A comparative co-simulation analysis to improve the sustainability of cogeneration-based district multi-energy systems using photovoltaics, power-to-heat, and heat storage

For an extensive decarbonization of district multi-energy systems, efforts are needed that go beyond today\u27s cogeneration of heat and power in district multi-energy systems. The multitude of existing technical possibilities are confronted with a large variety of existing multi-energy system configurations. The variety impedes the development of universal decarbonization pathways. In order to tackle the decarbonization challenge in existing and distinct districts, this paper calculates a wide range of urban district configurations in an extensive co-simulation based on domain specific submodels. A district multi-energy system comprising a district heating network, a power grid, and cogeneration is simulated for two locations in Germany with locally captured weather data, and for a whole year with variable parameters to configure a power-to-heat operation, building insolation/refurbishment, rooftop photovoltaic orientation, future energy demand scenarios, and district sizes with a temporal resolution of 60 seconds, in total 3840 variants. The interdependencies and synergies between the electrical low-voltage distribution grid and the district heating network are analysed in terms of efficiency and compliance with network restrictions. Thus, important sector-specific simulations of the heat and the electricity sector are combined in a holistic district multi-energy system co-simulation. The clearly most important impact on emission reduction and fuel consumption is a low heat demand, which can be achieved through thermal refurbishment of buildings. Up to \SI{46}{\percent} reduction in $CO_2$ emissions are possible using the surplus electricity from photovoltaics for power-to-heat in combination with central heat storage in the district\u27s combined heat and power plant. Domestic hot water heated by district heating network in combination with power-to-heat conversion distributed in the district reduces the load on the distribution power grid. Even though the investigated measures already improve the sustainability significantly, providing the energy needed for the production of synthetic fuels remains the crucial challenge on the further path towards net-zero

Räumlich hoch aufgelöste Modellierung des Spaltproduktverhaltens in einem HTR-Core mit kugelförmigen oder prismatischen Brennelementen

One of the most important aspects during the licensing procedure of nuclear facilities is the release of radioactive isotopes. The transport from the origin to the environment is called release chain. In the scope of this work, the spatially distributed fission product release from both spherical and prismatic fuel elements, the transport with the coolant as well as the deposition on reactor internals are simulated in detail. The fission product release codes which were developed at Forschungszentrum Jülich are analyzed, shortcomings are identified and resolved. On this basis, a consistent simulation module, named STACY, was developed, which contains all capabilities of the stand-alone codes and at the same time exceeds the methodology towards new aspects. The physics models were extended, for example to take the radial temperature profile within the fuel element and the realistic time-depending nuclide inventory into account. A central part of this work is the automated treatment of the release behavior of a representative number of fuel elements. This allows for a spatially resolved release calculation, where an individual release rate is calculated for each space region. The coupling with the depletion code Topological Nuclide Transmutation (TNT) allows for conducting an individual depletion calculation for each considered fuel element. It is shown, that the released inventory is representative for a certain number of fuel elements. By using this model, the fission product release is being studied for a reference plant (HTR-Modul). Both the releases from the equilibrium core as well as the release during a core heat-up after a fast depressurization accident are being studied. In comparison to former studies, the cumulative release of long-lived nuclides during the core heat-up phase is lower and the release of short-lived nuclides is about two times higher. The release calculation can also be conducted for prismatic fuel elements (e.g. those of the Japanese HTTR). In this case, for each fuel element the depletion and release behavior of a representative compact is being determined. Furthermore, a new pebble flow model Software for Handling Universal Fuel Elements (SHUFLE) has been developed, which allows for modeling the pebble flow more in detail within the framework of a multi-physics code package. The model describes the movement of smaller fuel element clusters as a sequence of seepage processes. With the help of experimental data, it is demonstrated that the model can depict the pebble fuel in detail

