Demand Side Management in Small Power Systems – The Estonian Case Study

The increasing amount of stochastic power generation connected to power system increases the need for additional ancillary reserves. Most of today's electricity consumers are relatively flexible and easily controllable,providing an already existing supplement for traditional power system ancillary services. The flexibility of loads depends on the number, type and size of consumers. In small power systems utilizing loads for power system services pose different challenges for the system operator than in larger systems. The main challenge lies in developing a business case and incentives for the customers to participate in such services. This paper discusses and analyses the Estonian three most energy intensive economic sectors potential for demand side response from a small power system point of view. Generally, it is determined that demand side flexibility provides incentives not only for the power system operator but also for the customer who is able optimize its processes to gain higher economic and energy efficiency and at the same time provide flexibility for the system operator

The Future European Energy System

This open access book analyzes the transition toward a low-carbon energy system in Europe under the aspects of flexibility and technological progress. By covering the main energy sectors – including the industry, residential, tertiary and transport sector as well as the heating and electricity sector – the analysis assesses flexibility requirements in a cross-sectoral energy system with high shares of renewable energies. The contributing authors – all European energy experts – apply models and tools from various research fields, including techno-economic learning, fundamental energy system modeling, and environmental and social life cycle as well as health impact assessment, to develop an innovative and comprehensive energy models system (EMS). Moreover, the contributions examine renewable penetrations and their contributions to climate change mitigation, and the impacts of available technologies on the energy system. Given its scope, the book appeals to researchers studying energy systems and markets, professionals and policymakers of the energy industry and readers interested in the transformation to a low-carbon energy system in Europe

Flexibility options in a decarbonising iron and steel industry

The decarbonisation of the iron and steel industry is expected to significantly increase its electricity consumption due to higher levels of electrification and the partial shift to hydrogen as iron reductant. With its batch processes, this industry offers large potential for the application of demand response strategies to achieve electricity cost savings. Previous research has primarily focused on investigating the demand response potential for currently operating manufacturing processes and partly for future low-carbon processes. This study aims to consolidate this knowledge and apply it to a modelling analysis that investigates the demand response potential of two new low-carbon technologies: the hydrogen-based direct reduction of iron with electric arc furnace technology (H2-DRI-EAF) and the blast furnace basic oxygen furnace technology retrofitted with carbon capture (BF-BOF-CCUS). A cost optimisation approach is applied to plant configurations with varying parameters relevant for flexibility, such as electrolyser and storage sizes, and in the context of future electricity prices. Multiple price profiles are selected to encompass uncertainties on the development of the power system. The potential for a H2-DRI-EAF plant is 3–27 times higher than for a BF-BOF-CCUS, with electricity costs savings potentials of 35% and 3%, respectively. The study finds that electricity prices have the most significant impact on the profitability of investing in electrolyser overcapacities, which enable operating costs reduction. Therefore, the profitability of these investments are strongly dependent on future power system configurations

Combined heat and power plants in decarbonized energy systems: Techno-economics of carbon capture and flexibility services at the plant, city and regional levels

Our present energy system is the main driver of climate change. Variable renewable electricity generation and carbon dioxide removal (CDR) are key technologies in the transformation to a sustainable energy system, but their broad implementation implies challenges related to energy system flexibility and energy requirements of CDR technologies. The aim of this thesis is to investigate the potential and incentives for combined heat and power (CHP) plants in Sweden to contribute with CDR and flexibility services in the energy system. A techno-economic assessment scheme that considers variability in boundary conditions, such as electricity prices, and includes the CHP plant, city, and regional energy system levels is developed and applied. System optimization modeling and process-level case studies are performed to investigate how CHP plant flexibility measures are utilized and valued, and to estimate the cost and potential of CDR from Swedish CHP plants.The results indicate a large potential for Swedish CHP plants to contribute to CDR, with at least 10 MtCO2/year being available for capture and storage. The realizability of this potential is challenged by the cost of carbon capture which increases notably for CHP plants that are small and have few full load hours. CHP plants can cost-effectively contribute with flexibility provision in the studied electricity system, although the impact on the total system is limited, as the installed capacity of CHP plants is small relative to the magnitude of net load variability. From a plant perspective, the plant revenue can increase if the operation is scheduled to follow electricity price variability, but this requires a significant level of price volatility and access to large-scale thermal energy storage for maximum benefit. The fuel price has a strong impact on the competitiveness of biomass-fired CHP plants on a regional level, that compete with power-to-heat technologies in the district heating sector. In contrast, in cities, there are stronger incentives for CHP plants as heat producers regardless of how the surrounding energy system and market prices develop, due to a limited availability of other technology options and a limited grid connection capacity to drive power-to-heat

