239 research outputs found

    Hybrid energy system integration and management for solar energy: a review

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    The conventional grid is increasingly integrating renewable energy sources like solar energy to lower carbon emissions and other greenhouse gases. While energy management systems support grid integration by balancing power supply with demand, they are usually either predictive or real-time and therefore unable to utilise the full array of supply and demand responses, limiting grid integration of renewable energy sources. This limitation is overcome by an integrated energy management system. This review examines various concepts related to the integrated energy management system such as the power system configurations it operates in, and the types of supply and demand side responses. These concepts and approaches are particularly relevant for power systems that rely heavily on solar energy and have constraints on energy supply and costs. Building on from there, a comprehensive overview of current research and progress regarding the development of integrated energy management system frameworks, that have both predictive and real-time energy management capabilities, is provided. The potential benefits of an energy management system that integrates solar power forecasting, demand-side management, and supply-side management are explored. Furthermore, design considerations are proposed for creating solar energy forecasting models. The findings from this review have the potential to inform ongoing studies on the design and implementation of integrated energy management system, and their effect on power systems

    Flexibility from local resources: Congestion management in distribution grids and carbon emission reductions

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    Flexibility from local energy systems has been discussed as a facilitator for the transition towards a more carbon-neutral energy system. Two use cases of this flexibility are congestion management in electricity distribution networks, and an individual-driven reduction of carbon footprints. However, for taping into this flexibility, effective incentive mechanisms and operation planning are essential. This licentiate thesis aims to provide new insights into two areas: 1) the design of market-based incentive mechanisms for congestion management in distribution grids, and 2) the operation planning of local flexible asset owners for reducing their carbon emission footprints.The first area focuses on challenges, design, and evaluation of local flexibility markets (LFMs) for congestion management in distribution grids. The utilized methods include literature review, field studies, scenario planning methods, and demonstration and simulation experiments.Results for identifying the challenges show that the most impactful and uncertain factors are the willingness and ability of end-users to participate in LFMs, and regulatory incentives for distribution system operators (DSOs). Moreover, five challenges are identified for LFM design including low market liquidity, reliability concerns, baselines, forecast errors at low aggregation levels, and the high cost of sub-meter measurements.An LFM design is proposed to address the challenges. The design is a triple horizon market structure including reservation, activation, and adjustment horizons which can support decision making of market participants and improve market liquidity and reliability. Adapted capacity-limitation products are proposed that are calculated based on net-load and subscribed connection capacity of end-users. The products can reduce conflict of interests, and administrative and sub-meter measurement costs related to delivery validation and baselines. Moreover, probabilistic approaches for calculating the cost and value of the products are proposed that can reduce the potential cost of forecast errors for market participants while providing insights on how the utility and cost of the products can be calculated.Evaluating the proposed design is an ongoing work utilizing simulations and real-life demonstrations. The most suitable congestion management solution can vary depending on the context and test-system. Therefore, the evaluation should include comparing the design with other congestion management solutions such as power tariffs. A comparison toolbox is proposed to be used by researchers and DSOs including a qualitative comparison framework and a reusable modeling platform for the quantitative comparison. Four cases are quantitatively compared using the toolbox on a sub-area of Chalmers campus testbed: i) LFM+PT+ET (i.e., considering the LFM, power tariff (PT), and energy cost (ET) simultaneously), ii) LFM+ET, iii) PT+ET, and iv) ET. The most recent results show that case (i), has the lowest number of congested hours. Moreover, congestions due to rebound effects from activating the LFM are observed. The comparison of cases (i) and (ii) suggests that enforcing power tariffs besides the LFM can reduce the rebound effects.The second area utilizes a multi-objective optimization model for identifying CO2 emission abatement strategies and their cost for Chalmers testbed local multi-energy system. The results of the case study show that the carbon emission footprint of the local system can be reduced by 20.8% with a 2.2% increase in the cost. The operation strategies for this purpose include more usage of biomass boilers in heat production, substitution of district heating and absorption chillers with heat pumps, and higher utilization of storage. The cost of the strategies ranged from 36.6-100.2 €/tCO2.This thesis can benefit system operators, flexibility asset owners, policy makers, and researchers dealing with local flexibility resources by offering insights into the challenges and proposing solutions and toolboxes for implementation and evaluation

