ABSTRACT This paper presents a prototyping framework that supports decisions on the design and deployment of prosumer‐oriented control strategies in low‐voltage (LV) grids. Unlike existing approaches that focus either on operational detail or on scalable planning studies, the framework combines conceptualisation, planning‐oriented and operational modelling within a single data‐driven process. It structures strategy development and establishes a KPI basis that captures grid‐related, customer‐related and practical aspects, thereby supporting data‐informed assessments of control strategies, such as smart electric vehicle (EV) charging, and their implications for grid planning and operation. A data‐driven case study on private EV charging illustrates the capabilities of the framework. Several practically relevant charging strategies are developed and assessed across a large set of LV grids using complementary simulation methods. In the case study, grid‐oriented strategies yield favourable outcomes, reducing the occurrence of critical grid situations significantly, for example, undervoltages by up to 50%. Price‐based concepts with grid‐dependent behaviour can also mitigate load peaks when parameterised appropriately. These strategies also contribute to delaying grid reinforcement and extension. A simplified bidirectional variant, focusing on local voltage‐based active power adjustments, provides initial insights into the grid‐supportive potential of vehicle‐to‐grid approaches. The case study demonstrates how the framework supports multiperspective KPI‐based evaluation and thereby strengthens decision‐making for the integration of prosumers into LV grids and for data‐driven smart charging concepts.

As energy systems are digitized to maintain and improve security of supply with a high amount of fluctuating renewable generation, highly complex cyber-physical energy systems (CPES) arise. Holistic planning of these systems, including reliability and resilience analysis as well as investment decision support, needs tools for calculating and simulating energy and information networks and their interactions. The work at hand presents a novel Python-based open-source tool for modeling information networks called “pandaict”. It is designed to be compatible with existing open-source tools for energy system modeling and is tested in a co-simulation in conjunction with those.

Control strategies for prosumers in low voltage grids are gaining importance for ensuring the safe and reliable grid operation. These strategies have unique features and impacts on electrical grids, making selection challenging. This paper introduces a prototyping framework tailored to the development and analysis of control strategies, which focus on adapting power set points of prosumers within low voltage grids to tackle this problem. The framework encompasses conceptualization and simulations, in which the development and analysis of control strategies are covered. Thus, they are also prepared for further refinement in lab and field tests. Throughout this, aspects related to the effect of control strategies on electrical grids, including grid planning and operation, are covered. This paper presents the framework, covering general information on the development and analysis elements as well as details on the utilized modeling approaches and evaluation methods. Application examples of all framework elements illustrate their possibilities. For this, a practically relevant control strategy is selected, which has a positive impact on grid planning and grid operation by reducing the occurrence of critical grid situations. The strategy requires collaboration among system components, some regulatory updates, and data related to price curves and load behavior.

The planned massive increase of producers and consumers such as electric vehicles, heat pumps and photovoltaic systems in distribution grids will lead to new challenges in the electrical power system. These can include grid congestions at the low voltage level but also at higher voltage levels. Control strategies can enable the efficient use of flexibilities and therefore help mitigate upcoming problems. However, they need to be evaluated carefully before their application in the energy system to avoid any unwanted effects and to choose the most fitting strategy for each application. In this publication, a Python-based modular simulation tool for developing and analysing control strategies for prosumers, which uses pandapower (Thurner et al. 2018), is presented. It is intended for sequential simulations and enables detailed operational analyses, which include evaluating the influence on grid situations, the necessary behavior of energy system components, required measurements and communications. This publication also gives an overview of control strategies, existing simulation tools, how the modular simulation tool fits in and illustrates its functionalities in an application example, which further highlights its versatility and efficiency. Time series simulations with the tool allow analyses regarding the effect of control strategies on power flow results. Moreover, the simulation tool also facilitates evaluating the behavior of energy system components (e.g. distribution substations), necessary communications and measurements as well as any faults that might occur.

The pan-European electric grid evolves towards a network with a wide diversity of (micro-)energy systems spread throughout all voltage levels. At the transmission level, this poses new challenges for cross-border energy exchange. At the distribution level small-scale generation, storages, and controllable loads offer flexibility available for provision of ancillary services. Meeting the EU energy supply policy while optimally operating the network under these conditions needs advanced TSO-DSO collaboration schemes. Taking this into account, this paper proposes a methodology which combines application of local flexibility management and control with central grid operation planning in order to meet planning criteria for future network operation. We discuss motivation and methodology process and present results of a proof-of-concept where the methodology was applied to a synthetic benchmark grid model.

