Tao Chen, Wei Tian, Jingying Wu, Lin Ye · 6 authors
In this paper, we study a local P2P energy trading with help of Blockchain technologies and consideration for customers’ risk preference. The local energy transactions are based on double-side auction mechanism, meanwhile enabling immediate seller-buyer pairing process via iterative price adjustment. Additionally, the quantitative description of risk preference guarantees the optimal decision-making according to customers’ subjective gain reference. The Blockchain platform is also used to support the proposed P2P energy trading mechanism, strengthening the decentralized implementation and smart contract deployment. The demonstration is provided using Ethereum and Remix development environment.
Scott Eisele, Carlos Barreto, Abhishek Dubey, Xenofon Koutsoukos · 7 authors
The emergence of blockchains and smart contracts has renewed interest in electrical cyberphysical systems, especially transactive energy systems. To address the associated challenges, we present TRANSAX, a blockchain-based transactive energy system that provides an efficient, safe, and privacy-preserving market built on smart contracts.
As subsidised feed-in-tariffs for distributed photovoltaic generation are reduced or abolished in many jurisdictions, there is growing interest in increasing self-consumption to realise greater value from rooftop PV generation. This paper proposes a blockchain based incentive mechanism for nonsumer communities with a centralized aggregator approach with the objective of increasing collective self-consumption and reduce peak demand. The incentive is implemented on a permissioned blockchain infrastructure, where generations and consumptions values are stored to the immutable ledger and smart contracts are used to implement the rewards calculation. In order to illustrate the developed incentive, the paper applies the method to four dwellings located in the south of Italy.
Blockchain technology is a decentralized data storage method. The application of blockchain technology to virtual power plants will have an important impact on its operation mode. This paper first expounds the blockchain technology and analyzes the applicability of its combination with virtual power plants. On this basis, it designs the virtual power plant transaction and management framework based on blockchain technology, and establishes the power transaction mode of virtual power plants based on blockchain technology. Finally, on the Ethereum platform, the simulation test is carried out. The results show that the virtual power plant transaction mode based on blockchain technology, combined with the continuous double auction mechanism, can realize the peer-to-peer transaction of distributed resources and loads within the virtual power plant, promote the local elimination of distributed energy source, and reduce the cost of power transaction and energy loss.
Uzma Amin, M. J. Hossain, Wayes Tushar, Khizir Mahmud
Emerging smart grid technologies and increased penetration of renewable energy sources (RESs) direct the power sector to focus on RESs as an alternative to meet both baseload and peak load demands in a cost-efficient way. A key issue in such schemes is the design and analysis of energy trading techniques involving complex interactions between an aggregator and multiple electricity suppliers (ESs) with RESs fulfilling a certain demand. This is challenging because ESs can be of various categories, such as small/medium/large scale, and they are self-interested and generally have different preferences toward trading based on their types and constraints. This article introduces a new contract theoretic framework to tackle this challenge by designing optimal contracts for ESs. To this end, a dynamic pricing scheme is developed such that the aggregator can utilize to incentivize the ESs to contribute to both baseload and peak load demands according to their categories. An algorithm is proposed that can be implemented in a distributed manner by trading partners to enable energy trading. It is shown that the trading strategy under a baseload scenario is feasible, and the aggregator only needs to consider the per unit generation cost of ESs to decide on its strategy. The trading strategy for a peak load scenario, however, is complex and requires consideration of different factors, such as variations in the wholesale price and its effect on the selling price of ESs, and the uncertainty of energy generation from RESs. Simulation results demonstrate the effectiveness of the proposed scheme for energy trading in the local electricity market.
