Models for the modern power grid

This article reviews different kinds of models for the electric power grid that can be used to understand the modern power system, the smart grid. From the physical network to abstract energy markets, we identify in the literature different aspects that co-determine the spatio-temporal multilayer dynamics of power system. We start our review by showing how the generation, transmission and distribution characteristics of the traditional power grids are already subject to complex behaviour appearing as a result of the the interplay between dynamics of the nodes and topology, namely synchronisation and cascade effects. When dealing with smart grids, the system complexity increases even more: on top of the physical network of power lines and controllable sources of electricity, the modernisation brings information networks, renewable intermittent generation, market liberalisation, prosumers, among other aspects. In this case, we forecast a dynamical co-evolution of the smart grid and other kind of networked systems that cannot be understood isolated. This review compiles recent results that model electric power grids as complex systems, going beyond pure technological aspects. From this perspective, we then indicate possible ways to incorporate the diverse co-evolving systems into the smart grid model using, for example, network theory and multi-agent simulation.Comment: Submitted to EPJ-ST Power Grids, May 201

Energy system optimisation and smart technologies - a social sciences and humanities annotated bibliography

The challenge: * Systems perspectives on energy involve a holistic view on balancing demand and supply; system optimisation can support security of supply, affordability, sustainability and profitability. * A central, and relatively recent, element of system optimisation is the move towards smart grids, and smart technologies, which concern interconnection of system elements usually through the internet. As well as increasing the resilience of the network, it is hoped this will help “citizens take ownership of the energy transition [and] benefit from new technologies”. * ‘Smartification’ of the energy system introduces a range of new societal conditions and consequences. The aim: * European energy policy has so far mainly relied on research from Science, Technology Engineering and Mathematics (STEM) disciplines. Energy-related Social Sciences and Humanities (energy-SSH) have been significantly underrepresented. The aim of this bibliography is to give policymakers a selected yet broad impression of the SSH research community focusing on ‘energy system optimisation and smart technologies’. Wherever possible, policy deductions or research and innovation recommendations are mentioned. Coverage: * Disciplines covered in this bibliography are broadly representative of the current SSH research community in the area, with a slight bias towards Economics, Sociology and Science & Technology Studies. Nevertheless, robust accounts from Psychology, Politics, Ethnography, Development, Environmental Social Science, Geography, Planning, Law, History and other fields are also included. * Geographically, research presented is primarily from Western and Northern Europe, but with diversity across these regions, and inclusion of some Eastern European and non-European contributions. * Techno-economic accounts are very highly represented in the field of energy system optimisation and smart technologies, a fact highlighted by researchers themselves. Much of this research concentrates on financial cost/benefit of smart grid and technical design, while approaches focusing on social practices or user-centric design are increasing but still underrepresented. The latter were deliberately given higher visibility in this bibliography. Key findings: * Numerous papers presented here focus on how questions of smart technology diffusion, innovation, and adoption might be shifted away from monetary incentives or cost/benefit analyses of technologies. * A unifying message across many topics and disciplines - from energy justice or socio-technical scenarios, to Economics or Ethnography - is that co-operation between techno-economic and SSH approaches needs more attention and is crucial for successful smart grid realisation. * Another important debate for SSH researchers is the deconstruction of overly optimistic visions of smart societies. Many authors urge caution in considering the (financial and social) costs and benefits of smart technologies for all of society, including issues of privacy intrusion. There are calls for more research on both policy initiatives, preferably targeting the community level, and clear communication strategies which fully consider these aspects

Smart Local Energy Systems (SLES): A framework for exploring transition, context, and impacts

Energy systems globally are becoming increasingly decentralised; experiencing new types of loads; incorporating digital or “smart” technologies; and seeing the demand side engage in new ways. These changes impact on the management and regulation of future energy systems and question how they will support a socially equitable, acceptable, net-zero transition. This paper couples a meta-narrative literature review with expert interviews to explore how socio-technical regimes associated with centralised systems of provision (i.e. the prevailing paradigm in many countries around the world) differ to those of smart local energy systems (SLES). Findings show how SLES regimes incorporate niche technologies, business models and governance structures to enable new forms of localised operation and optimisation (e.g. automated network management), smarter decision making and planning, by new actors (e.g. local authorities, other local stakeholders), and engaging users in new ways. Through this they are expected to deliver on a wide range of outcomes, both within the SLES boundary and to the wider system. However, there may be trade-offs between outcomes due to pressures for change originating from competing actors (e.g. landscape vs. incumbents in the regime); understanding the mapping between different outcomes, SLES elements and their interconnections will be key to unlocking wider benefits

