node and the electrical transmission grid, which is necessary to ensure security of supply. The Decentral use case will focus on the necessary expansion planning with focus on the Decentral Energy System. Therefore, renewable energy sources and other assets are located in a real distribution grid and an operational planning of this distribution grid is performed on basis of various coordination-mechanisms to minimise Decentral system costs. A distribution network expansion planning is performed to identify optimal grid expansion measures. The data requirements and scenario frameworks to model the two use cases are listed in a table with explanations and possible data sources.

Download (PDF): Deliverable 2.1

The Central use case aims to plan the Central Energy System, considering the commodities electricity, gas, heat and mobility. In an integrated expansion approach, generation capacity expansion will be combined with grid expansion. The main target of this optimisation problem is to generate a cost efficient energy system which is compliant with GHG emission (GHG) targets. Results of the first use case will be the planned expansion capacities per grid node and the electrical transmission grid, which is necessary to ensure security of supply. The Decentral use case will focus on the necessary expansion planning with focus on the Decentral Energy System. Therefore, renewable energy sources and other assets are located in a real distribution grid and an operational planning of this distribution grid is performed on basis of various coordination-mechanisms to minimise Decentral system costs. A distribution network expansion planning is performed to identify optimal grid expansion measures. The data requirements and scenario frameworks to model the two use cases are listed in a table with explanations and possible data sources.

Download (PDF): Deliverable 2.1

2D2.2 Mathematical formulation of the model

The general objective of PlaMES is the development of an integrated planning tool for multi-energy systems on a European
scale considering the expansion of generation and storage technologies as well as related infrastructure in an integrated
manner. Disruptive structural developments are necessary to deliver to the European Union’s COP21 commitments, as defined
by the "Clean Energy for All Europeans" package . Specific targets and measures are identified for the energy performance
in buildings, renewable energy, energy efficiency, governance and the market designs that envisage an increased cross-border cooperation and mobilisation of public and private investment. Providing European energy system planners with the means to develop eficient strategies to reach these goals is however associated with significant challenges.

In the following, a mathematical and functional formulation of the PlaMES tools is outlined and developed. Not neglecting the intention of an integrated planning, several tools are developed that cater to the individual needs of planning approaches in generation, transmission and distribution infrastructure expansion planning. The core of each tool is a mathematical model which is described with its ownnomenclature. As opposed to amonolithic model formulation, decomposing the problem benefits applicability as well as solvability. The decomposition approach follows functionality with diferent planning aspects in focus. As a result each tool can be run separately, nevertheless, every tool is needed to get a comprehensive understanding.

Download (PDF): Deliverable 2.2

In the following, a mathematical and functional formulation of the PlaMES tools is outlined and developed. Not neglecting the intention of an integrated planning, several tools are developed that cater to the individual needs of planning approaches in generation, transmission and distribution infrastructure expansion planning. The core of each tool is a mathematical model which is described with its ownnomenclature. As opposed to amonolithic model formulation, decomposing the problem benefits applicability as well as solvability. The decomposition approach follows functionality with diferent planning aspects in focus. As a result each tool can be run separately, nevertheless, every tool is needed to get a comprehensive understanding.

Download (PDF): Deliverable 2.2

3D2.3. Analysis of problem structure and first concept of decomposition approach

This deliverable describes the main algorithmic tools that will be developed within the project PlaMES to solve the two centralized optimization problems, namely the Central Energy System (CES) problem, which allows planning the necessary generation expansion in the centralised energy system and the Transmission Expansion Planning (TEP) problem, which allows for a detailed expansion planning of the electrical transmission grid, considering the allocation of generation units and their dispatch provided by CES.

These modules have to be optimized in coordination with the ther tools that will be considered within PlaMES, i.e., the Decentral Energy System Aggregation (DESA), the Decentral Energy System Disaggregation (DESD), the Decentral Energy SystemOperation (DESOP), and the DistributionNetwork Expansion Planning (DNEP). These four tools, that are defined at a decentralized level,may be object of further evaluation based on the outcomesof the first implementations of (decentral) models and the size of instances to be solved.