Developing a Decision Making Approach for District Cooling Systems Design using Multi-objective Optimization

Energy consumption rates have been dramatically increasing on a global scale within the last few decades. A significant role in this increase is subjected by the recent high temperature levels especially at summer time which caused a rapid increase in the air conditioning demands. Such phenomena can be clearly observed in developing countries, especially those in hot climate regions, where people depend mainly on conventional air conditioning systems. These systems often show poor performance and thus negatively impact the environment which in turn contributes to global warming phenomena. In recent years, the demand for urban or district cooling technologies and networks has been increasing significantly as an alternative to conventional systems due to their higher efficiency and improved ecological impact. However, to obtain an efficient design for district cooling systems is a complex task that requires considering a wide range of cooling technologies, various network layout configuration possibilities, and several energy resources to be integrated. Thus, critical decisions have to be made regarding a variety of opportunities, options and technologies. The main objective of this thesis is to develop a tool to obtain preliminary design configurations and operation patterns for district cooling energy systems by performing roughly detailed optimizations and further, to introduce a decision-making approach to help decision makers in evaluating the economic aspects and environmental performance of urban cooling systems at an early design stage. Different aspects of the subject have been investigated in the literature by several researchers. A brief survey of the state of the art was carried out and revealed that mathematical programming models were the most common and successful technique for configuring and designing cooling systems for urban areas. As an outcome of the survey, multi objective optimization models were decided to be utilized to support the decision-making process. Hence, a multi objective optimization model has been developed to address the complicated issue of decision-making when designing a cooling system for an urban area or district. The model aims to optimize several elements of a cooling system such as: cooling network, cooling technologies, capacity and location of system equipment. In addition, various energy resources have been taken into consideration as well as different solar technologies such as: trough solar concentrators, vacuum solar collectors and PV panels. The model was developed based on the mixed integer linear programming method (MILP) and implemented using GAMS language. Two case studies were investigated using the developed model. The first case study consists of seven buildings representing a residential district while the second case study was a university campus district dominated by non-residential buildings. The study was carried out for several groups of scenarios investigating certain design parameters and operation conditions such as: Available area, production plant location, cold storage location constraints, piping prices, investment cost, constant and variable electricity tariffs, solar energy integration policy, waste heat availability, load shifting strategies, and the effect of outdoor temperature in hot regions on the district cooling system performance. The investigation consisted of three stages, with total annual cost and CO2 emissions being the first and second single objective optimization stages. The third stage was a multi objective optimization combining the earlier two single objectives. Later on, non-dominated solutions, i.e. Pareto solutions, were generated by obtaining several multi objective optimization scenarios based on the decision-makers’ preferences. Eventually, a decision-making approach was developed to help decision-makers in selecting a specific solution that best fits the designers’ or decision makers’ desires, based on the difference between the Utopia and Nadir values, i.e. total annual cost and CO2 emissions obtained at the single optimization stages.Die Energieverbrauchsraten haben in den letzten Jahrzehnten auf globaler Ebene dramatisch zugenommen. Diese Erhöhung ist zu einem großen Teil