Optimization approaches for exploiting the load flexibility of electric heating devices in smart grids

Energy systems all over the world are undergoing a fundamental transition to tackle climate change and other environmental challenges. The share of electricity generated by renewable energy sources has been steadily increasing. In order to cope with the intermittent nature of renewable energy sources, like photovoltaic systems and wind turbines, the electrical demand has to be adjusted to their power generation. To this end, flexible electrical loads are necessary. Moreover, optimization approaches and advanced information and communication technology can help to transform the traditional electricity grid into a smart grid. To shift the electricity consumption in time, electric heating devices, such as heat pumps or electric water heaters, provide significant flexibility. In order to exploit this flexibility, optimization approaches for controlling flexible devices are essential. Most studies in the literature use centralized optimization or uncoordinated decentralized optimization. Centralized optimization has crucial drawbacks regarding computational complexity, privacy, and robustness, but uncoordinated decentralized optimization leads to suboptimal results. In this thesis, coordinated decentralized and hybrid optimization approaches with low computational requirements are developed for exploiting the flexibility of electric heating devices. An essential feature of all developed methods is that they preserve the privacy of the residents. This cumulative thesis comprises four papers that introduce different types of optimization approaches. In Paper A, rule-based heuristic control algorithms for modulating electric heating devices are developed that minimize the heating costs of a residential area. Moreover, control algorithms for minimizing surplus energy that otherwise could be curtailed are introduced. They increase the self-consumption rate of locally generated electricity from photovoltaics. The heuristic control algorithms use a privacy-preserving control and communication architecture that combines centralized and decentralized control approaches. Compared to a conventional control strategy, the results of simulations show cost reductions of between 4.1% and 13.3% and reductions of between 38.3% and 52.6% regarding the surplus energy. Paper B introduces two novel coordinating decentralized optimization approaches for scheduling-based optimization. A comparison with different decentralized optimization approaches from the literature shows that the developed methods, on average, lead to 10% less surplus energy. Further, an optimization procedure is defined that generates a diverse solution pool for the problem of maximizing the self-consumption rate of locally generated renewable energy. This solution pool is needed for the coordination mechanisms of several decentralized optimization approaches. Combining the decentralized optimization approaches with the defined procedure to generate diverse solution pools, on average, leads to 100 kWh (16.5%) less surplus energy per day for a simulated residential area with 90 buildings. In Paper C, another decentralized optimization approach that aims to minimize surplus energy and reduce the peak load in a local grid is developed. Moreover, two methods that distribute a central wind power profile to the different buildings of a residential area are introduced. Compared to the approaches from the literature, the novel decentralized optimization approach leads to improvements of between 0.8% and 13.3% regarding the surplus energy and the peak load. Paper D introduces uncertainty handling control algorithms for modulating electricheating devices. The algorithms can help centralized and decentralized scheduling-based optimization approaches to react to erroneous predictions of demand and generation. The analysis shows that the developed methods avoid violations of the residents\u27 comfort limits and increase the self-consumption rate of electricity generated by photovoltaic systems. All introduced optimization approaches yield a good trade-off between runtime and the quality of the results. Further, they respect the privacy of residents, lead to better utilization of renewable energy, and stabilize the grid. Hence, the developed optimization approaches can help future energy systems to cope with the high share of intermittent renewable energy sources

An Overview on Functional Integration of Hybrid Renewable Energy Systems in Multi-Energy Buildings

Buildings are responsible for over 30% of global final energy consumption and nearly 40% of total CO2 emissions. Thus, rapid penetration of renewable energy technologies (RETs) in this sector is required. Integration of renewable energy sources (RESs) into residential buildings should not only guarantee an overall neutral energy balance over long term horizon (nZEB concept), but also provide a higher flexibility, a real-time monitoring and a real time interaction with end-users (smart-building concept). Thus, increasing interest is being given to the concepts of Hybrid Renewable Energy Systems (HRES) and Multi-Energy Buildings, in which several renewable and nonrenewable energy systems, the energy networks and the energy demand optimally interact with each other at various levels, exploring all possible interactions between systems and vectors (electricity, heat, cooling, fuels, transport) without them being treated separately. In this context, the present paper gives an overview of functional integration of HRES in Multi-Energy Buildings evidencing the numerous problems and potentialities related to the application of HRESs in the residential building sector. Buildingintegrated HRESs with at least two RESs (i.e., wind–solar, solar–geothermal and solar–biomass) are considered. The most applied HRES solutions in the residential sector are presented, and integration of HRES with thermal and electrical loads in residential buildings connected to external multiple energy grids is investigated. Attention is focused on the potentialities that functional integration can offer in terms of flexibility services to the energy grids. New holistic approaches to the management problems and more complex architectures for the optimal control are described

