Evaluation der Maßnahmen zur Umsetzung der Vorschläge der Hartz-Kommission: Arbeitspaket 1, Wirksamkeit der Instrumente; Modul 1c: Arbeitsbeschaffungsmaßnahmen ; zweiter Bericht

Das Fazit aus den Untersuchungen zu Effektivität und Effizienz des ABM-Einsatzes in den Jahren 1999-2004 lautet: Eine klare Befürwortung oder Ablehnung dieses arbeitsmarktpolitischen Förderinstrumentes lässt sich aus den ermittelten Befunden nicht ableiten. Der Gesetzgeber wie auch die Akteure vor Ort haben mit dem ABM-Einsatz im Wesentlichen fünf Ziele verfolgt - Integration in den allgemeinen Arbeitsmarkt, Erhalt bzw. Wiedererlangung der Beschäftigungsfähigkeit, Umsetzung strukturwirksamer Maßnahmen, temporäre Schaffung von Marktersatz sowie Inklusion besonders förderungsbedürftiger Personen. Die dabei gesetzte Zielhierarchie unterscheidet sich von Akteur zu Akteur und hat sich im Zeitverlauf zudem verändert: Während für den Gesetzgeber bis 2003 die Arbeitsmarktintegration im Vordergrund stand, ist mit der Neuausrichtung von ABM in 2004 der Marktersatz das vorrangige Ziel. Für die Akteure vor Ort war die Arbeitsmarktintegration im gesamten Untersuchungszeitraum 2000-2004 nur in einigen Fällen das vorrangige Ziel; zumeist wurde vielmehr von einer Gleichrangigkeit der fünf Ziele ausgegangen. Allerdings zeigten sich deutliche regionale Unterschiede: In Ostdeutschland hatten die Ziele Marktersatz, Beschäftigungsfähigkeit und Strukturwirksamkeit ein besonderes Gewicht, in Westdeutschland die Zielgruppeninklusion und die Arbeitsmarktintegration. Die Untersuchungen zur Zielerreichung erbrachten positive Befunde hinsichtlich der Ziele Beschäftigungsfähigkeit, Strukturwirksamkeit und Zielgruppeninklusion, wobei strukturwirksame Effekte von ABM vor allem für Ostdeutschland zu konstatieren sind. In Bezug auf das Ziel der Arbeitsmarktintegration sind die Befunde ambivalent: Die Nettointegrationseffekte von ABM fallen, kurzfristig betrachtet, sowohl in Ost- als auch Westdeutschland negativ aus. Allerdings sind mit der größeren Zielgruppenschärfe und dem verringertem Umfang des ABM-Einsatzes im Zeitverlauf relative Verbesserungen zu konstatieren. Für Westdeutschland sind langfristig positive Nettointegrationseffekte festzustellen. Die angestellten Kosten-Nutzen-Betrachtungen erlauben in einer gesamtgesellschaftlichen Bilanz weder die Schlussfolgerung, dass ABM generell effizient noch grundsätzlich ineffizient sind. Allerdings zeigen die bisherigen Ergebnisse einer akteursbezogenen Analyse, dass die Bundesagentur für Arbeit beim ABM-Einsatz ein "Nettozahler" ist, während andere Akteure, vor allem die ABM-Beschäftigten bzw. die zuvor Arbeitslosen und die Kommunen, eher als "Nettoempfänger" charakterisiert werden können. (IAB2

Multi Agent Control Based Energy Optimization of a Prosumer Household and a Community with Bidirectional Electric Vehicles

Prosumer households with photovoltaic systems face the problem of occasionally generating electricity that cannot be used within the house but must be fed into the electricity grid. This is not desired since with changing policies in Germany, the feed-in tariff has been reduced considerably and the cost of power consumed from the grid has increased significantly. It’s advisable to consume the solar power instead of feeding it into the grid. To achieve this, the excess solar power can be consumed by an electric vehicle present at the household. Additionally, this system can supply power to the household if solar power is insufficient. This study presents how bidirectional electric vehicles can optimize the self-consumption of solar photovoltaic energy and increase the self-sufficiency of the loads in a household and a community (i.e., group of households) by a hierarchical structure of control systems: car, household and community. They are optimizing power flow locally and additionally consider information from the over- and underlying controllers. The car controller is a bidirectional charging station where the electric vehicle is connected, it takes user preferences that are used by the household controller to perform power optimization by handling the mismatch between generation and demand. The community level controller performs an on-the-top optimization which reduces the power flow between the community and the electricity grid. The effect of the proposed system is investigated on a reference distribution grid simulated in the software package DIgSILENT PowerFactory whereas the control framework is developed in Python. Real load and photovoltaic profiles are used to execute the simulations. The results show that there is a 40% and 36% increase in the self-consumption and selfsufficiency on a household level whereas a 51% and 31% increase on a community level when the coordinated control system is implemented