This document, based on the decomposition approach and mathematical models presented in Deliverable D2.2, is organized as follows. Chapter 1 recaps the general structure of the PlaMES framework and identifies the two optimization problems that are addressed. For the sake of completeness, these two problems will be addressed in two separate chapters. In particular, Chapter 2 reports a short description of problem CES, the main assumptions in modelling the problem, and the proposed mathematical formulation. Similarly, Chapter 3 gives the same information for problem TEP. Chapter 4 shows an analysis on the main characteristics of the models and gives a sketch of a possible solution approach based on Benders decomposition. Finally, Chapter 5 draws someconclusions and mentions relevant issues to be considered during the implementation of the algorithms, that will be part of WP4 “Development of solution methods”.

Download (PDF): Deliverable 2.3

These modules have to be optimized in coordination with the ther tools that will be considered within PlaMES, i.e., the Decentral Energy System Aggregation (DESA), the Decentral Energy System Disaggregation (DESD), the Decentral Energy SystemOperation (DESOP), and the DistributionNetwork Expansion Planning (DNEP). These four tools, that are defined at a decentralized level,may be object of further evaluation based on the outcomesof the first implementations of (decentral) models and the size of instances to be solved.

This document, based on the decomposition approach and mathematical models presented in Deliverable D2.2, is organized as follows. Chapter 1 recaps the general structure of the PlaMES framework and identifies the two optimization problems that are addressed. For the sake of completeness, these two problems will be addressed in two separate chapters. In particular, Chapter 2 reports a short description of problem CES, the main assumptions in modelling the problem, and the proposed mathematical formulation. Similarly, Chapter 3 gives the same information for problem TEP. Chapter 4 shows an analysis on the main characteristics of the models and gives a sketch of a possible solution approach based on Benders decomposition. Finally, Chapter 5 draws someconclusions and mentions relevant issues to be considered during the implementation of the algorithms, that will be part of WP4 “Development of solution methods”.

Download (PDF): Deliverable 2.3

4D3.1. Description of workflow coordination

This document describes the workflow and data managemen of the tools developed in WorkPackage3 (WP3) of thePlaMES
project. Since WP3 mainly comprises the tools dealing with mathematical optimization problems (described in Deliverable
2.2), this is also the focus of this deliverable. The final PlaMES tool architecture will consist of a range of additional tools and
submodules which are in development or will be developed at later stages. Nevertheless, provided information may be
useful with later developments, e.g. external data exchange interfaces, additional tool integration, or as an inspiration for
developments outside the projects’ context.

Download (PDF): Deliverable 3.1

Download (PDF): Deliverable 3.1

5D5.2. Report on assessment of the tool performance and test application results

PlaMES intends to help stakeholders in the energy system to take decisions about how the energy system should be designed
in 2050 to meet the carbon reduction goals. Therefore, we have developed the six models and tools as sketched in Deliverable 2.21 and shown in Figure 1.1. The models can be used in different combinations. As exemplary use cases, we have defined the Central Use Case and Decentral Use Case. In the Central Use Case, the generation and network expansion for the Europeanenergy systemcan be planned. Inthe Decentral Use Case, distribution systemscan be planned considering different coordination mechanisms for decentral energy systems.

Both use cases in PlaMES can lead to large optimization models. On the one hand, modeling the central European energy system leads to very large data sets and thus to large models. On the other hand, decentral energy systems are rather small compared to the central energy system but need to be modeled with higher granularity. This also leads to large models.To determine the simulation requirements for the two use cases of PlaMES, the hardware requirements need to be tested. Therefore, in the following chapters the models are tested and evaluated based on their run time, their required RAM and the required number of cores.

Download (PDF): Deliverable 5.2

Both use cases in PlaMES can lead to large optimization models. On the one hand, modeling the central European energy system leads to very large data sets and thus to large models. On the other hand, decentral energy systems are rather small compared to the central energy system but need to be modeled with higher granularity. This also leads to large models.To determine the simulation requirements for the two use cases of PlaMES, the hardware requirements need to be tested. Therefore, in the following chapters the models are tested and evaluated based on their run time, their required RAM and the required number of cores.

Download (PDF): Deliverable 5.2

6D6.1. Report on validation results

The presentation summarizes the results of the validation of the PlaMES tools.

Download (PDF): Deliverable 6.1

Download (PDF): Deliverable 6.1