Optimal design of a hybrid energy plant by accounting for the cumulative energy demand

In this paper, the optimal design of a hybrid energy plant composed of a solar thermal collector, a photovoltaic panel, a combined heat and power system, an absorption chiller, an air source heat pump, a ground source heat pump and a thermal energy storage is studied. The size of each technology is optimized by applying a model implemented in Matlab® environment. The optimization goal is the minimization of the primary energy consumed throughout the life cycle of the hybrid energy plant by using a genetic algorithm. The primary energy consumed during the manufacturing phase of the hybrid energy plant is represented by the cumulative energy demand and is calculated by carrying out a cradle to gate life cycle assessment. The primary energy consumed during the operation phase is evaluated by simulating the system throughout one year. The cumulative energy demand of each system composing the hybrid energy plant is calculated as a function of the technology size. Therefore, the problem of life cycle assessment scaling of renewable and non-renewable energy systems is also taken into account in this paper. A tower located in the north of Italy is selected as a case study and two different approaches are evaluated. The first approach consists of solving the sizing optimization problem by minimizing the primary energy consumption only during the operation phase, while in the second approach the primary energy consumption is minimized throughout the life cycle of the plant by integrating the life cycle assessment into the optimization process. The results show that, if life cycle assessment is accounted for, the optimal hybrid energy plant configuration is different and a higher primary energy saving (approximately 12%) is achieved

Heat Pumps and Their Role in Decarbonising Heating Sector: A Comprehensive Review. ESRI WP627, June 2019

Addressing the growing concerns of climate change necessitates the decarbonisation of energy sectors globally. The heating sector is the largest energy end-use, accounting for almost half of the total energy consumption in most countries. This paper presents an extensive review of previous works on several aspects of heat pumps, including their role in the decarbonisation of the heating sector. In addition, we cover themes related to the recent technological advances of heat pumps as well as their roles in terms of adding flexibility to renewable-rich systems and carbon abatement. We also identify challenges and barriers for a significant uptake of heat pumps in various markets. Generally, as the share of renewables in the energy mix increases, heat pumps can play a role in addressing a multitude of problems induced by climate change. However, economic, regulatory, structural and infrastructural barriers exist, which may hinder heat pump integration rate

Long-term sustainable operation of hybrid geothermal systems through optimal control

Hybrid geothermal systems such as hybrid GEOTABS typically comprise a geothermal heat pump that supplies the main building thermal energy needs, complemented by a fast-reacting supplementary production and/or emission system for the peak building thermal loads. Optimal predictive controllers such as Model Predictive Control (MPC) are desired for these complex systems due to their optimized and automated energy savings potential (while providing the same or better thermal comfort) thanks to system integration and their anticipative action. However, the predictions of these controllers are typically limited to a few days. Consequently, the controller is unaware whether abusive energy injection/extraction into/from the soil will deplete the source over the years. This paper investigates in which cases the long-term dynamics of the borefield ought to be included in the MPC formulation. A simulation model of a hybrid GEOTABS system is constructed. Different borefield sizes, ground imbalance loads, and electricity/gas ratios are evaluated. The model control inputs are optimized to minimize the energy use in 5 years through (i) a reference Optimal Control Problem (OCP) for the 5 years, solved in hourly timesteps and (ii) an MPC control with a prediction horizon of 1 week. The obtained results reveal that MPC can be up to 20% far from the true optimal, especially in the cases where the borefield is undersized and there is a large cost gap between the different energy systems

Photovoltaic Thermal hybrid collectors for a district CCHP system: modelling and optimization

Modellazione e simulazione di un sistema basato sulla tecnologia dei pannelli solari ibridi per la trigenerazione di energia destinata ad un uso residenziale. I carichi e le condizioni ambientali sono valori orari annuali tratti da banche dati per le città di Atene in Grecia e Vicenza in Italia. L'ottimizzazione sfrutta un algoritmo evolutivo per implementare un problema di ricerca del minimo. Le funzioni obiettivo usate sono parametri economici ed energetici.openEmbargo temporaneo per motivi di segretezza e/o di proprietà dei risultati e/o informazioni sensibil

New sizing methodology for cost minimization of ground coupled heat pump systems considering groundwater flow