This publication presents a co-simulation framework that enables joint simulation experiments by multiple remote laboratories for analyses of smart grid energy systems that can also include power hardware-in-the-loop. It introduces a proof of concept where individual parts of an example electrical grid are modelled at three geographically distributed Fraunhofer Institutes. The models differ greatl...

In this paper, it is investigated if an exchange of grid-related data in TSO/DSO system use cases of the EU-project TDX-ASSIST can be sufficiently performed with the CIM-CGMES version 2.4.15 data model. For those use cases which cannot be mapped onto CGMES, novel extensions of the data model are proposed. The proposals are a work in progress state and will be finalized in the upcoming deliverables of TDX-ASSIST. Our work aims at a wide usage of CGMES to exchange grid-related data.

Converting today's energy supply to a system relying on renewable energy sources (RES) represents an essential goal of the German energy transition. As a prerequisite, however, volatile RES need to be exploited more efficiently. To raise awareness of end customers for this challenge, a gamification based energy management approach is proposed in this paper. The concept aims at motivating consumers to harmonize their electrical consumption with a volatile generation of RES by applying game design elements to the energy related context. To test the approach, a corresponding field test is conducted. The evaluation of the data collected during the field test shows that the consumers' electricity demand can be influenced by intrinsic incentives in order to shift their electrical consumption into times with high RES availability.

The goal of the INTERPLAN project is to provide an INTEgrated opeRation PLANning tool towards the pan-European network, to support the European Union in reaching the expected low-carbon targets, while maintaining the network security. A methodology for proper representation of a “clustered” model of the pan-European network will be provided, with the aim to generate grid equivalents as a growing library able to cover all relevant system connectivity possibilities occurring in the real grid, by addressing operational issues at all network levels (transmission, distribution and TSOs-DSOs interfaces). In this perspective, the chosen top-down approach will lead to an "integrated" tool, both in terms of voltage levels, going from high voltage down to low voltage up to end user, and in terms of building a bridge between static, long-term planning and considering operational issues by introducing controllers in the operation planning. Proper cluster and interface controllers will be developed to intervene in presence of criticalities, by exploiting the flexibility potentials throughout the grid.

The Nobel Grid project is developing information technology to integrate and fully utilise flexibility potentials of demand response and end-customer operated distributed energy resources (DERs) in the electric energy system. As key part of an according technical solution, the authors develop the ‘smart meter extension (SMX)’ for rapid development and deployment of new functionalities at end-customer premises. The document at hand reports the project results achieved so far. After summarising their approach, they introduce the Nobel Grid architecture. They then detail the architecture focusing on the SMX. Finally, they show how the SMX can be used to implement two example smart grid functions, highlighting the SMX's capabilities as a modular interface for software-driven DER integration.

Private households constitute a considerable share of Europe's electricity consumption. The current electricity distribution system treats them as effectively passive individual units. In the future, however, users of the electricity grid will be involved more actively in the grid operation and can become part of intelligent networked collaborations. They can then contribute the demand and supply ...

Within the European project Smart House / Smart Grids (SH/SG), contemporary technologies for automated demand response (ADR) in private smart houses and automated load and generation control were developed and tested. At the same time, impacts of ADR and distributed generation (DG) on low-voltage grid operation were researched by means of software simulations in a real urban network. Research questions included whether ADR can be used for lowering grid losses, voltage control and increasing the accommodation ceiling of DG. The paper at hand shortly introduces the basic energy management concept as well as simulation goals. It then presents and discusses simulation results regarding operation of an ADR system with high amounts of DG in a grid area in the city of Mannheim.

The high heterogeneity in smart house infrastructures as well as in the smart grid poses several challenges when it comes into developing approaches for energy efficiency. Consequently, several monitoring and control approaches are underway, and although they share the common goal of optimizing energy usage, they are fundamentally different at design and operational level. Therefore, we consider of high importance to investigate if they can be integrated and, more importantly, we provide common services to emerging enterprise applications that seek to hide the existing heterogeneity. We present here our motivation and efforts in bringing together the PowerMatcher, BEMI and the Magic system.