Voltage controls the majority of the processes around us, starting from\nlighting an incandescent lamp to running huge machines in industries.\nTherefore, voltage monitoring becomes essential, which demands efficient\nmeasurement and storage of voltage data. However, there is hardly any system\ntill date that fulfils both the goals of voltage monitoring and voltage data\nstorage. To achieve this goal, we propose the application of the Internet of\nThings along with the server-based framework and Distributed Ledger Technology\nto build systems for smart voltage monitoring. Two models - a centralised model\nand a decentralised model have been presented and analysed thoroughly in this\npaper. The centralised model is built on client-server architecture, whereas\nthe decentralised model is based on a peer-to-peer architecture. Blockchain and\nInterPlanetary File System have been used for the implementation of the\ndecentralised system. Potential improvements to make these systems robust have\nalso been discussed. The methods proposed in this paper for voltage monitoring\nare novel; ensure efficient data storage and can be used for IoT data storage\nof any form.\n
Increasing demand for electricity necessitates the use of efficient mechanisms for demand response management (DRM) in the existing smart grid (SG) system. In the Industry 4.0 era, the usage of information and communication technologies in the energy industry revolutionized the existing grid called SG, which provides a bi-directional flow of energy and data. To handle the energy demand of the consumers, DRM is crucial. It provides the active participation of consumers in the energy trading system (ETS) between consumers and service providers. The traditional energy trading system (TETS) relies on the centralized system or trusted third parties, which may act as a single point of failure. So, it is essential to equip the SG system with a secure energy trading system (SETS) to provide privacy and security to the consumer's data. In this direction, one of the emerging technology, called blockchain, can handle the issue as mentioned above, which is a chain of decentralized and distributed transaction ledger that is retained and maintained by each user. It performs peerto- peer (P2P) energy transactions among different consumers, such as individual houses, using smart contracts, and without a central control body. In a decentralized system, each consumer has its energy storage locally generated using renewable energy resources (RES). In this article, SETS, a blockchain-based decentralized ETS framework, is proposed for storing and processing the data generated from smart meters (SMs). In SETS, miner node is designated to validate the requests of energy requirements, dynamic pricing, and time of stay. Then, an energy transaction execution approach is designed for SETS. The evaluation results obtained show that SETS outperforms the TETS in terms of computation time and communication costs.
Yuanrui Sang, Ümit Cali, Murat Kuzlu, Manisa Pipattanasomporn · 6 authors
Blockchain is an emerging technology that can be applied to many industries involving transactions. It is a fair, transparent and secure way to settle and record transactions between multiple parties without the involvement of a third party. In recent years, many blockchain applications in the field of energy have emerged, however, there is still no guideline or standard for blockchain applications in energy yet. In order to fill the gap, the paper aims to provide a brief review of grid and prosumer blockchain applications and present the standard development activities by the IEEE Standard Association (SA). The review shows that blockchain in energy is a maturing technology that can be used in many areas in the power and energy industry, facilitating the growth of different modern grid technologies. With the development of standards, guidelines for blockchain applications in energy will be provided so that this technology will be better utilized.
Islam El‐Sayed, Komal Khan, Xavier Domínguez, Pablo Arboleyá
The ever growing energy demand due to population growth, higher penetration of electric vehicles and smart appliances, as well as superior living standards, is a demanding incentive to the better utilization of conventional and renewable energy systems. Moreover, to facilitate the emerging requirements of prosumers to participate in the electricity market and monetise their efforts towards distributed energy deployment, traditional centralised energy trading architectures are no longer viable. In this context, blockchain-based ledger technology emerges as the most feasible solution which offers a peer to peer (P2P) energy trading platform providing a unique distributed local energy market model for beneficial energy exchanges among participants. This will represent a significant evolution for future smart grids. In this regard, this work provides a ground understanding as well as all the necessary technical details and procedures required to implement a pilot-platform P2P energy trading system based on blockchain technology. All the source codes have been uploaded and socialized. This may support academics and entrepreneurs at the initial development stage of these kind of initiatives.
Future 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.
Energy trading systems have revolutionized by taking advantage of energy users who produce surplusenergy. In the cyberphysical energy sharing systems, the participation of such consumers who can also sell their residuum energy for profit, namely prosumers, is critical for the sustainable and efficient energy sharing procedure and requires improved prosumer management. The idea of grouping the prosumers for better profits is a promising approach for prosumer management which is currently carried out in centralized manner; that face trust, security and scalability issues. Hence, a strong tool that can protect the prosumer privacy; log the changes for audit purposes and eventually improve the performance of the system is necessary. This paper proposes a blockchain-assisted approach using smart contracts for improved scalability and decentralization of the prosumer grouping mechanism in the context of P2P energy trading. The results show around 38.7% improvement in the performance and scalability of the system.