Estudio de lechos fluidizados de esferas aplicados a reactores HTR

Los reactores nucleares de alta temperatura refrigerados por gas (HTR) forman una de las ramas en desarrollo para la construcción de los reactores de III+ y IV generación. Se caracterizan por obtener elevados rendimientos eléctricos y la posibilidad de obtener calor de proceso a muy alta temperatura además de una mayor seguridad intrínseca. En el pasado estuvieron operativos varios modelos en Alemania, Reino Unido y EE.UU. los cuales mostraron su viabilidad técnica. Existen diversos proyectos de desarrollo y construcción a nivel mundial y actualmente esta operativo un reactor de pruebas en China de 10MWe. Uno de los conceptos en estudio avanzado es el de lecho fluido, en el cual, la vasija del reactor es similar a un silo de almacenamiento. Dicha vasija esta rellena de esferas de 6cm de diámetro las cuales forman una matriz de grafito refractario. Dentro de las mismas se encuentra embebido el material radiactivo que actúa como combustible en las reacciones nucleares. Para el desarrollo de los nuevos diseños de reactores es preciso conocer el comportamiento de las esferas en el lecho fluidizado así como su movimiento, ya que la carga de combustible nuclear depende del tiempo que tardan las esferas en abandonar la vasija. La gravedad es la fuerza impulsora de dichas esferas, las cuales caen a ritmo controlado mediante un dispositivo de expulsión. Por lo tanto, es preciso conocer con precisión la distribución de tiempos de residencia, así como los perfiles de velocidad y las lineas de corriente. Dado que este comportamiento esta orientado a la etapa de diseño del reactor, se requiere también, que los cálculos sean realizados en el menor tiempo posible y que se fijen unos parámetros que doten de flexibilidad al modelo de cálculo así como de un cierto margen de calibración para el estudio de diferentes diseños. Es posible realizar dicha tarea a través de métodos de computación de sistemas mecánicos, sin embargo, no cumplen los requerimientos de tiempo y flexibilidad, además, suman complejidad y coste. Por lo tanto, y siguiendo una serie de trabajos realizados en el pasado, se contempla como opción mas viable, el desarrollo de un modelo basado en fluidodinámica computacional (CFD) que ya se mostraron eficaces en el pasado. Para realizar dicha tarea, es necesaria primeramente una labor de investigación acerca de los fenómenos de fluido granular, fluidos viscosos, fuerzas de fricción, propiedades de los materiales, características geométricas, así como de los diferentes métodos de cálculo ya realizados. Con todo ello, se pretende acoplar las variables de ambos sistemas y adaptarlas para que sea posible obtener una solución realista y con cierto nivel de precisión. Posteriormente, el modelo ha de ser calibrado y validado con una serie de experimentos realizados. Finalmente se han de calibrar las diferentes variables para poder continuar con los trabajos en el futuro. Con todo lo anterior, se pretende obtener un modelo de comportamiento que pueda ser utilizado en los programas que se comercializan actualmente

Economic and Ecologic Evaluation of Low Temperature Waste Heat Integration Into Existing District Heating

The integration of waste heat into district heating of-fers the potential to decrease the environmental im-pact of the district heating’s energy supply. A signifi-cant amount of waste heat is available at low tempera-tures, compared to existing district heating networks.In this paper, we generate a simulation model of a dis-trict heating network from a database and evaluatethe integration of waste heat compared to the originaldesign. Our simulation demonstrates the feasibility ofintegrating low temperature waste heat into an exist-ing network. The waste heat utilization can decreasethe primary energy consumption and CO2emissionsfor the respective buildings. These results can beimproved further by optimizing the low-temperaturenetwork connection of each building

Impact of Parametrization of Battery Energy Storages on Multi-AgentEnergy Systems with a High Share of Renewable Energy Sources

With the increasing share of distributed renewable energy sources not only the need for distributed energy storages rises, but also the need to coordinate those storages in the context of their local micro-grid. This publication illustrates the impact of battery energy storages on the overall performance of a district energy system. The energy system is controlled in a distributed way by using a multiagent approach that is scheduled by a market-mechanism. This market-mechanism allows to coordinate many individual agents with only few restrictions. The individual agents are flexible in the internal approach to forecast power supply or demand, allowing easy development of agents using individual algorithms.Besides pure consumer or producer agents, the battery storage forms a prosumer agent that can consume energy in some time-steps while supplying energy in others. By this, battery agents provide flexibility to the micro-grid while also aiming to generate profit for the owner. This approach is therefore attractive to both, the district energy system and the battery storage operator. The presented battery agents use model predictive control to determine the optimal operation strategy/bid for the upcoming time horizon. The determination of optimal strategy does not only assume losses but also takes the resulting degradation of the battery-cells into account. In a case study, we show the impact of battery storages on the overall system performance. As a main part of the publication, a sensitivity study reveals the importance of the individual parameters and how the revenue of the storage agent is affected. By adapting the charging and discharging power by 20 %, the profit can be increased by 33 % for the presented case

Modelling of Energy Systems with Seasonal Storage and System State dependent Boundary Conditions using Time Series Aggregation and Segmentation