Multi Agent Control Based Energy Optimization of a Prosumer Household and a Community with Bidirectional Electric Vehicles

Prosumer households with photovoltaic systems face the problem of occasionally generating electricity that cannot be used within the house but must be fed into the electricity grid. This is not desired since with changing policies in Germany, the feed-in tariff has been reduced considerably and the cost of power consumed from the grid has increased significantly. It’s advisable to consume the solar power instead of feeding it into the grid. To achieve this, the excess solar power can be consumed by an electric vehicle present at the household. Additionally, this system can supply power to the household if solar power is insufficient. This study presents how bidirectional electric vehicles can optimize the self-consumption of solar photovoltaic energy and increase the self-sufficiency of the loads in a household and a community (i.e., group of households) by a hierarchical structure of control systems: car, household and community. They are optimizing power flow locally and additionally consider information from the over- and underlying controllers. The car controller is a bidirectional charging station where the electric vehicle is connected, it takes user preferences that are used by the household controller to perform power optimization by handling the mismatch between generation and demand. The community level controller performs an on-the-top optimization which reduces the power flow between the community and the electricity grid. The effect of the proposed system is investigated on a reference distribution grid simulated in the software package DIgSILENT PowerFactory whereas the control framework is developed in Python. Real load and photovoltaic profiles are used to execute the simulations. The results show that there is a 40% and 36% increase in the self-consumption and selfsufficiency on a household level whereas a 51% and 31% increase on a community level when the coordinated control system is implemented

Integration von Wasserstoffenergiespeichern - Nutzen für Stromnetze?

Der Beitrag gibt einen Überblick über die Anforderungen an eine netzorientierte Integration von Wasserstoffenergiespeichern und -komponenten in das Stromnetz. Vor dem Hintergrund einer allgemeinen Definition von Wasserstoffenergiespeichern und möglichen Komponenten werden der zukünftige Wasserstoffbedarf, Elektrolyseleistung und Speicherkapazität vorgestellt, der in verschiedenen aktuellen Gesamtsystemstudien mit Ziel der Klimaneutralität im Jahr 2045 bestimmt wurde. Durch den angestrebten beschleunigten Ausbau erneuerbarer Erzeugungskapazität ergibt sich weiterer Netzausbaubedarf zusätzlich zu dem Ausbaubedarf durch bisherige Netzengpässen. Elektrolyseanlagen könnten also bereits im heutigen Stromnetz zur verbesserten Integration von EE-Anlagen eingesetzt werden. Derzeit bestehen allerdings kaum Anreize für netzdienliche Allokation und Betrieb von Elektrolyse bzw. Power-to-Gas Anlagen. Als Praxisbeispiele werden zwei mögliche Standorte für Wasserstoffanlagen aus zwei aktuellen Forschungsprojekten HyCavMobil und dem Innovationslabor Wasserstoffregion Nordwest (H2-ReNoWe) vorgestellt. Anhand von Stromnetzmodellen wird die Integration von Elektrolyseanlagen an diesen Standorten im derzeitigen Hoch- bzw. Höchstspannungsnetz untersucht

Optimal Power Dispatch in Energy Systems Considering Grid Constraints

In this research, an energy system dispatch optimization model is employed. It includes an iterative approach for generating grid constraints, which is decoupled from the linear unit commitment problem. The dispatch of all energy carriers in the system is optimized while considering the physical electrical grid limits

Distributed Co-Simulation of Networked Hardware-in-the-Loop Power Systems

The paper presents a method to extend existing co-simulation frameworks to emulate quasi-dynamic behavior of real grid components in a grid simulator using a distributed networked co-simulation platform. The platform uses generic socket communication to exchange data between real grid components and the grid simulator. The framework utilizes event triggered models to enable data exchange between grid components and the platform over user datagram protocol (UDP)/IP interface. This framework has its use-case in smart grids as well as microgrids for analyzing, monitoring and control applications where it is impractical to model each component separately inside the grid simulator. Intrinsic communication delays including jitter is handled using built-in fallback strategies inside the framework itself. As a proof-of-concept, a co-simulation between a simulated low-voltage (LV) grid model and an emulation of a simplified Photovoltaic (PV) model is presented. The behavior of PV emulator is integrated in the grid simulator using socket communication. The primary focus of this work is to validate the extended framework. The effect of network delays on the stability of the distributed co-simulation setup are also investigated

