Flexibilität im zukünftigen Elektrizitätsmarkt - Analyse von Herausforderungen in Koordination, Komplementarität und Vorhersagbarkeit

Im Elektrizitätsmarkt der Zukunft wird der Strom zunehmend von Erneuerbare-Energien-Anlagen erzeugt. Dadurch erfolgt die Einspeisung zunehmend entkoppelt von der Nachfrage und in niedrigen Spannungsebenen. Dies erfordert in erheblichem Umfang einen Umbau des Elektrizitätsnetzes. Eine mögliche Alternative zu einem teuren Netzausbau ist eine stärkere Orientierung des Verbrauchs an der Erzeugung bzw. an der aktuellen, lokalen Netzauslastungssituation. Um lokalen Netzüberlastungen entgegenzuwirken, ist eine separate Preisbildung auf einem lokalen Markt ökonomisch naheliegend, weil hier ein lokaler Preis die lokale Knappheitssituation widerspiegeln kann. Schon heute sind technische Anlagen wie intelligente Steuerungseinheiten für Haushaltsgeräte oder Messanlagen zum Monitoring in kritischen Netzbereichen verfügbar. Eine Orientierung der Nachfrage an der lokalen Netzauslastung bedeutet jedoch eine erhebliche Veränderung von Verhaltensmustern und Anlagenfahrweisen, die ohne entsprechende Anreize kaum zu erwarten sind. Zugleich sind lokale Preissignale bislang im europäischen Elektrizitätsmarkt nicht vorhanden. Vor diesem Hintergrund untersucht diese Arbeit, wie lokale Preise im Falle von Netzknappheitssituationen gestaltet werden könnten, wie potentiell flexible Netznutzer auf Preisanreize reagieren können und welche Folgen ein solches Marktdesign für die verschiedenen Teilnehmer des Elektrizitätsmarktes haben kann. Bei den flexiblen Netznutzern liegt ein besonderer Fokus hierbei auf Batteriespeichern und Wärmepumpen als Anlagen mit großem Verschiebepotential, die in der Niederspannung angeschlossen sind. Dabei ist von besonderem Interesse, wieviel Flexibilität durch diese Anlagen tatsächlich bereitgestellt werden kann bzw. welche Hindernisse durch anlagenspezifische Restriktionen gegeben sind. Insbesondere wird auch der Einfluss unsicherer Inputfaktoren (wie Preise und Wetter) betrachtet. Die erzielten Ergebnisse zeigen, dass Preissignale, die einfache Netzengpässe abbilden, mit einfachen und effizienten Algorithmen ermittelt werden können, auch wenn der Systemoperator nicht über vollständige Information verfügt. Es wird aber auch deutlich, dass bei einem Marktdesign mit lokalen Preisanreizen verschiedene Hemmnisse auf praktischer Ebene zu überwinden sind: Auf Seiten der flexiblen Netznutzer ist festzustellen, dass a) unsichere Preise die Profitabilität von teuren Batteriespeichern sehr in Frage stellen und b) unsichere Wetterbedingungen für Gebäude mit Wärmepumpenheizung schon bei einem Planungshorizont von einem Tag zu Verletzungen der Komfortgrenzen führen, wenn keine Anpassung der Fahrweise an das aktuelle Wetter möglich ist. Mit Blick auf die gesamte Marktausgestaltung zeigt sich, dass die Vorteilhaftigkeit von Netzengpass-bedingten lokalen Preisen begrenzt ist (zumindest für das betrachtete Beispiel eines zukünftigen Niederspannungsnetzbereiches). Des Weiteren sind die Verteilung des Systemvorteils auf die verschiedenen Netznutzer und die Ausgestaltung von Kompensationsregelungen kritische Fragen, da politische Festlegungen hier über Gewinner und Verlierer unter den jeweiligen Netznutzergruppen entscheiden.In future electricity systems, power will be generated more and more from renewable energy sources. Thus, infeed will increasingly occur independently from power demand and at lower voltage levels. This will require a substantial redesign of electricity networks at the distribution grid level. Instead of rebuilding and expanding important parts of the network, an adaptation of demand according to the available infeed or the actual local congestion situation may be envisaged. In case of congestions, a separate price mechanism for a local market is economically appropriate, as the local scarcity or surplus can then be reflected by a local price. Technical preconditions such as smart control devices for household equipment or units for a monitoring of critical network assets are already available. Yet, adjusting consumption patterns according to the local grid situations corresponds to a substantial change of behavior and appliance operation schemes. Hence this is not likely to happen without suitable price incentives. On the other hand, such local prices are currently not provided in the European electricity market design. Against this background, this thesis investigates how local prices may be determined in case of congestion situations, how flexible grid users may respond to these price signals and which consequences are to be expected for various market participants under such a market design. Among the flexible grid users, the focus is thereby laid on battery storage systems and heat pumps, which are applications with a high demand shifting potential installed at the low voltage grid level. How much flexibility these units may provide and which impediments result from device-specific restrictions is of particular interest in that context. Special emphasis is also laid on the impact of uncertain input factors (as prices and weather). Results show that prices reflecting simple congestion situations may be obtained through simple and efficient algorithms even if full information is not available to the system operator. But it also becomes obvious that a market design with local price incentives raises various challenges from a practical point of view: For the flexible grid users, the results indicate a) that the profitability of battery storage systems is much lower with uncertain prices and b) that uncertain weather conditions lead to violations of comfort restrictions in case of buildings with heat-pumps if a day-ahead planning without later adjustments to actual weather is assumed. With respect to the market design itself, results indicate that efficiency gains resulting from congestion-based local prices are rather low (at least for the considered example). Moreover, the redistribution effects of local prices and compensation payments turn out to be a critical issue, as the corresponding political choices define winners and losers among the various groups of grid users

