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.
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
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.
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.
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
Abstract What is the impact of blockchain technology on electronic markets in the energy sector? In this interview with Electronic Markets, Dr. Tobias Paulun, chief strategy officer of the European Energy Exchange (EEX), explains where the leading European energy exchange recognizes potentials of blockchain technology compared to existing electronic platforms and which blockchain projects EEX is working on. In his view, the impact of blockchain technology depends on the respective market segment and on the availability of solutions for safeguarding guarantees of origin. He expects that established exchange systems and blockchain-based systems will coexist in this strongly regulated and specialized industry.
Teng Zhang, Ren Yucheng, Cao Xiaodong, Kang Xie · 5 authors
Abstract In order to promote the synergistic interaction between source network and storage, and enhance the load control capability, the adjustable load measurement technology based on blockchain has become the focus of research at home and abroad. This paper reviews the current research status of block chain technology and its application in declaration and issuance, market supervision, market settlement, load measurement, enhancing mutual trust of market transactions and information security. Distributed ledger from block chain under containerized edge service engine, improved directed and acyclic chart distributed ledger structure and adjustable load execution score three based on distributed ledger data. In this respect, the key and difficult points of technology are summarized. Combined with the current situation of power development demand, power market, electricity price mode, demand response, the possible problems and development trend of adjustable load measurement technology based on block chain are discussed in detail.
Energy systems around the globe nowadays are undergoing a rapid transformation in their conventional structures that are vital from an environmental, economic, and social perspective. The driving forces behind the shift to the new era of the energy, also known as Energy 4.0, are the so-called 3 D’s: Decarbonization, Digitalization, and Decentralization. \n \nThe blockchain technology, which comes as a result of digitalization, is considered by many experts a transformative force for the energy sector. More specifically, it is believed that it can be a direct driver for the decentralization of energy systems as well as an indirect one for their decarbonization and further digitalization. This is due to the technology’s most prominent technical capacities, namely, transparency, security, and decentralization. All these combined have provided practical use cases, with the most widely-known being peer-to-peer power trading. On this occasion, consumers are enabled to trade the surplus amount of the energy they produce (e.g. with photovoltaics) with other consumers in decentralized energy networks. Such a solution can contribute to the decentralization of energy systems and make them more democratic and inclusive. \n \nMost of the blockchain applications in the energy sector today have been directed towards the electric power industry, with more than half of blockchain use cases focusing on decentralized energy trading and energy projects financing. In contrast, the application of blockchain in the petroleum industry is still in its infancy. In the oil and gas sector, new technologies have to pass through several phases before mass adoption occurs, due to high costs and increased probability of component failures. Another deterrent is the particular nature of operations in the industry. For instance, oil is traded as a commodity on a global level and is impacted by external factors such as geopolitics, while electricity is specific to a regional level. Despite the sluggish adaptability of the industry, more recently, a number of blockchain initiatives from oil and gas majors have been launched. \n \nRegardless of those advances and the fact that there is a growing number of startup companies developing similar solutions, blockchain is still in an exploratory phase of development. That is the main reason for it not being widely adopted by large industry players or in large-scale applications, which could otherwise help it grow faster and be established as a standard technology for particular applications. It will only become apparent in the next five to ten years, at a time when blockchain is expected to reach maturity from a technical standpoint, whether it will be a revolutionary technology that will bring about a revolution in the structure and processes of the energy industry. \n \nThis thesis aims at reviewing the main characteristics of blockchain technology, and based on its technical advantages, analyze the role it has played up to this day in the transformation of the energy industry and, more specifically, in the electric power and oil & gas sectors. In addition, a case study is presented that aims at showing how blockchain can provide solutions for the Greek energy ecosystem.
With the development of smart cities, not only are all corners of the city connected to each other, but also connected from city to city. They form a large distributed network together, which can facilitate the integration of distributed energy station (DES) and corresponding smart aggregators. Nevertheless, because of potential security and privacy protection arisen from trustless energies trading, how to make such energies trading goes smoothly is a tricky challenge. In this paper, we propose a blockchain-based multiple energies trading (B-MET) system for secure and efficient energies trading by executing a smart contract we design. Because energies trading requires the blockchain in B-MET system to have high throughput and low latency, we design a new byzantine-based consensus mechanism (BCM) based on node's credit to improve efficiency for the consortium blockchain under the B-MET system. Then, we take combined heat and power (CHP) system as a typical example that provides distributed energies. We quantify their utilities, and model the interactions between aggregators and DESs in a smart city by a novel multi-leader multi-follower Stackelberg game. It is analyzed and solved by reaching Nash equilibrium between aggregators, which reflects the competition between aggregators to purchase energies from DESs. In the end, we conduct plenty of numerical simulations to evaluate and verify our proposed model and algorithms, which demonstrate their correctness and efficiency completely.