The optimization of planning is one of the challenging tasks for the optimal control of energy systems with seasonal storage. An optimization quickly becomes computationally intractable due to a high temporal resolution and a long time horizonneeded for seasonal energy storage. Time series aggregation, in combination with additional time coupling constraints, can be used to reduce the size of the optimization problem drastically. However, some constraints of an energy system aredirectly dependent on the current system state and cannot be modeled as part of a typical period. To preserve the computational advantages of time series aggregation with extra constraints for storage units while modeling a set of constraints with a full temporal resolution, we propose a method that uses a mapping between intra-period, inter-period, and full-resolution variables. Furthermore, we propose a separation of the year into different regions during the clustering. This leads to a decoupling of different regions of the year and therefore increases the flexibility of the optimization.In a case study, we adopt the approach for an energy system with a dynamic hydrogen pipeline and a liquid organic hydrogen carrier (LOHC) storage system with a hot pressure swing reactor. By using full-resolution variables and a separationof the year in 3 different regions, we were able to reduce the computational time by 78% while maintaining an accuracy of 3% compared to an optimization with the full-time resolution.The separation of the year into 3 regions lead to a consistent improvement in accuracy of up to 29.4% and a run time decrease of up to 82% compared to a clustering of the whole year in typical periods. Furthermore, a separation of the yearinto 3 regions extended the feasibility of the optimization problem to very low numbers of typical periods

Data-Driven Generation of Mixed-Integer Linear Programming Formulations for Model Predictive Control of Hybrid Energy Storage Systems using detailed nonlinear Simulation Models

The scheduling of hybrid energy systems with battery storage systems (BSS) and hydrogen storage systems (HSS) for the storage of renewable energies is a non-trivial task due to the nonlinear nature of electrolyzers and fuel cells and the volatile electricity generation by renewable energies. Mathematical optimization of the scheduling increases the system efficiency and decreases the share of grid electricity required to cover the electrical demand. Hence, tailor-made models are required for each hydrogen component due to the uniqueness of each hydrogen system. Therefore, the time-consuming work of model generation and validation needs to be done for every system in order to ensure adequate accuracy of the mathematical models used for model predictive control. This work derives and utilizes a simulation model of a hybrid energy system as a substitute for a real-world system. We propose a framework that uses functional mock-up units of detailed simulation models to derive tailormade mixed-integer linear programming (MILP) formulations of the steady-state operational behavior. We combine the derived formulations for the operational behavior of each component into an optimization model of the whole hybrid energy system. The optimization model is then used for model predictive control of the simulation model. The results show that we can generate accuratemodels of the component behavior without detailed knowledge of the simulation model. The resulting optimization model of the whole energy system accurately reflects the simulation model and is, therefore, suitable for model predictive control

Low-Grade Waste Heat Integration into an Existing High-Temperature District Heating System at the Research Centre in Juelich, Germany

To decarbonize the building sector, using waste heat sources in district heating systems is crucial for the futureefficient and sustainable heat supply of buildings. This paper investigates a possible integration of a large wasteheat source into an existing local district heating system on the research centre campus in J¨ ulich, Germany.The new energy source to be integrated into the district heating system is a new high-performance computerthat supplies waste heat at a low-temperature level. We investigate the possibilities of integrating the wasteheat source based on the design of the currently operating combined cooling, heating and power generationsystem by calculating and evaluating different system concepts. In addition, we prove the feasible waste heatintegration into the district heating system through network simulations in Modelica. The environmental benefitsin terms of carbon dioxide reduction are evaluated while showing the challenges for an economic realization.However, the usable waste heat in the current energy system is limited since a high workload operation ofthe present combined heating and power system is necessary for an economical operation. Therefore, westudy an approach to maintain a high workload of the combined heat and power system by shifting a higherproportion of high-temperature heat to the absorption refrigerator for cooling purposes. The studied options ofwaste heat integration into the local district heating system show a reduction of carbon dioxide emissions upto 3,396 tCO2 per year. Furthermore, economic integration of the new waste heat source is also feasible byimplementing the studied measures in the local energy system. Therefore, this study shows that it is possibleto integrate a low-grade heat source into an energy system that is mainly supplied by a combined cooling,heating and power generation system

Hierarchical Model Predictive Control for Complex Building Energy Systems

In this paper, a hierarchical Modelica-based Model Predictive Control (MPC) is presented in order to control complex building energy systems with different dynamics. The hierarchical MPC concept tackles the problem of controlling buildings with slow dynamics such as thermally activated building systems (TABS) and fast actuators such as air handling units (AHUs). It further addresses prediction errors of system disturbances (e.g. weather, occupancy) and ensures anticipation, reactivity and real-time capability. The benefits compared to single MPC, Rule-Based-Control (RBC) and Proportional-Integrative-Derivative (PID) strategies are demonstrated in simulations on Modelica models including detailed models for solar shading and visual comfort