Ce mémoire de maîtrise introduit une nouvelle méthodologie de conception et d’optimisation techno-économique de systèmes géothermiques qui tient compte des écoulements souterrains. Une revue de littérature est complétée et la problématique est définie en s’appuyant sur les manques à combler au niveau des procédures de dimensionnement actuelles. La nouvelle procédure de dimensionnement inclut, entre autre, les données hydrogéologiques, les charges thermiques du bâtiment et les coûts du système géothermique. De plus, elle améliore les méthodologies actuelles en incluant une approche analytique pour la modélisation des écoulements souterrains lors de la simulation du champ de puits géothermiques. La méthodologie de recherche est présentée, y compris la stratégie d'optimisation, les fonctions G utilisées lors de la simulation énergétique et les défis rencontrés au cours de cette maîtrise. Les fonctions G sont calculées avec deux modèles analytiques: source cylindrique infinie et source linéique finie mobile. Une nouvelle simplification mathématique pour l'intégration des fonctions G dans la routine d'optimisation est démontrée, ce qui permet de réduire considérablement le temps de calcul (jusqu'à 25%), en plus de constituer un nouvel ajout aux méthodologies actuelles utilisant des fonctions G. Les procédures de test et l'analyse de la convergence sont également discutées. La nouvelle méthode de dimensionnement comprend le calcul des coûts initiaux et opérationnels. Des variables de conception optimales (profondeur de forage, distance entre les trous de forage consécutifs, etc.) et des aménagements de champ de puits (nombre de puits dans la direction x) sont présentés pour différentes valeurs de conductivité thermique du sol et de vitesse d’écoulement des eaux souterraines. En outre, une étude paramétrique est réalisée pour mesurer l’impact de l’écoulement des eaux souterraines par rapport au champ de puits sur l'aspect économique du projet. Une comparaison simultanée des coûts initiaux et opérationnels est également effectuée, ce qui permet de fournir des notions intéressantes pour les processus de conception à critères multiples. Enfin, les conceptions optimisées sont testées en dehors des conditions d’opération nominales.This master’s thesis introduces a new sizing methodology for ground coupled heat pump (GCHP) systems which takes into account groundwater flow in order to achieve a technoeconomic optimization of the total cost of the project. A literature review is presented and the problem is defined in order to show missing elements from current GCHP sizing procedures. The new sizing procedure includes hydrogeological data, building thermal loads, and GCHP system costs, while improving actual design methodologies by including an analytical approach for groundwater flow in the heat transfer simulation of the borefield. The research methodology is presented, including the optimization strategy, the G-functions used during energy simulations, and the challenges encountered during this master’s degree. The G-functions are calculated with two analytical models: infinite cylinder source (ICS) and moving finite line source (MFLS). A new mathematical simplification for the integration of G-functions in the optimization routine is derived, which considerably reduces computational time (by up to 25%) and is a new addition to current methodologies using G-functions. Testing procedures and a convergence analysis are also discussed. The new sizing methodology includes the calculation of the initial and the annual operational costs. Optimal design variables (borehole depths, distance between consecutive boreholes, etc.) and borefield layouts (number of boreholes in the x -direction) are presented for different values of ground thermal conductivity and groundwater velocity. In addition, a parametric study is done to measure the impact of the groundwater flow velocity and angle with respect to the borefield on the economics of the project. A simultaneous comparison of the initial and operational costs is also completed, as it can provide interesting insights for multi-criterion design processes. Finally, optimized designs are tested under off-design operating conditions

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques

Thermal Baths as Quantum Resources: More Friends than Foes?

In this article we argue that thermal reservoirs (baths) are potentially useful resources in processes involving atoms interacting with quantized electromagnetic fields and their applications to quantum technologies. One may try to suppress the bath effects by means of dynamical control, but such control does not always yield the desired results. We wish instead to take advantage of bath effects, that do not obliterate "quantumness" in the system-bath compound. To this end, three possible approaches have been pursued by us: (i) Control of a quantum system faster than the correlation time of the bath to which it couples: Such control allows us to reveal quasi-reversible/coherent dynamical phenomena of quantum open systems, manifest by the quantum Zeno or anti-Zeno effects (QZE or AZE, respectively). Dynamical control methods based on the QZE are aimed not only at protecting the quantumness of the system, but also diagnosing the bath spectra or transferring quantum information via noisy media. By contrast, AZE-based control is useful for fast cooling of thermalized quantum systems. (ii) Engineering the coupling of quantum systems to selected bath modes: This approach, based on field -atom coupling control in cavities, waveguides and photonic band structures, allows to drastically enhance the strength and range of atom-atom coupling through the mediation of the selected bath modes. More dramatically, it allows us to achieve bath-induced entanglement that may appear paradoxical if one takes the conventional view that coupling to baths destroys quantumness. (iii) Engineering baths with appropriate non-flat spectra: This approach is a prerequisite for the construction of the simplest and most efficient quantum heat machines (engines and refrigerators). We may thus conclude that often thermal baths are "more friends than foes" in quantum technologies.Comment: 27 pages, 17 figure