USDOE Office of Electricity Delivery and Energy Reliability (OE), Mariola Rodríguez, Peter L. Fuhr, Gary Hahn · 6 authors
This paper provides descriptions of the key components of different distributed ledger technology platforms.Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices.The platforms use cryptographically linked "blocks" to store and verify transactional information between these organizations.DLT increases data security, data integrity, trust among its participants.Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories.In this study we examine twelve different DLT platforms.There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions.These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain.However, further development is required to realize the full promise of DLT.Our assessment includes a general description of each DLT and its key characteristics.Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless.The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements.During this research we found key parameters to measure performance and existing tools for assessment.Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability.The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks.From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures.The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.
Ifiok Anthony Umoren, Syeda Sanober Ali Jaffary, Muhammad Zeeshan Shakir, Konstantinos Katzis · 5 authors
This article presents a blockchain-based scheme for energy trading between electric vehicles (prosumers) and critical load (consumer) in a logical network. Unlike traditional wholesale energy markets where retailers sell energy to consumers, our proposed model directly connects prosumers with consumers to meet temporary energy demands. We exploit blockchain technology to establish a trusted energy trading ecosystem and develop an application to remotely monitor energy trading activities between trading entities. Experimental results illustrate that the energy trading system is effective in finding, associating, and routing prosumers to consumers, while protecting privacy of entities. Numerical results show a favorable performance of our optimization model in comparison to traditional frameworks.
Distributed renewable energy offers an exciting opportunity for sustainable transition and climate change mitigation. However, it is overlooked in most of the conventional tradable green certificates programs. Blockchain shows an advantage of incorporating a galaxy of distributed prosumers in a transparent and low-cost manner. This paper proposes I-Green, a blockchain-based individual green certificates system for promoting voluntary adoption of distributed renewable energy. Combing the features of blockchain technology and the theories of social norm and peer effects, the novel green ratio incentive scheme and proof of generation consensus protocol are designed for I-Green. A blockchain simulator is constructed to evaluate the effectiveness and efficiency of I-Green system. The simulation results present its potential for facilitating widespread adoption of distributed generation, and confirm the feasibility of blockchain as the information communication technology (ICT).
Contract-for-Difference financial instruments are available to renewable electricity generators in day-ahead electricity markets to allow them to hedge against revenue risk. Traditional CfDs while designed to hedge revenue risk, introduce other new risks such as counterparty credit, margining and third-party risks. We therefore propose a novel financial instrument - an Ethereum blockchain-based dual escrow smart contract, to serve as the mediator in a CfD agreement between a renewable electricity generator and supplier. This financial instrument addresses hedging related risks that result from traditional CfD agreements in day-ahead electricity markets. In this paper, we design the logic of the financial instrument, translate this logic to smart contract codes and demonstrate its expected performance. Overall, the proposed financial instrument has the benefits of reducing hedging related risks inherent in traditional CfDs. Likewise, it enables secure, efficient, cost-effective, consistent, reliable, transparent and frictionless transactions between contracting parties in a CfD agreement.
The electricity industry has always been under scrutiny in order to improve the quality of electricity supply, measurement and billing services to have the at most user transparency, while providing these services with the highest efficiency. Although many solutions have emerged, of which the smart meter was considered a viable option, it was quick to perish under the prodigious complications with the real-life feasibilities. El DApp- An electricity power consumption tracking application solution, harnessing both the IoT and Blockchain utilities to provide a decentralized and secure recording mechanism, that provides an improved architecture to the smart meter is proposed in this article. The El DApp provides a high security and cost efficient decentralized live electricity power consumption recording of the user that is maintained by a Raspberry Pi based Ethereum network.
