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With the increasing share of renewable energies and the nuclear phase-out, the energy transition is accelerating. From the perspective of building technology, there is great potential to support this transition given its large share in total energy consumption and the increasing number of flexible and controllable components and storages. However, a question often asked at the plant level is: "How do we use this flexibility to support the regional grid?". In this work, a grid-supportive controller of a real-world building energy plant was developed using mathematical optimisation methods and its technical feasibility was demonstrated. The results could convince actors from the energy industry and academia about the practicality of these methods and offer tools for their implementation.
Am 1. Juli 2022 trafen sich im Rahmen des Abschlusskolloquiums des Projekts ACA-Modes rund 60 Teilnehmende aus Forschung, Lehre und Industrie zu einer internationalen Konferenz an der Hochschule Offenburg. Hier wurden die Projektergebnisse rund um die erfolgreiche Implementierung modellprädiktiver Regelstrategien vorgestellt, aktuelle Fragestellungen diskutiert und Entwicklungspfade hin zu einem netzdienlichen Betrieb von Energieverbundsystemen skizziert.
A coordinated operation of decentralised micro-scale hybrid energy systems within a locally managed network such as a district or neighbourhood will play a significant role in the sector-coupled energy grid of the future. A quantitative analysis of the effects of the primary energy factors, energy conversion efficiencies, load profiles, and control strategies on their energy-economic balance can aid in identifying important trends concerning their deployment within such a network. In this contribution, an analysis of the operational data from five energy laboratories in the trinational Upper-Rhine region is evaluated and a comparison to a conventional reference system is presented. Ten exemplary data-sets representing typical operation conditions for the laboratories in different seasons and the latest information on their national energy strategies are used to evaluate the primary energy consumption, CO2 emissions, and demand-related costs. Various conclusions on the ecologic and economic feasibility of hybrid building energy systems are drawn to provide a toe-hold to the engineering community in their planning and development.
Cooling towers or recoolers are one of the major consumers of electricity in a HVAC plant. The implementation and analysis of advanced control methods in a practical application and its comparison with conventional controllers is necessary to establish a framework for their feasibility especially in the field of decentralised energy systems. A standard industrial controller, a PID and a model based controller were developed and tested in an experimental set-up using market-ready components. The characteristics of these controllers such as settling time, control difference, and frequency of control actions are compared based on the monitoring data. Modern controllers demonstrated clear advantages in terms of energy savings and higher accuracy and a model based controller was easier to set-up than a PID.
Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analysis. It is shown that a simplified model may be sufficient for the system-oriented approach especially when the objective is an optimization-based control or planning. However, from a field level operational point of view, the differences in the time series signify the importance of the component-oriented approaches.
It is considered necessary to implement advanced controllers such as model predictive control (MPC) to utilize the technical flexibility of a building polygeneration system to support the rapidly expanding renewable electricity grid. These can handle multiple inputs and outputs, uncertainties in forecast data, and plant constraints, amongst other features. One of the main issues identified in the literature regarding deploying these controllers is the lack of experimental demonstrations using standard components and communication protocols. In this original work, the economic-MPC-based optimal scheduling of a real-world heat pump-based building energy plant is demonstrated, and its performance is evaluated against two conventional controllers. The demonstration includes the steps to integrate an optimization-based supervisory controller into a typical building automation and control system with off-the-shelf HVAC components and usage of state-of-art algorithms to solve a mixed integer quadratic problem. Technological benefits in terms of fewer constraint violations and a hardware-friendly operation with MPC were identified. Additionally, a strong dependency of the economic benefits on the type of load profile, system design and controller parameters was also identified. Future work for the quantification of these benefits, the application of machine learning algorithms, and the study of forecast deviations is also proposed.
Optimisation based economic despatch of real-world complex energy systems demands reduced order and continuously differentiable component models that can represent their part-load behaviour and dynamic responses. A literature study of existing modelling methods and the necessary characteristics the models should meet for their successful application in model predictive control of a polygeneration system are presented. Deriving from that, a rational modelling procedure using engineering principles and assumptions to develop simplified component models is applied. The models are quantitatively and qualitatively evaluated against experimental data and their efficacy for application in a building automation and control architecture is established.
Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.
Im Rahmen des EU-Forschungsprojektes ACA-Modes (Advanced Control Algorithms for Management of Decentralised Energy Systems) werden reale Labore der Projektpartner primärenergetisch, ökonomisch und die Emissionen betreffend bewertet. Vier Projektpartner liefern Datensätze aus Messreihen typischer Bereitstellungsszenarien. Die verschiedenen Systeme bestehen unter anderem aus einer KWK-Anlage mit Erdgas-Verbrennungsmotor, einer KWKK-Anlage mit Adsorptionskältemaschine, einer Photovoltaik-Anlage mit Batteriespeicher und Wärmepumpe und einer Solarthermieanlage mit Adsorptionskältemaschine.
The transformation of the building energy sector to a highly efficient, clean, decentralised and intelligent system requires innovative technologies like microscale trigeneration and thermally activated building structures (TABS) to pave the way ahead. The combination of such technologies however presents a scientific and engineering challenge. Scientific challenge in terms of developing optimal thermo-electric load management strategies based on overall energy system analysis and an engineering challenge in terms of implementing these strategies through process planning and control. Initial literature research has pointed out the need for a multiperspective analysis in a real life laboratory environment. To this effect an investigation is proposed wherein an analytical model of a microscale trigeneration system integrated with TABS will be developed and compared with a real life test-rig corresponding to building management systems. Data from the experimental analysis will be used to develop control algorithms using model predictive control for achieving the thermal comfort of occupants in the most energy efficient and grid reactive manner. The scope of this work encompasses adsorption cooling based microscale trigeneration systems and their deployment in residential and light commercial buildings.