Anish Jindal, Jakob Kronawitter, Ramona Kühn, Martin Bor · 10 authors
Abstract With the increased penetration of distributed renewable energy sources (DRES) in the grid, new pathways are required to keep the electricity distribution system stable. The provision of ancillary services (AS) by the DRES can contribute in this regard. However, it is necessary to communicate the need for AS from the third party providers such as distribution system operator (DSO) to the DRES in an efficient and scalable manner. To this end, a flexible information and communication technology (ICT) architecture is presented in this paper, and the requirements for the architecture are elaborated. We argue that this architecture is capable of supporting the present and future needs of electricity distribution networks. To illustrate its utility and effectiveness, an accounting use case for DSOs has been presented; it describes a remuneration scheme for the AS provision. A dashboard has been developed to enable communication via this architecture and to allow control of the grid. In addition, a distributed ledger technology for the realization of accounting has been analysed with respect to its scalability and performance capabilities.
Summary Smart grid systems are widely used across the world for providing demand response management between users and service providers. In most of the energy distributions scenarios, the traditional grid systems use the centralized architecture, which results in large transmission losses and high overheads during power generation. Moreover, owing to the presence of intruders or attackers, there may be a mismatch between demand and supply between utility centers (suppliers) and end users. Thus, there is a need for an automated energy exchange to provide secure and reliable energy trading between users and suppliers. We found, from the existing literature, that blockchain can be an effective solution to handle the aforementioned issues. Motivated by these facts, we propose a blockchain‐based smart energy trading scheme, ElectroBlocks , which provides efficient mechanisms for secure energy exchanges between users and service providers. In ElectroBlocks , nodes in the network validate the transaction using two algorithms that are cost aware and store aware. The cost‐aware algorithm locates the nearest node that can supply the energy, whereas the store‐aware algorithm ensures that the energy requests go to the node with the lowest storage space. We evaluated the performance of the ElectroBlocks using performance metrics such as mining delay, network exchanges, and storage energy. The simulation results obtained demonstrate that ElectroBlocks maintains a secure trade‐off between users and service providers when using the proposed cost‐aware and store‐aware algorithms.
Blockchain is a promising technology for local trading of the electricity. It has specific components, such as smart contracts, data ledger, consensus, and provides many benefits for both buyers and sellers because they are obtaining/generating electricity at better prices compared with the electricity from the public grid. This practice leads to a better integration of renewable energy sources, increasing the appetite for new local generation sources and storage facilities, transparency and trading opportunities for all market players. Grid operators also benefit from blockchain since the grid loading will be reduced as the grid does not have to transmit or distribute electricity from large power plants located far away from consumption place. In the end, the market players will benefit from reducing the grid loading and alleviating the congestions as onerous investment in grid infrastructure is avoided. In this paper, we will analyse the advantages of different electricity market mechanisms for trading and settlement. Several auction mechanisms such as pay-as-bid, uniform price, generalised second price or Vickrey-Clarke-Groves are taken into account as feasible options for local markets and peer-to-peer trading.