Self-organising smart grid architectures for cyber-security

PhD ThesisCurrent conventional power systems consist of large-scale centralised generation and unidirectional power flow from generation to demand. This vision for power system design is being challenged by the need to satisfy the energy trilemma, as the system is required to be sustainable, available and secure. Emerging technologies are restructuring the power system; the addition of distributed generation, energy storage and active participation of customers are changing the roles and requirements of the distribution network. Increased controllability and monitoring requirements combined with an increase in controllable technologies has played a pivotal role in the transition towards smart grids. The smart grid concept features a large amount of sensing and monitoring equipment sharing large volumes of information. This increased reliance on the ICT infrastructure, raises the importance of cyber-security due to the number of vulnerabilities which can be exploited by an adversary. The aim of this research was to address the issue of cyber-security within a smart grid context through the application of self-organising communication architectures. The work examined the relevance and potential for self-organisation when performing voltage control in the presence of a denial of service attack event. The devised self-organising architecture used techniques adapted from a range of research domains including underwater sensor networks, wireless communications and smart-vehicle tracking applications. These components were redesigned for a smart grid application and supported by the development of a fuzzy based decision making engine. A multi-agent system was selected as the source platform for delivering the self-organising architecture The application of self-organisation for cyber-security within a smart grid context is a novel research area and one which presents a wide range of potential benefits for a future power system. The results indicated that the developed self-organising architecture was able to avoid control deterioration during an attack event involving up to 24% of the customer population. Furthermore, the system also reduces the communication load on the agents involved in the architecture and demonstrated wider reaching benefits beyond performing voltage control

Scalable pathways to net zero carbon in the UK higher education sector: A systematic review of smart energy systems in university campuses

The following literature review sets out the state-of-the-art research relating to smart building principles and smart energy systems in UK higher education university campuses. The paper begins by discussing the carbon impact of the sector and the concept of ‘smart campuses' applied to the sector in the context of decarbonisation. Opportunities and challenges associated with integrating smart energy systems at the university campus from a policy and technical perspective are then discussed. This is followed by a review of building and campus-scale frameworks supporting a transition to smart energy campuses using the BPIE’ Smart Buildings' framework. The paper finds that the complexity of achieving net-zero carbon emissions for new and existing higher education buildings and energy systems can be addressed with the adoption of ‘smart building principles' and integrating 'smartness' into their energy systems. Several universities in the UK and worldwide are integrating smart services and Information and Communication Technologies (ICT) in their operations following the smart campus premise. At the building level, existing frameworks often create conceptual roadmaps for the smart building premise or propose technical implementation and assessment methods. At university campus scale, implementation typically comes through single-vector interventions, and only few examples exist that propose a multi-vector approach. Comparisons of the drivers and the decision-making process are made, with carbon and cost reduction being the most prominent from leveraging distributed energy generation. Therefore, this study identified the need for a comprehensive technical or policy framework to drive the uptake of the smart energy campus, aiming to bring together the holistic value of smart energy campuses

A Systematic Literature Review of Peer-to-Peer, Community Self-Consumption, and Transactive Energy Market Models

Capper, T., Gorbatcheva, A., Mustafa, M. A., Bahloul, M., Schwidtal, J. M., Chitchyan, R., Andoni, M., Robu, V., Montakhabi, M., Scott, I., Francis, C., Mbavarira, T., Espana, J. M., & Kiesling, L. (2021). A Systematic Literature Review of Peer-to-Peer, Community Self-Consumption, and Transactive Energy Market Models. Social Science Research Network (SSRN), Elsevier. https://doi.org/10.2139/ssrn.3959620Peer-to-peer and transactive energy markets, and community or collective self-consumption offer new models for trading energy locally. Over the past 10 years there has been significant growth in the amount of academic literature and trial projects examining how these energy trading models might function. This systematic literature review of 139 peer-reviewed journal articles examines the market designs used in these energy trading models. The Business Ecosystem Architecture Modelling framework is used to extract information about the market models used in the literature and identify differences and similarities between the models. This paper identifies six archetypal market designs and three archetypal auction mechanisms used in markets presented in the reviewed literature. It classifies the types of commodities being traded, the benefits of the markets and other features such as the types of grid models. Finally, this paper identifies five evidence gaps which need future research before these markets can be widely adopted.publishersversionpublishe

A rapid review on community connected microgrids

As the population of urban areas continues to grow, and construction of multi-unit developments surges in response, building energy use demand has increased accordingly and solutions are needed to offset electricity used from the grid. Renewable energy systems in the form of microgrids, and grid-connected solar PV-storage are considered primary solutions for powering residential developments. The primary objectives for commissioning such systems include significant electricity cost reductions and carbon emissions abatement. Despite the proliferation of renewables, the uptake of solar and battery storage systems in communities and multi-residential buildings are less researched in the literature, and many uncertainties remain in terms of providing an optimal solution. This literature review uses the rapid review technique, an industry and societal issue-based version of the systematic literature review, to identify the case for microgrids for multi-residential buildings and communities. The study describes the rapid review methodology in detail and discusses and examines the configurations and methodologies for microgrids