Simulation of Incidental Distribution Generation Curtailment to Maximize the Integration of Renewable Energy Generation in Power Systems

Power system security is increasingly endangered due to novel power flow situations caused by the growing integration of distributed generation. Consequently, grid operators are forced to request the curtailment of distributed generators to ensure the compliance with operational limits more often. This research proposes a framework to simulate the incidental amount of renewable energy curtailment based on load flow analysis of the network. Real data from a 110 kV distribution network located in Germany are used to validate the proposed framework by implementing best practice curtailment approaches. Furthermore, novel operational concepts are investigated to improve the practical implementation of distributed generation curtailment. Specifically, smaller curtailment level increments, coordinated selection methods, and an extension of the n-1 security criterion are analyzed. Moreover, combinations of these concepts are considered to depict interdependencies between several operational aspects. The results quantify the potential of the proposed concepts to improve established grid operation practices by minimizing distributed generation curtailment and, thus, maximizing power system integration of renewable energies. In particular, the extension of the n-1 criterion offers significant potential to reduce curtailment by up to 94.8% through a more efficient utilization of grid capacities

Technical and economic analysis of curative actions in distribution networks utilizing battery energy storage systems

Renewable energy generation curtailment increases due to more frequently occurring congestions in power system operation. Post-contingency curative congestion management actions can reduce the necessity of renewable energy curtailment by enabling a more efficient utilization of transmission capacities. In this research, the potential of curative actions to substitute renewable energy curtailment is studied considering technical and economic criteria. Therefore, a novel pricing methodology for the market-based provision of curative actions is introduced. The method is based on the security constraint optimal power flow technique. Simulations are carried out on a modified version of the IEEE 14-bus network and a real-world 110 kV distribution network. Battery energy storage systems are implemented as an exemplary technology to provide curative actions. The developed method achieves a positive power system impact by reducing operational costs and maximizing renewable energy integration. Also, novel business models for merchant-owned battery energy storage systems are unveiled. The provision of curative actions further proves to be competitive to established battery storage applications. Additionally, results of different grid expansion scenarios of the 110 kV network reveal the need to coordinate power system planning and operation more extensively in the future

Generating worst-case scenarios by randomly distributing loads for risk assessment in low voltage residential electricity grids

In order to assess the capacity of low voltage electricity grids different grid operation cases are usually analyzed. These cases are used to identify weaknesses in the grid, evaluate the risks involved and subsequently facilitate the integration of new loads such as electric vehicles or heat pumps which are joining these grids in an increasing degree. This study suggests a random load allocation algorithm to create realistic worst-case scenarios for grid operation without the need for historical load data or reverting to load profiles. This is achieved by distributing loads asymmetrically across all three phases so that they comply with grid codes and burden the local transformer moderately. In this way, a multitude of feasible load scenarios is generated and evaluated. A metric is proposed to select those scenarios which lead to a critical operation state of the grid. The generated worst-case scenarios can be used to evaluate the potential capacity and risks of integrating new consumers into grids. This is demonstrated in a use case where electric vehicles are integrated into the investigated grid at half of all connection points. The Analysis shows that the grid is additionally stressed and the reinforcement of cables or charge management would be required to facilitate the safe operation of the grid with additional loads

Forecast of Renewable Curtailment in Distribution Grids Considering Uncertainties

Renewable energies curtailment induced by grid congestions increase due to grown renewable energies integration and the resulting mismatch of grid expansion. Short-term predictions for curtailment can help to increase the efficiency of its management. This paper proposes a novel, holistic approach of a short-term curtailment prediction for distribution grids. The load flow calculations for congestion detection are realized by taking different operational security criteria into account, whereas the models for the node-injections are adjusted to the characteristic of each grid node specifically. The determination of required curtailment based on the resulting congestions considers uncertainties of component loading and its corresponding probability. The forecast model is validated using an actual 110 kV distribution grid located in Germany. In order to meet the requirements of a forecast model designed for operational business, prediction accuracy, and its greatest source of error are analyzed. Furthermore, a suitable length of training data is investigated. Results indicate that a six month time period for maintenance gains the highest accuracy. Curtailment prediction accuracy is better for transmission system operator components than for distribution system operator components, but the Słrensen Dice factor for the aggregated grid shows a high match of historic and predicted curtailment with a value of 0.84 and a low error for curtailed energy, which makes 2.23% of the historic curtailed energy. The model is a promising approach, which can contribute to improvement of curtailment strategies and enable valuable insight into distribution grids