Blockchain-Based Hardware-in-the-Loop Simulation of a Decentralized Controller for Local Energy Communities

The 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

Uncertainty Reduction on Flexibility Services Provision from DER by Resorting to DSO Storage Devices

Current trends in electrification of the final energy consumption and towards a massive electricity production from renewables are leading a revolution in the electric distribution system. Indeed, the traditional “fit & forget” planning approach used by Distributors would entail a huge amount of network investment. Therefore, for making these trends economically sustainable, the concept of Smart Distribution Network has been proposed, based on active management of the system and the exploitation of flexibility services provided by Distributed Energy Resources. However, the uncertainties associated to this innovation are holding its acceptance by utilities. For increasing their confidence, new risk-based planning tools are necessary, able to estimate the residual risk connected with each choice and identify solutions that can gradually lead to a full Smart Distribution Network implementation. Battery energy storage systems, owned and operated by Distributors, represent one of these solutions, since they can support the use of local flexibility services by covering part of the associated uncertainties. The paper presents a robust approach for the optimal exploitation of these flexibility services with a simultaneous optimal allocation of storage devices. For each solution, the residual risk is estimated, making this tool ready for its integration within a risk-based planning procedure

Energy Blockchain for Public Energy Communities

This paper suggests an application of blockchain as an energy open data ledger, designed to save and track data regarding the energy footprint of public buildings and public energy communities. The developed platform permits writing energy production and consumption of public buildings using blockchain-enabled smart meters. Once authenticated on the blockchain, this data can be made available to the public domain for techno-economic analyses for either research studies and internal or third parties audits, increasing, in this way, the perceived transparency of the public institutions. A further feature of the platform, starting on the previously disclosed raw data, allows calculating, validating, and sharing sustainability indicators of public buildings and facilities, allowing the tracking of their improvements in sustainability goals. The paper also provides the preliminary results of a field-test experimentation of the proposed platform on a group of public buildings, highlighting the possible benefits of its widespread exploitation

Distributed ledger technologies for peer-to-peer local markets in distribution networks

The newest Distributed Ledger Technology platforms, which delegate the execution of complex tasks in the form of Smart Contracts, make it possible to devise novel local electricity market frameworks, which are performed in a fully automated fashion. This paper proposes a novel fully automated platform for energy and ancillary service markets in distribution networks, able to run in a decentralized fashion, bypassing the need for a physical central authority. The proposed platform, able to perform the role of Virtual Decentralized Market Authority, shows excellent potential applications in the management of local ancillary service markets in local energy communities of various sizes. The proposed Virtual Decentralized Market Authority showed reasonable running costs and comparable technical management capabilities with respect to a physical, centralized managing authority

Decentralized Autonomous Control of Smart Grid with Blockchain Algorithms

The upcoming revolution in electricity distribution will change the way in which electricity will be delivered to end-users. In particular, these advancements will make end-users capable to managing and controlling the local energy production/consumption through local energy markets and peer to peer initiatives. In this scenario, this paper wants to propose a Decentralized Genetic Algorithm (DGA) able to perform market and grid optimizations in a fully autonomous and distributed fashion. The proposed DGA is specifically designed for being performed by IoT devices, such as smart meters and intelligent controllers, spread through the power network. Coordination among them is obtained by the presence of a Decentralized Master Ledger (DML) running on a blockchain, which serves as a common, immutable, trustless and cyber-attack safe memory for the process. In particular, the DGA has been used for performing automated scheduling of a LV smart distribution network through a grid constraint aware local energy market. The DGA platform has been tested with a Hardware in the Loop experimental setup implemented on a RTDS Novacor device as network simulator, and Raspberry Pi Zeroes as DGA computing devices. The defined setup has allowed to achieve decentralized and automated scheduling of distributed resources in the network with a fine-grained time step of one minute

Dynamic Programming for Optimal Energy Management in Nanogrids

The technological advancement in the energy sector leads to innovative grid structures for increasing the connection of renewable energy sources. The Nanogrid, a local modest-sized building energy system with power generation, energy storage, and real-time operation system, ranging from a residential home to a small commercial or industrial building, is a typical example. This paper aims to analyse the benefits for prosumers derived by adopting an intelligent electric energy management system that enables the optimal coordinated operation of the available resources within their Nanogrid. The optimisation objective is to maximise profits for the smart Nanogrid owner. The proposed energy management system is based on a dynamic programming algorithm implemented in MatLab on which is modelled the control system of the Nanogrid. The simulation result confirms that the proposed approach can be used in e realistic real-world case study

Distributed Ledger Based Management of Local Energy Markets with a Federated Learning Approach

This 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

Impact on Electricity Consumption and Market Pricing of Energy and Ancillary Services during Pandemic of COVID-19 in Italy

At 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

A Decentralized Market Solver for Local Energy Communities

The 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

A cyber-physical platform for simulating energy transactions in local energy markets

The paper deals with the design and development of a cyber-physical platform for simulating new local smart electricity markets where even small size consumers and prosumers, located on a relatively small geographic area, can sell/buy the electrical energy or power to contribute to the balance of the power system. The local electricity market is managed by a commercial aggregator, organized as a Virtual Power Plant (VPP), that gathers the energy/power flexibility bids from its consumers/prosumers portfolio. The aggregator is responsible for making trading offers in the day ahead and ancillary services (balancing, reserve, voltage regulation, congestion management) electricity markets, and is also responsible for technical aspects and for commercial transactions among its users by exploiting the Blockchain technology