in den jüngst hohen Temperaturniveaus, vor allem in der Sommerzeit, begründet, die einen starken Anstieg der Nachfrage nach Klimaanlagen verursachen. Solche Ereignisse sind deutlich in Entwicklungsländern zu beobachten, vor allem in heißen Klimaregionen, wo Menschen vor allem konventionelle Klimaanlagensysteme benutzen. Diese Systeme verfügen meist über eine ineffiziente Leistungsfähigkeit und wirken sich somit negativ auf die Umwelt aus, was wiederum zur globalen Erwärmung beiträgt. In den letzten Jahren ist die Nachfrage nach Stadt- oder Fernkältetechnologien und -Netzwerken als Alternative zu konventionellen Systemen aufgrund ihrer höheren Effizienz und besseren ökologischen Verträglichkeit satrk gestiegen. Ein effizientes Design für Fernkühlsysteme zu erhalten, ist allerdings eine komplexe Aufgabe, die die Integration einer breite Palette von Kühltechnologien, verschiedener Konfigurationsmöglichkeiten von Netzwerk-Layouts und unterschiedlicher Energiequellen erfordert. Hierfür ist das Treffen kritischer Entscheidungen hinsichtlich einer Vielzahl von Möglichkeiten, Optionen und Technologien unabdingbar. Das Hauptziel dieser Arbeit ist es, ein Werkzeug zu entwickeln, das vorläufige Design-Konfigurationen und Betriebsmuster für Fernkälteenergiesysteme liefert, indem aureichend detaillierte Optimierungen durchgeführt werden. Zudem soll auch ein Ansatz zur Entscheidungsfindung vorgestellt werden, der Entscheidungsträger in einem frühen Planungsstadium bei der Bewertung städtischer Kühlungssysteme hinsichtlich der wirtschaftlichen Aspekte und Umweltleistung unterstützen soll. Unterschiedliche Aspekte dieser Problemstellung wurden in der Literatur von verschiedenen Forschern untersucht. Eine kurze Analyse des derzeitigen Stands der Technik ergab, dass mathematische Programmiermodelle die am weitesten verbreitete und erfolgreichste Methode für die Konfiguration und Gestaltung von Kühlsystemen für städtische Gebiete sind. Ein weiteres Ergebnis der Analyse war die Festlegung von Mehrzieloptimierungs-Modelles für die Unterstützung des Entscheidungsprozesses. Darauf basierend wurde im Rahmen der vorliegenden Arbeit ein Mehrzieloptimierungs-Modell für die Lösung des komplexen Entscheidungsfindungsprozesses bei der Gestaltung eines Kühlsystems für ein Stadtgebiet oder einen Bezirk entwickelt. Das Modell zielt darauf ab, mehrere Elemente des Kühlsystems zu optimieren, wie beispielsweise Kühlnetzwerke, Kühltechnologien sowie Kapazität und Lage der Systemtechnik. Zusätzlich werden verschiedene Energiequellen, auch solare wie Solarkonzentratoren, Vakuum-Solarkollektoren und PV-Module, berücksichtigt. Das Modell wurde auf Basis der gemischt-ganzzahlig linearen Optimierung (MILP) entwickelt und in GAMS Sprache implementiert. Zwei Fallstudien wurden mit dem entwickelten Modell untersucht. Die erste Fallstudie besteht aus sieben Gebäuden, die ein Wohnviertel darstellen, während die zweite Fallstudie einen Universitätscampus dominiert von Nichtwohngebäuden repräsentiert. Die Untersuchung wurde für mehrere Gruppen von Szenarien durchgeführt, wobei bestimmte Designparameter und Betriebsbedingungen überprüft werden, wie zum Beispiel die zur Verfügung stehende Fläche, Lage der Kühlanlage, örtliche Restriktionen der Kältespeicherung, Rohrpreise, Investitionskosten, konstante und variable Stromtarife, Strategie zur Einbindung der Solarenergie, Verfügbarkeit von Abwärme, Strategien der Lastenverschiebung, und die Wirkung der Außentemperatur in heißen Regionen auf die Leistung des Kühlsystems. Die Untersuchung bestand aus drei Stufen, wobei die jährlichen Gesamtkosten und die CO2-Emissionen die erste und zweite Einzelzieloptimierungsstufe darstellen. Die dritte Stufe war ein Pareto-Optimierung, die die beiden ersten Ziele kombiniert. Im Anschluss wurden nicht-dominante Lösungen, also Pareto-Lösungen, erzeugt, indem mehrere Pareto-Optimierungs-Szenarien basierend auf den Präferenzen der Entscheidungsträger abgebildet wurden. Schließlich wurde ein Ansatz zur Entscheidungsfindung entwickelt, um Entscheidungsträger bei der Auswahl einer bestimmten Lösung zu unterstützen, die am besten den Präferenzen des Planers oder des Entscheidungsträgers enstpricht, basierend auf der Differenz der Utopia und Nadir Werte, d.h. der jährlichen Gesamtkosten und CO2-Emissionen, die Ergebnis der einzelnen Optimierungsstufen sind