Abstract The global transition toward sustainable energy paradigms necessitates sophisticated, robust control mechanisms capable of managing the intermittent and stochastic nature of renewable energy sources (RES). This article investigates the implementation of microcontroller-based embedded systems as the foundational architecture for real-time renewable energy management. We analyze the evolution of control strategies—from passive, reactive monitoring to active, predictive, and intelligent power management—and evaluate the pivotal role of microcontrollers in optimizing the integration of solar and wind energy into domestic, industrial, and microgrid infrastructures. By examining the synergy between hardware constraints and software optimization, we demonstrate that microcontroller-based architectures, when coupled with advanced sensor arrays, significantly improve power efficiency, minimize harmonic distortion, reduce load losses, and enhance grid stability. This study serves as a comprehensive retrospection of the foundational innovations that defined energy management engineering between 2010 and 2019, providing a roadmap for the intelligent, decentralized grids of the future. Keywords: Microcontrollers, Renewable Energy, Embedded Systems, Smart Grids, Power Optimization, Solar Photovoltaic Systems, Energy Management Systems (EMS) 1.Introduction The increasing global demand for electricity, coupled with the urgent requirement to decarbonize energy production, has accelerated the adoption of renewable energy sources. However, the inherent intermittent output of wind and solar energy—dictated by weather patterns and diurnal cycles—presents significant challenges for grid reliability, frequency regulation, and power quality. Embedded systems, specifically microcontroller-based units, have emerged as the primary solution for the autonomous, real-time regulation of power distribution, voltage stabilization, and battery state-of-charge management. This paper reviews the foundational technological trends from 2010 to 2019, analyzing how these developments established the critical infrastructure for contemporary smart energy management. As the backbone of decentralized energy, microcontrollers have transitioned from simple monitoring tools to sophisticated edge-computing devices that enable autonomous grid-edge decision-making. By moving the "intelligence" of the grid closer to the source of generation and consumption, these embedded systems have effectively mitigated the negative impacts of power intermittency, enabling a shift from centralized, fossil-fuel-dependent architectures to resilient, distributed green energy networks. This transition has fundamentally altered the relationship between consumers and utility providers, transforming passive energy users into active "prosumers" who contribute to grid stabilization through localized, automated energy management, thereby increasing the overall elasticity of the modern power market. Furthermore, the standardization of these embedded interfaces has lowered the barrier to entry for small-scale developers, fostering a competitive ecosystem of innovative energy solutions that prioritize efficiency and local adaptability. This decentralization has, in turn, spurred advancements in micro-inverter technologies and energy storage systems (ESS), which rely heavily on low-latency microcontroller processing to perform critical tasks like phase synchronization and islanding detection, ensuring that distributed energy systems remain safely connected or gracefully disconnected during grid faults. The evolution of this field reflects a paradigm shift where grid-edge intelligence is no longer a luxury, but a necessity for surviving in a low-inertia energy environment. Ultimately, the integration of these microcontrollers into residential and industrial infrastructure serves as the catalyst for a more responsive grid capable of absorbing the volatility inherent in renewable energy generation. The result is a highly granular, responsive network where individual nodes contribute to the collective health and efficiency of the macro-grid. As these nodes learn to communicate their state and capacity, we witness the emergence of "Swarm Intelligence" in power distribution, where thousands of small, distributed controllers collectively act to stabilize a neighborhood-level grid against external disturbances. This distributed control architecture mimics biological systems, where localized interactions lead to emergent, system-wide stability, providing a robust buffer against the unpredictable nature of intermittent weather-based energy inputs. By decentralizing the control logic, the power network gains a level of self-healing and self-organization that centralized fossil-fuel plants could never achieve, turning the grid into a living, adaptive infrastructure. This transition towards self-optimizing neighborhood-scale energy systems represents the culmination of a decade of embedded innovation, where the aggregate behavior of micro-nodes replaces the rigid, top-down dispatch models of the previous century. 2. Microcontroller Roles in Energy Management Microcontrollers serve as the "brains" of modern energy harvesting and distribution systems. Research during the 2010s demonstrated that these units provide the high-speed computational power required to process complex sensor data in real-time, effectively bridging the gap between physical power components and software-defined control. Real-time Monitoring and Data Acquisition: Microcontrollers utilize Analog-to-Digital Converters (ADCs) to track vital parameters such as voltage, current, frequency, and environmental variables (temperature, solar irradiance, wind speed). This precise data capture allows for the identification of power fluctuations before they impact the grid. High-resolution sampling enables microcontrollers to perform spectral analysis, detecting deviations—such as voltage sags or frequency spikes—that could indicate impending component failure or grid instability. Furthermore, the integration of Non-Volatile Memory (NVM) allows for the logging of