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

Local Market Mechanisms: how Local Markets can shape the Energy Transition

Europe has embarked on a journey towards a zero-emission system, with the power system at its core. From electricity generation to electric vehicles, the European power system must transform into an interconnected, intelligent network. To achieve this vision, active user participation is crucial, ensuring transparency, efficiency, and inclusivity. Thus, Europe has increasingly focused on the concept of markets in all their facets. This thesis seeks to answer the following questions: How can markets, often considered abstract and accessible only to high-level users, be integrated for end-users? How can market mechanisms be leveraged across various phases of the electrical system? Why is a market- driven approach essential for solving network congestions and even influencing planning? These questions shape the core of this research. The analysis unfolds in three layers, each aligned with milestones leading to 2050. The first explores how market mechanisms can be integrated into system operator development plans, enhancing system resilience in the face of changes. In this regard, this step addresses the question of how a market can be integrated into the development plans of a network and how network planning can account for uncertainties. Finally, the analysis highlights the importance of sector coupling in network planning, proposing a study in which various energy vectors lead to a multi-energy system. According to the roadmap to 2030, this layer demonstrates how markets can manage several components of the gas and electrical network. Finally, even though the robust optimisation increases the final cost in the market, it allows to cover the system operator from uncertainties. The second step delves into the concept of network congestion. While congestion management is primarily the domain of operators, it explores how technical and economic collaboration between operators and system users, via flexibility markets, can enhance resilience amid demand uncertainties and aggressive market behaviours. In addition to flexibility markets, other congestion markets are proposed, some radically different, like locational marginal pricing, and others more innovative, such as redispatching markets for distribution. Building upon the first analysis, this section addresses questions of how various energy vectors can be used not only to meet demand but also to manage the uncertainties associated with each resource. Consequently, this second part revisits the concept of sector coupling, demonstrating how various energy vectors can be managed through flexibility markets to resolve network congestion while simultaneously handling uncertainties related to different vectors. The results demonstrate the usefulness of the flexibility market in managing the sector coupling and the uncertainties related to several energy vectors. The third and most innovative step proposes energy and service markets for low-voltage users, employing distributed ledger technology. Since this step highlights topics that are currently too innovative to be realized, this third section offers a comparative study between centralised and decentralised markets using blockchain technology, highlighting which aspects of distributed ledger technology deserve attention and which aspects of low-voltage markets need revision. The results show that the blockchain technology is still in the early stage of its evolution, and several improvements are needed to fully apply this technology into real-world applications. To sum up, this thesis explores the evolving role of markets in the energy transition. Its insights are aimed at assisting system operators and network planners in effectively integrating market mechanisms at all levels of

Multi-agent reinforcement learning for the coordination of residential energy flexibility

This thesis investigates whether residential energy flexibility can be coordinated without sharing personal data at scale to achieve a positive impact on energy users and the grid. To tackle climate change, energy uses are being electrified at pace, just as electricity is increasingly provided by non-dispatchable renewable energy sources. These shifts increase the requirements for demand-side flexibility. Despite the potential of residential energy to provide such flexibility, it has remained largely untapped due to cost, social acceptance, and technical barriers. This thesis investigates the use of multi-agent reinforcement learning to overcome these challenges. This thesis presents a novel testing environment, which models electric vehicles, space heating, and flexible household loads in a distribution network. Additionally, a generative adversarial network-based data generator is developed to obtain realistic training and testing data. Experiments conducted in this environment showed that standard independent learners fail to coordinate in the partially observable stochastic environment. To address this, additional coordination mechanisms are proposed for agents to practise coordination in a centralised simulated rehearsal, ahead of fully decentralised implementation. Two such coordination mechanisms are proposed: optimisation-informed independent learning, and a centralised but factored critic network. In the former, agents lean from omniscient convex optimisation results ahead of fully decentralised coordination. This enables cooperation at scale where standard independent learners under partial observability could not be coordinated. In the latter, agents employ a deep neural factorisation network to learn to assess their impact on global rewards. This approach delivers comparable performance for four agents and more, with a 34-fold speed improvement for 30 agents and only first-order computational time growth. Finally, the impacts of implementing implicit coordination using these multi- agent reinforcement learning methodologies are modelled. It is observed that even without explicit grid constraint management, cooperating energy users reduce the likelihood of voltage deviations. The cooperative management of voltage constraints could be further promoted by the MARL policies, whereby their likelihood could be reduced by 43.08% relative to an uncoordinated baseline, albeit with trade-offs in other costs. However, while this thesis demonstrates the technical feasibility of MARL-based cooperation, further market mechanisms are required to reward all participants for their cooperation