For both offline planning and online operation of smart grids, the distribution system operator (DSO) and/or the aggregator will be faced with the challenge of dispatching a large number of controllable resources of different types i.e. intermittent renewable energy supplies (RES), dispatchable micro sources, storage units and demand side management loads. This paper presents a grid and a market agent hosting the tasks of virtual power plant (VPP) operators, retailers, aggregators, DSO, energy brokers and any emerging role or actor in the smart grid. On the one hand, an extension of the distribution system operation via the grid agent will be presented, and on the other hand, a novel ICT infrastructure facilitating the aggregation mechanisms will be described Finally, various technical issues regarding the development of such a model will be presented and the advantages of the approach chosen will be assessed.

The current electricity distribution system treats home and working environments as consisting of isolated and passive individual energy-consuming units. This severely limits the achieved energy efficiency and sustainability, as it ignores the potential delivered by homes, offices, and commercial buildings which are seen as intelligent networked collaborations where energy can be intelligently managed. The Smarthouse/SmartGrid project is developing an ICT architecture introducing a holistic concept and technology for smart houses as they are situated and intelligently managed within their broader environment. Smart homes and buildings are considered as (i) proactive customers that (ii) negotiate and collaborate as an intelligent network in (iii) close interaction with their external environment. Three interrelated field experiments validate and demonstrate the ICT architecture in real world home and working environments. The initial results show that the newly developed control strategies and network architectures (i) enhance energy efficiency, (ii) improve efficient management of local power grids (e.g. improve network load factors) and (iii) enable the integration of a larger amount of renewable energy resources with less carbon emission impact.

Treating homes, offices and commercial buildings as intelligently networked collaborations can contribute to enhancing the efficient use of energy. When smart houses are able to communicate, interact and negotiate with both customers and energy devices in the local grid, the energy consumption can be better adapted to the available energy supply, especially when the proportion of variable renewable generation is high. Several efforts focus on integrating the smart houses and the emerging smart grids. We consider that a highly heterogeneous infrastructure will be in place and no one-size-fits-all solution will prevail. Therefore, we present here our efforts focusing not only on designing a framework that will enable the gluing of various approaches via a service-enabled architecture, but also discuss on the trials of these.

Energy management and energy efficiency for small electricity customers as part of a Smart Grid strategy are gaining significance with increasing share of renewable and distributed generation. The concept presented provides a single Gateway between the customer and the grid on top of which a variety of applications shall be executable, which access costumer devices, user displays, smart meters, measuring data, pricing data etc.

Der Preis eines Gutes ergibt sich am freien Markt aus dem Verhältnis von Angebot und Nachfrage. Die Nachfrage im Energiemarkt, also der Energieverbrauch, schwankt permanent. Tagsüber wird mehr Strom verbraucht als nachts und besonders um die Mittagszeit und am Abend im Winter ist die Nachfrage besonders hoch. Das Angebot im Energiemarkt, also die Stromerzeugung, wird entsprechend der schwankenden Nachfrage geregelt. Allerdings erhöht der Ausbau von erneuerbaren, fluktuierenden Energien, wie Windturbinen und Photovoltaik-Anlagen, den Anteil einer nicht steuerbaren Schwankung auf der Angebotsseite.

In this paper we present a strategic approach for energy management of distributed electric resources in low-voltage networks with special consideration of services for the distribution system operator (DSO). A system comprising Bidirectional Energy Management Interfaces (BEMIs) developed and tested at ISET, carrying out decentralized decisions and grid supervision is introduced. The paper presents operational states and possible applications of the proposed system in the distribution grid as well as a simulation designed for researching the system’s behaviour. Finally first results are given on the simulation-based development of an algorithm implementing a new approach for incentive-based voltage control, which is one of the system’s advanced applications.

Radical changes in the energy system, at the lower network level, will require integration of smart houses in the smart grid in order to realize the full potential. Introduction of renewables, an increase of distributed generation, and the trend towards an all-electric infrastructure lead to an increase in complexity, system management effort and cost that the smart grid should provide an answer for. This calls for houses that are pro-active and flexible participants in the smart grid. The home will no longer be an extension of a utility or energy service provider, but serve as an autonomous building block in a smart grid and determine autonomously how and to whom it will accept from and deliver energy services on the smart grid.