1,720,979 research outputs found
Transactive Energy Systems in Decentralized Autonomous Renewable Energy Communities
No full textIn the near future, renewable energy communities will play a crucial role in the transition to a cleaner energy system and the reduction of carbon emissions in the electricity sector. In order to ensure a broad base of participation among consumer and producers (prosumers), it is necessary to develop new business models and governance tools for energy communities, and, in this context, blockchain technology may have several applications in the implementation and management of these communities. This paper proposes a decentralized autonomous organization model for renewable energy communities, which will enable a transactive energy scenario for the community governance process. In order to illustrate the usefulness of the methodology, an example of the proposed approach with a distributed organization process for an automated local energy market among community members is presented
Distributed Ledger Based Management of Local Energy Markets with a Federated Learning Approach
No full textThis paper presents an innovative methodology for managing a local electric market based on artificial intelligence techniques, integrated with a distributed ledger technology platform. The methodology allows an aggregate of users, for example constituting a local energy community, to optimize its energy costs by adopting a local energy market that manages its controllable energy resources in real-time. To achieve this result, the electricity market is managed by means of a distributed ledger platform used for both the certified recording of market operators' bids and for the sharing of a market-solving deep neural network algorithm. This market-solving platform is continuously adapted to the external changes in energy production, consumption and prices. By sharing the state of the system by means of the distributed ledger, the proposed platform allows every operator to locally define its optimal production/consumption and adapting its status according to the community energy needs. The proposed platform has been implemented with a computer-based simulation software and successfully tested for a day-long, 1-minute timestep. The results presented in the paper shown the usefulness of the tool developed in a renewable energy community real case scenario
Smart Grid Optimization with Blockchain Based Decentralized Genetic Algorithm
No full textFuture smart grids are expected to be equipped with a multitude of distributed and connected devices, able to measure, manage and control the state of the grid. In this view, the presence of distributed devices, with spare computational capabilities, allows the development of Distributed Machine Learning (ML) algorithms, aiming at performing the analyses and optimizations needed to ensure the correct grid operation. This work aims to present a new Decentralized Genetic Algorithm (DGA) approach able to perform, form a global perspective, the optimization of the network operation, showing resilience to malfunctioning and cyber-attacks to the distributed Internet of Things (IoT) devices. This result has been achieved by implementing an immutable, certified and decentralized blockchain based master ledger, which serves as the coordinating node among all the distributed computing devices. The proposed methodology has been tested considering an optimal scheduling problem in a local MV network, with high penetration of Distributed Renewable Generation and Controllable Loads
Impact on Electricity Consumption and Market Pricing of Energy and Ancillary Services during Pandemic of COVID-19 in Italy
Full text linkAt the moment of writing, in Italy, there is an ongoing pandemic of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Its outbreak is leading to severe global socioeconomic disruptions impacting on all economic sectors from tourism, industry and the tertiary sector, up to the operational and opening of public offices, the closure of schools and the organization of families. Measures adopted by the Italian government to deal with the COVID-19 emergency have had direct effects both on people’s daily lives and on the activity of most industrial and commercial production companies. These changes have been unequivocally reflected also on the Italian electricity system, which has shown unprecedented behavior in terms of both energy consumption and volume and subsequently, in the observed share of renewable and conventional production technologies. The goal of this study is to show the impact on the power industry of all the restrictions and lockdown of the activities in Italy and to discuss the effects of COVID-19 outbreak on the bulk power system and the entire electricity sector. In particular, the consequences on load profiles, electricity consumption and market prices in Italy, including the environmental aspects, are examined
Optimal positioning of storage systems in microgrids based on complex networks centrality measures
Full text linkWe propose a criterion based on complex networks centrality metrics to identify the optimal position of Energy Storage Systems in power networks. To this aim we study the relation between centrality metrics and voltage fluctuations in power grids in presence of high penetration of renewable energy sources and storage systems. For testing purposes we consider two prototypical IEEE networks and we compute the correlation between node centrality (namely Eigenvector, Closeness, Pagerank, Betweenness) and voltage fluctuations in presence of intermittent renewable energy generators and intermittent loads measured from domestic users. We show that the topological characteristics of the power networks are able to identify the optimal positioning of active and reactive power compensators (such as energy storage systems) used to reduce voltage fluctuations according to the common quality of service standards. Results show that, among the different metrics, eigenvector centrality shows a statistically significant exponential correlation with the reduction of voltage fluctuations. This finding confirms the technical know-how for which storage systems are heuristically positioned far from supply reactive nodes. This also represents an advantage both in terms of computational time, and in terms of planning of wide resilient networks, where a careful positioning of storage systems is needed, especially in a scenario of interconnected microgrids where intermittent distributed energy sources (such as wind or solar) are fully deployed
A Decentralized Market Solver for Local Energy Communities
No full textThe progressive development of local energy communities requires the reorganization of the energy production and consumption, with a new energy system in which the technical and commercial decision-making process need to be decentralized from central authorities to distributed entities properly coordinated. This will be increasingly aided by the spread of IoT systems capable of interacting among distributed resources. The technical and commercial energy management burden will be then shared among cooperating IoT devices, which will perform the necessary optimization and control operations. In this context, a Decentralized Genetic Algorithm (DGA) methodology, able to perform a wide spectrum of power system optimizations in a fully decentralized fashion is introduced. This paper aim at developing a DGA management procedure, tested considering a model for a local energy market and an automated distributed resource scheduling in a local energy community. The testing is performed through a HIL experimental setup, which proves the effectiveness of the methodology proposed, as well as a Blockchain platfor
Blockchain-Based Hardware-in-the-Loop Simulation of a Decentralized Controller for Local Energy Communities
Full text linkThe development of local energy communities observed in the last years requires the reorganization of energy consumption and production. In these newly considered energy systems, the commercial and technical decision processes should be decentralized in order to reduce their maintenance costs. This will be allowed by the progressive spreading of IoT systems capable of interacting with distributed energy resources, giving local sources the ability to be optimally coordinated in terms of network and energy management. In this context, this paper presents a decentralized controlling architecture that performs a wide spectrum of power system optimization procedures oriented to the local market management. The controller framework is based on a decentralized genetic algorithm. The manuscript describes the structure of the tool and its validation, considering an automated distributed resource scheduling for local energy markets. The simulation platform permits implementing the blockchain-based trading process and the automated distributed resource scheduling. The effectiveness of the tool proposed is discussed with a hardware-in-the-loop case study
A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility
Full text linkWe study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas
The digitalization of peer-to-peer electricity trading in energy communities
No full textOne of the motivating factors for developing energy communities is to create an opportunity for peer-to-peer trading among the members. Smart meters, Internet of Things devices, distributed ledger, and digitalization enable energy communities based on renewable energy production to thrive. The local energy market participants can trade energy and provide services to the upstream distribution and transmission system operators. This chapter introduces the local energy market concept describing enabling technologies. A laboratory-scale local energy community operated by P2P and blockchain is used to show the feasibility and benefits of this new technology
Community core detection in transportation networks
No full textThis work analyzes methods for the identification and the stability under perturbation of a territorial community structure with specific reference to transportation networks. We considered networks of commuters for a city and an insular region. In both cases, we have studied the distribution of commuters’ trips (i.e., home-to-work trips and vice versa). The identification and stability of the communities’ cores are linked to the land-use distribution within the zone system, and therefore their proper definition may be useful to transport planners
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