Parametric study of transport aircraft systems cost and weight

The results of a NASA study to develop production cost estimating relationships (CERs) and weight estimating relationships (WERs) for commercial and military transport aircraft at the system level are presented. The systems considered correspond to the standard weight groups defined in Military Standard 1374 and are listed. These systems make up a complete aircraft exclusive of engines. The CER for each system (or CERs in several cases) utilize weight as the key parameter. Weights may be determined from detailed weight statements, if available, or by using the WERs developed, which are based on technical and performance characteristics generally available during preliminary design. The CERs that were developed provide a very useful tool for making preliminary estimates of the production cost of an aircraft. Likewise, the WERs provide a very useful tool for making preliminary estimates of the weight of aircraft based on conceptual design information

Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks

In this era of advanced distribution automation technologies, demand response is becoming an important tool for electricity network management. The available flexible loads can efficiently help in alleviating the network constraints and achieving demand-supply balance. Therefore, this forms the rationale behind this paper, which aims to implement a multi-agent system framework in order to achieve flexible price-based demand response. A genetic algorithm-based multi-objective optimization technique is applied to determine the optimal locations and the amount of required demand reduction in order to keep the network within statutory limits. The methodology is based on probabilistic estimation of the granularity of total available flexible demand from shiftable home appliances in each low-voltage feeder. Moreover, an optimal decision making for the start time of appliances upon receiving a real-time price signal is proposed. This is accomplished by considering the willingness to participate as well as price demand elasticity of the different clusters of customers. To fully demonstrate the feasibility and effectiveness of the proposed framework, a modified IEEE 69 bus distribution network comprising 1824 low voltage residential customers has been implemented and analyzed

Assessment of novel distributed control techniques to address network constraints with demand side management

The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid.The development of sustainable generation, a reliable electricity supply and affordable tariffs are the primary requirements to address the uncertainties in different future energy scenarios. Due to the predicted increase in Distributed Generation (DG) and load profile changes in future scenarios, there are significant operational and planning challenges facing netwrok operators. These changes in the power system distribution network require a new Active Network Management (ANM) control system to manage distribution constraint issues such as thermal rating, voltage, and fault levels. The future smart grid focuses on harnessing the control potential from demand side via bidirectional power flow, transparent information communication, and contractual customer participation. Demand Side Management (DSM) is considered as one of the effective solutions to defer network capacity reinforcement, increase energy efficiency, facilitate renewable access, and implement low carbon energy strategy. From the Distribution Network Operator's (DNO) perspective, the control opportunity from Demand Response (DR) and Decentralized Energy Resource (DER) contributes on capacity investment reduction, energy efficiency, and enable low carbon technologies. This thesis develops a new decentralized control system for dealing effectively with the constraint issues in the Medium Voltage (MV) distribution network. In the decentralized control system, two novel control approaches are proposed to autonomously relieve the network thermal constraint via DNO's direct control of the real power in network components during the operation period. The first approach, Demand Response for Power Flow Management (DR-PFM), implements the DSM peak clipping control of Active Demand (AD), whilst the second approach, Hybrid Control for Power Flow Management (HC-PFM), implements the hybrid control of both AD and DER. The novelty of these two new control algorithms consists in the application of a Constraint Satisfaction Problem (CSP) based programming model on decision making of the real power curtailment to relieve the network thermal overload. In the Constraint Programming (CP) model, three constraints are identified: a preference constraint, and a network constraint. The control approaches effectively solve the above constraint problem in the CSP model within 5 seconds' time response. The control performance is influenced by the pre-determined variable, domain and constraint settings. These novel control approaches take advantages on flexible control, fast response and demand participation enabling in the future smart grid