    Optimization of Sustainable Urban Energy Systems: Model Development and Application

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    Digital Appendix: Optimization of Sustainable Urban Energy Systems: Model Development and Applicatio

    Book of Abstracts:9th International Conference on Smart Energy Systems

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    Demand Response in Smart Grids

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    The Special Issue “Demand Response in Smart Grids” includes 11 papers on a variety of topics. The success of this Special Issue demonstrates the relevance of demand response programs and events in the operation of power and energy systems at both the distribution level and at the wide power system level. This reprint addresses the design, implementation, and operation of demand response programs, with focus on methods and techniques to achieve an optimized operation as well as on the electricity consumer

    Life-cycle optimization of building performance: a collection of case studies

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    The building sector is one of the most impacting on the energy demand and on the environment in developed countries, together with industry and transports. The European Union introduced the topic of nearly zero-energy building (nZEB) and promoted a deep renovations in the existing building stock with the aim of reducing the energy consumption and environmental impacts of the building sector. The design of a nZEB, and in general of a low-energy building, involves different aspects like the economic cost, the comfort indoor, the energy consumption, the life cycle environmental impacts, the different points of view of policy makers, investors and inhabitants. Thus, the adoption of a multicriteria approach is often required in the design process to manage some potential conflicting domains. In detail, one of the most suitable approaches is to integrate the preliminary building design (or renovation) phase in a multi-objective optimization problem, allowing to rapidly compare many alternatives and to identify the most adapt interventions

    Mathematical Methods and Operation Research in Logistics, Project Planning, and Scheduling

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    In the last decade, the Industrial Revolution 4.0 brought flexible supply chains and flexible design projects to the forefront. Nevertheless, the recent pandemic, the accompanying economic problems, and the resulting supply problems have further increased the role of logistics and supply chains. Therefore, planning and scheduling procedures that can respond flexibly to changed circumstances have become more valuable both in logistics and projects. There are already several competing criteria of project and logistic process planning and scheduling that need to be reconciled. At the same time, the COVID-19 pandemic has shown that even more emphasis needs to be placed on taking potential risks into account. Flexibility and resilience are emphasized in all decision-making processes, including the scheduling of logistic processes, activities, and projects

    Sustainable Design of Industrial Energy Supply Systems - Development of a model-based decision support framework

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    Energy and media supply systems and related infrastructure at industrial sites have grown historically and is largely dependent on the use of fossil fuels. High fuel prices and the emission reduction targets of companies challenge existing supply concepts. Supply concepts usually remain in place for decades due to the long-lived nature of generation technologies and distribution systems. Today's investment decisions are therefore confronted with a changing environment in which the share of volatile renewables from solar and wind is continuously increasing. The long planning horizons make design decisions very complex. Optimization-based design approaches automatically derive cost- or carbon-optimal selections of generation technologies and procurement tariffs. Thus, they enable faster and more accurate planning decisions in techno-economic feasibility studies. In this work, a novel optimization model for techno-economic feasibility studies in industrial sites is developed. The optimization model uses a generic technology formulation with base classes, which takes into account the large variety of technologies and procurement tariffs at industrial sites. The optimization model also includes two reserve concepts: an operating reserve concept for short-term disruptions and a redundancy concept for long-term plant failures. The two concepts ensure security of supply for production-related energy requirements and thereby contributes to avoidance of costly production outages. The optimization model is integrated into an optimization framework to effectively calculate decarbonization strategies. The framework uses time series aggregation and heuristic decomposition techniques. Time series aggregation is performed by an integer program and results in a robust selection of representative days. The selection of representative days is used in a multi-year planning model to derive transformation roadmaps. Transformation roadmaps analyze the evolution of energy supply systems to long-term trends and consider adaptive investment decisions. A transformation strategy with myopic foresight (MYOP) solves the multi-year planning problem sequentially and is solved up to 98 % faster than a transformation approach with perfect foresight (PERF). The high uncertainties in early planning phases and the resulting need for detailed sensitivity analysis make this approach the preferred choice for many feasibility studies. The newly developed optimization framework is used in numerous research and consulting projects for urban districts, microgrids and factories. In this work, the capabilities of the framework are demonstrated for three use cases (automotive, pharmaceutical, dairy) of factory sites in southern Germany. In the use cases, decarbonization strategies for electricity, steam, heating and cooling supply are analyzed. Simulation evaluations identify changing operating patterns of combined heat and power (CHP) plants along the 15-year planning horizon. In addition, electrification of heating demand leads to a significant increase of total electricity demands. The results derived with the framework provide decision makers in industrial companies a clear view of the long-term impact of their investment decisions on decarbonization strategies

