An overview of grid-edge control with the digital transformation

Distribution networks are evolving to become more responsive with increasing integration of distributed energy resources (DERs) and digital transformation at the grid edges. This evolution imposes many challenges to the operation of the network, which then calls for new control and operation paradigms. Among others, a so-called grid-edge control is emerging to harmonise the coexistence of the grid control system and DER’s autonomous control. This paper provides a comprehensive overview of the grid-edge control with various control architectures, layers, and strategies. The challenges and opportunities for such an approach at the grid edge with the integration of DERs and digital transformation are summarised. The potential solutions to support the network operation by using the inherent controllability of DER and the availability of the digital transformation at the grid edges are discussed

Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

L'abstract è presente nell'allegato / the abstract is in the attachmen

Background, Systematic Review, Challenges and Outlook

Publisher Copyright: © 2013 IEEE. This research is supported by the Digital Manufacturing and Design Training Network (DiManD) project funded by the European Union through the Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2018) under grant agreement no. 814078The concept of smart manufacturing has attracted huge attention in the last years as an answer to the increasing complexity, heterogeneity, and dynamism of manufacturing ecosystems. This vision embraces the notion of autonomous and self-organized elements, capable of self-management and self-decision-making under a context-aware and intelligent infrastructure. While dealing with dynamic and uncertain environments, these solutions are also contributing to generating social impact and introducing sustainability into the industrial equation thanks to the development of task-specific resources that can be easily adapted, re-used, and shared. A lot of research under the context of self-organization in smart manufacturing has been produced in the last decade considering different methodologies and developed under different contexts. Most of these works are still in the conceptual or experimental stage and have been developed under different application scenarios. Thus, it is necessary to evaluate their design principles and potentiate their results. The objective of this paper is threefold. First, to introduce the main ideas behind self-organization in smart manufacturing. Then, through a systematic literature review, describe the current status in terms of technological and implementation details, mechanisms used, and some of the potential future research directions. Finally, the presentation of an outlook that summarizes the main results of this work and their interrelation to facilitate the development of self-organized manufacturing solutions. By providing a holistic overview of the field, we expect that this work can be used by academics and practitioners as a guide to generate awareness of possible requirements, industrial challenges, and opportunities that future self-organizing solutions can have towards a smart manufacturing transition.publishersversionpublishe

Centralised and decentralised control of active distribution systems: models, algorithms and applications.

Power system were traditionally planned and designed by assuming unidirectional power flows from power stations to loads. Nowadays, several factors (e.g., liberalization of the electricity market, need of increased reliability, and environmental issues) lead to a situation where electricity is produced also downstream the transmission level. Connecting generators to the distribution networks could provide several benefits to the whole system, but also technical and safety problems that must be faced. On the other hand, the loads are changing: new loads like electric vehicles and electric pumps are appearing in the network and they are going to modify the electricity consumption; while traditional loads are designed in order to be more efficient, but with additional functions or special features that require more energy. For all these reasons, since 2005, the interest on Smart Grid (electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers – in order to efficiently deliver sustainable, economic and secure electricity supplies) increased. In this framework different techniques to control, operate and thereby integrate distributed energy resources into the network have been analysed and developed. The first technique designed is a centralised control, characterised by a central controller (Distribution Management System) that gathers information like the measures of the main electric parameters, energy price and indicates to DERs (Active Loads, Generators, Energy Storage) the optimal set points minimizing the system cost, subject to technical and economical constraints. The second technique developed is a decentralised control using Multi Agent Systems (MAS). This type of control has been designed and developed for the direct control of active demand and plug-in electric vehicles, managed by the Aggregator, entrusted by the end users to change their consumption habits according to their needs. Moreover, the proposed decentralised MAS, with the active participation of small consumers in the electricity system, support the integration of the Electric Vehicles in the LV distribution network and reduce its harmful impact on voltage regulation. The techniques and the algorithms proposed by the author are analysed and applied in representative Italian Distribution networks, by taking into account the development of the distribution system according to the load profile evolution, providing several examples to underline the importance of the Active Management for deferring the reinforcement of the existing grid infrastructures, increasing the hosting capacity of the networ

Centralised and decentralised control of active distribution systems: models, algorithms and applications.

Power system were traditionally planned and designed by assuming unidirectional power flows from power stations to loads. Nowadays, several factors (e.g., liberalization of the electricity market, need of increased reliability, and environmental issues) lead to a situation where electricity is produced also downstream the transmission level. Connecting generators to the distribution networks could provide several benefits to the whole system, but also technical and safety problems that must be faced. On the other hand, the loads are changing: new loads like electric vehicles and electric pumps are appearing in the network and they are going to modify the electricity consumption; while traditional loads are designed in order to be more efficient, but with additional functions or special features that require more energy. For all these reasons, since 2005, the interest on Smart Grid (electricity network that can intelligently integrate the actions of all users connected to it – generators, consumers – in order to efficiently deliver sustainable, economic and secure electricity supplies) increased. In this framework different techniques to control, operate and thereby integrate distributed energy resources into the network have been analysed and developed. The first technique designed is a centralised control, characterised by a central controller (Distribution Management System) that gathers information like the measures of the main electric parameters, energy price and indicates to DERs (Active Loads, Generators, Energy Storage) the optimal set points minimizing the system cost, subject to technical and economical constraints. The second technique developed is a decentralised control using Multi Agent Systems (MAS). This type of control has been designed and developed for the direct control of active demand and plug-in electric vehicles, managed by the Aggregator, entrusted by the end users to change their consumption habits according to their needs. Moreover, the proposed decentralised MAS, with the active participation of small consumers in the electricity system, support the integration of the Electric Vehicles in the LV distribution network and reduce its harmful impact on voltage regulation. The techniques and the algorithms proposed by the author are analysed and applied in representative Italian Distribution networks, by taking into account the development of the distribution system according to the load profile evolution, providing several examples to underline the importance of the Active Management for deferring the reinforcement of the existing grid infrastructures, increasing the hosting capacity of the networ

Location Awareness in Multi-Agent Control of Distributed Energy Resources

The integration of Distributed Energy Resource (DER) technologies such as heat pumps, electric vehicles and small-scale generation into the electricity grid at the household level is limited by technical constraints. This work argues that location is an important aspect for the control and integration of DER and that network topology can inferred without the use of a centralised network model. It addresses DER integration challenges by presenting a novel approach that uses a decentralised multi-agent system where equipment controllers learn and use their location within the low-voltage section of the power system. Models of electrical networks exhibiting technical constraints were developed. Through theoretical analysis and real network data collection, various sources of location data were identified and new geographical and electrical techniques were developed for deriving network topology using Global Positioning System (GPS) and 24-hour voltage logs. The multi-agent system paradigm and societal structures were examined as an approach to a multi-stakeholder domain and congregations were used as an aid to decentralisation in a non-hierarchical, non-market-based approach. Through formal description of the agent attitude INTEND2, the novel technique of Intention Transfer was applied to an agent congregation to provide an opt-in, collaborative system. Test facilities for multi-agent systems were developed and culminated in a new embedded controller test platform that integrated a real-time dynamic electrical network simulator to provide a full-feedback system integrated with control hardware. Finally, a multi-agent control system was developed and implemented that used location data in providing demand-side response to a voltage excursion, with the goals of improving power quality, reducing generator disconnections, and deferring network reinforcement. The resulting communicating and self-organising energy agent community, as demonstrated on a unique hardware-in-the-loop platform, provides an application model and test facility to inspire agent-based, location-aware smart grid applications across the power systems domain