Optimization of Sustainable Urban Energy Systems: Model Development and Application

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

Grid Capacity Issues with Distributed Generation

Climate change is more evident than ever as reflected in The European union's environmental directives which say that the carbon emission must be reduced by 20% and 20% of the used energy must come from renewable energy sources until 2020. In Germany political decision has been made that the nuclear power will be replaced by renewable energy in long term. The purpose of the Master Thesis is to investigate how high penetration of photovoltaic affects the electrical grid on a distribution level concerning active power and map the potential for different renewable energy sources in Germany. Using a simulation model and grid data received from E.ON the goal is to map what problems that may occur and evaluate different measures for solving the problems. The data and information collection have been done by interviews and literature studies. The simulation program that has been used is DIGSILENT Power Factory where all the simulations have been static ones. Different load profiles for households have been handed by an internal source in E.ON and evaluated before inserted in the simulations. The studied measures for balancing the active power are battery storages of different technologies, load shifting and biomass power plants. The investigated battery technologies were Li-ion batteries, Lead-acid batteries and Vanadium Redox flow batteries. The main purpose of evaluating three different technologies is the costs for each technology. Battery storages and load shifting have been used for all load profiles, the biomass power plants have been used while the PV output has been low. The results showed that Germany is able to increase its wind and PV output in the future. Implementation of battery storage and load shifting will balance the grid and less power will be taken from the transmission grid. Load shifting is very hard to analyze and utilize but assumed to have low capital costs. Load shifting in households is also a very immature technology. Storing energy is the most effective measure for balancing the active power because of the valuable property to store energy and use when it is needed. But the costs of battery storages are high even if no costs of power electronics were included. Implementation of a 10 MW biomass power plant will balance the active power while low production of PV and high demand

Energy System Optimization including Carbon-Negative Technologies for a High-Density Mixed-Use Development

I In this paper, we use the ‘energy hub’ optimization model to perform a multi-objective analysis on a high-density mixed-use development (termed the ‘mothership’) under different scenarios and compare these results to appropriate base cases. These scenarios explore how the optimal energy system changes under different assumptions, including a high carbon tax, net metering, net-zero emissions and negative emissions, as well as two different electrical grid carbon intensities. We also include ‘carbon negative’ technologies involving biochar production, to explore the role that such processes can play in reducing the net emissions of energy systems. The annualized cost and total emissions of the mothership with a simple energy system are 4 and 8.7 times lower respectively than a base case using single detached homes housing the same population, due to the more efficient form and hence lower energy demand. Of the scenarios examined, it is notable that the case with the lowest annualized cost was one with a net-zero carbon emissions restriction. This gave an annualized cost of CAD 2.98M, which 36% lower than the base case annualized cost of CAD 4.66M. This relied upon the carbon negative production and sale of biochar. All scenarios examined had lower annualized costs than the base cases with many of the cases having negative operating costs (generating profit) due to the sale of renewable energy or carbon credits. This illustrates that the integration of renewable energy technologies is not only beneficial for reducing emissions but can also provide an income stream. These results give hope that suitably optimized urban developments may be able to implement low cost solutions that have zero net emissions