    Komponentenbasierte dynamische Modellierung von Energiesystemen und Energiemanagement-Strategien fĂŒr ein intelligentes Stromnetz im Heimbereich

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    The motivation of this work is to present an energy cost reduction concept in a home area power network (HAPN) with intelligent generation and flexible load demands. This study endeavors to address the energy management system (EMS) and layout-design challenges faced by HAPN through a systematic design approach. The growing demand for electricity has become a significant burden on traditional power networks, prompting power engineers to seek ways to improve their efficiency. One such solution is to integrate dispersed generation sources, such as photovoltaic (PV) and storage systems, with an appropriate control mechanism at the distribution level. In recent years, there has been a significant increase in interest in the installation of PV-Battery systems, due to their potential to reduce carbon emissions and lower energy costs. This research proposes an optimal economic power dispatch strategy using Model Predictive Control (MPC) to enhance the overall performance of HAPN. A hybrid AC/DC microgrid concept is proposed to address the control choices made by the appliance scheduling and hybrid switching approaches based on a linear programming optimization framework. The suggested optimization criteria improve consumer satisfaction, minimize grid disconnections, and lower overall energy costs by deploying inexpensive clean energy generation and control. Various examples from actual case study demonstrate the use of the established EMS and design methodology.Die Motivation dieser Arbeit besteht darin, ein Konzept zur Senkung der Energiekosten in einem Heimnetzwerk (HAPN) mit intelligenter Erzeugung und exiblen Lastanforderungen vorzustellen. Im Rahmen dieser Forschungsarbeit wird ein Entwurf fĂŒr ein HAPN entwickelt, indem das Energiemanagementsystem (EMS) und der Entwurf des Layouts auf der Grundlage des Systemmodells und der betrieblichen Anforderungen gelöst werden. Die steigende Nachfrage nach ElektrizitĂ€t ist fĂŒr traditionelle Stromnetze kostspielig und infrastrukturintensiv. Daher konzentrieren sich Energietechniker darauf, die Effizienz der derzeitigen Netze zu erhöhen. Dies kann durch die Integration verteilter Erzeugungsanlagen (z. B. Photovoltaik (PV), Speicher) mit einem geeigneten Kontrollmechanismus fĂŒr das Energiemanagement auf der Verteilungsseite erreicht werden. DarĂŒber hinaus hat das Interesse an der Installation von PV-Batterie-basierten Systemen aufgrund der Reduzierung der CO2-Emissionen und der Senkung der Energiekosten erheblich zugenommen. Es wird eine optimale wirtschaftliche Strategie fĂŒr den Energieeinsatz unter Verwendung einer modellprĂ€diktiven Steuerung (MPC) entwickelt. Es wird zudem ein hybrides AC/DC-Microgrid-Konzept vorgeschlagen, um die Steuerungsentscheidungen, die von den AnsĂ€tzen der GerĂ€teplanung und der hybriden Umschaltung getroffen werden, auf der Grundlage eines linearen Programmierungsoptimierungsrahmens zu berĂŒcksichtigen. Die vorgeschlagenen Optimierungskriterien verbessern die Zufriedenheit der Verbraucher, minimieren Netzabschaltungen und senken die Gesamtenergiekosten durch den Einsatz von kostengĂŒnstiger und sauberer Energieerzeugung. Verschiedene Beispiele aus einer Fallstudie demonstrieren den Einsatz des entwickelten EMS und der Entwurfsmethodik
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