historical performance data, facilitating predictive maintenance and long-term efficiency analysis. This data-driven approach is crucial for minimizing operational downtime in remote renewable installations, where physical inspection is costly and logistically difficult. By analyzing trend patterns in historical data, these controllers can suggest preventative maintenance, ensuring the reliability of the system in harsh environmental conditions. The ability to monitor high-frequency harmonic content also provides insight into the degradation of power electronic components like IGBTs and capacitors, allowing for proactive component replacement before catastrophic failure occurs. This proactive monitoring extends the operational lifespan of power electronics, reducing the total cost of ownership for renewable assets. By aggregating this data into cloud-based dashboards, operators can derive actionable insights that optimize system performance across regional deployments. This data visibility fosters a transparent energy market where every kilowatt-hour is tracked, accounted for, and optimized for maximum yield. Furthermore, by utilizing edge-side analytics, microcontrollers can now flag anomalous consumption patterns that may indicate faulty grid-side infrastructure, acting as a secondary diagnostic layer for distribution utilities. This turns the humble meter into a sophisticated grid sensor, capable of localized grid-health reporting and load profiling that was previously impossible. Load Balancing and Dynamic Switching: By implementing adaptive logic, microcontrollers can dynamically switch between utility grid power and renewable storage (battery banks) based on real-time demand, tariff structures, and storage availability. This optimizes the utilization of self-generated power, reducing reliance on the main grid and minimizing electricity costs for the end-user. Sophisticated priority-based scheduling algorithms allow these controllers to manage residential or small-scale industrial loads, ensuring essential systems—such as medical equipment, refrigeration, or security systems—maintain power during grid fluctuations. This dynamic response prevents deep discharge of batteries, significantly extending their operational lifespan, and reduces the need for expensive, centralized peaker-plant power generation that usually relies on high-carbon fuel sources. In large-scale deployments, these controllers facilitate "load shedding" during peak demand, allowing for a more stable and balanced load across the entire local distribution circuit. Furthermore, by utilizing "time-of-use" pricing models programmed directly into the controller's logic, energy management systems can prioritize self-consumption when grid prices are highest, maximizing the economic viability of renewable investments for the consumer. This capability empowers users to actively shape their energy footprint, providing a tangible economic incentive for the deployment of renewable resources. By shifting non-essential loads—such as water heating, EV charging, or HVAC operation—to periods of high solar/wind production, prosumers effectively minimize their carbon footprint while simultaneously relieving the stress on the utility infrastructure. This creates a "demand-side flexibility" that grid operators can leverage to stabilize the network, turning consumers into active, paid participants in the grid's operational strategy, thus establishing a symbiotic economic relationship between the utility and the home. The microcontroller acts as the mediator in this transaction, autonomously making decisions that optimize the user's economic utility while aligning with the macro-grid's stability requirements. Maximum Power Point Tracking (MPPT): The implementation of advanced algorithms (such as Pe
Distributed generation in the microgrid becomes increasingly significant, as it eliminates the power losses from long-distance electricity transmission lines. Distributed energy resources owners who can both produce and consume energy are defined as prosumers. To encourage the peer-to-peer (P2P) energy trading between prosumers, blockchain as a thriving technology is utilized in the P2P network due to its transparency, security, and rapidity in executing transactions. Due to its decentralized quality, any intermediaries are eliminated so that transactions happen directly among traders. This article introduces a consortium blockchain trading model to support P2P energy trading, using a proof-of-stake protocol. The pre-selected miners are responsible for compensating the power losses in distribution lines by energy transactions. The specific process of the blockchain establishment, as well as the smart contract creation, are demonstrated. In addition, a type of crypto-currency named “elecoin” is created in the P2P market, which is published by the mining mechanism of the blockchain. Finally, a case study is introduced to realise the functions of the proposed blockchain model. Simulation results show the feasibility and effectiveness of the proposed approach.
Berrak Perk, Can Bayraktaroglu, Engin Deniz Dogu, Faizan Safdar Ali · 5 authors
As a decentralized immutable ledger where several trustless peers can reach consensus with each other without the need of any trusted third party, blockchain technology fits perfectly with the peer-to-peer (P2P) energy trading paradigm. In this paper, we propose, design and analyze a marketplace for energy trading based on smart contracts on the blockchain. The proposed system named Joulin serves as a competitive and efficient marketplace where peers can both produce, buy and sell energy depending on their needs. As a proof-of-concept, we developed the prototype of the Joulin system using Ethereum blockchain. Our results, in terms of usability, flexibility and resiliency, demonstrate the potential to achieve an easily extendable and reliable system with low transaction costs. Low Ethereum gas costs and quick response times demonstrate usability. Our smart contracts have also been tested with security tools to ensure that they are not vulnerable to outside manipulations.