Shivam Saxena, Hany E. Z. Farag, Hjalmar Turesson, Henry Kim
Transactive energy systems (TES) are modern mechanisms in electric power systems that allow disparate control agents to utilise distributed generation units to engage in energy transactions and provide ancillary services to the grid. Although voltage regulation is a crucial ancillary grid service within active distribution networks (ADNs), previous work has not adequately explored how this service can be offered in terms of its incentivisation, contract auditability, and enforcement. Blockchain technology shows promise in being a key enabler of TES, allowing agents to engage in trustless, persistent transactions that are both enforceable and auditable. To that end, this study proposes a blockchain based TES that enables agents to receive incentives for providing voltage regulation services by (i) maintaining an auditable reputation rating for each agent that is increased proportionately with each mitigation of a voltage violation, (ii) utilising smart contracts to enforce the validity of each transaction and penalise reputation ratings in case of a mitigation failure, and (iii) automating the negotiation and bidding of agent services by implementing the contract net protocol as a smart contract. Experimental results on both simulated and real‐world ADNs are executed to demonstrate the efficacy of the proposed system.
With the increase in local energy generation from Renewable Energy Sources (RESs), the concept of decentralized peer-to-peer Local Energy Market (LEM) is becoming popular. In this paper, a blockchain-based LEM is investigated, where consumers and prosumers in a small community trade energy without the need for a third party. In the proposed model, a Home Energy Management (HEM) system and demurrage mechanism are introduced, which allow both the prosumers and consumers to optimize their energy consumption and to minimize electricity costs. This method also allows end-users to shift their load to off-peak hours and to use cheap energy from the LEM. The proposed solution shows how energy consumption and electricity cost are optimized using HEM and demurrage mechanism. It also provides economic benefits at both the community and end-user levels and provides sufficient energy to the LEM. The simulation results show that electricity cost is reduced up to 44.73% and 28.55% when the scheduling algorithm is applied using the Critical Peak Price (CPP) and Real-Time Price (RTP) schemes, respectively. Similarly, 65.15% and 35.09% of costs are reduced when CPP and RTP are applied with demurrage mechanism. Moreover, 51.80% and 44.37% electricity costs reduction is observed when CPP and RTP are used with both demurrage and scheduling algorithm. We also carried out security vulnerability analysis to ensure that our energy trading smart contract is secure and bug-free against the common vulnerabilities and attacks.
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang, Thang X. Vu · 6 authors
In this paper, we propose a novel energy-efficient framework for an electric vehicle (EV) network using a contract theoretic-based economic model to maximize the profits of charging stations (CSs) and improve the social welfare of the network. Specifically, we first introduce CS-based and CS clustering-based decentralized federated energy learning (DFEL) approaches which enable the CSs to train their own energy transactions locally to predict energy demands. In this way, each CS can exchange its learned model with other CSs to improve prediction accuracy without revealing actual datasets and reduce communication overhead among the CSs. Based on the energy demand prediction, we then design a multi-principal one-agent (MPOA) contract-based method. In particular, we formulate the CSs' utility maximization as a non-collaborative energy contract problem in which each CS maximizes its utility under common constraints from the smart grid provider (SGP) and other CSs' contracts. Then, we prove the existence of an equilibrium contract solution for all the CSs and develop an iterative algorithm at the SGP to find the equilibrium. Through simulation results using the dataset of CSs' transactions in Dundee city, the United Kingdom between 2017 and 2018, we demonstrate that our proposed method can achieve the energy demand prediction accuracy improvement up to 24.63% and lessen communication overhead by 96.3% compared with other machine learning algorithms. Furthermore, our proposed method can outperform non-contract-based economic models by 35% and 36% in terms of the CSs' utilities and social welfare of the network, respectively.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Fernando Lezama · 7 authors
Efficient alternatives in energy production and consumption are constantly being investigated and conducted by increasingly strict policies. Buildings have a significant influence on electricity consumption, and their management may contribute to the sustainability of the electricity sector. Additionally, with growing incentives in the distributed generation (DG) and electric vehicle (EV) industries, it is believed that smart buildings (SBs) can play a key role in sustainability goals. In this work, an energy management system is developed to reduce the power demands of a residential building, considering the flexibility of the contracted power of each apartment. In order to balance the demand and supply, the electrical power provided by the external grid is supplemented by microgrids such as battery energy storage systems (BESS), EVs, and photovoltaic (PV) generation panels. Here, a mixed binary linear programming formulation (MBLP) is proposed to optimize the scheduling of the EVs charge and discharge processes and also those of BESS, in which the binary decision variables represent the charging and discharging of EVs/BESS in each period. In order to show the efficiency of the model, a case study involving three scenarios and an economic analysis are considered. The results point to a 65% reduction in peak load consumption supplied by an external power grid and a 28.4% reduction in electricity consumption costs.
European buildings are producing a massive amount of data from a wide spectrum of energy-related sources, such as smart meters’ data, sensors and other Internet of things devices, creating new research challenges. In this context, the aim of this paper is to present a high-level data-driven architecture for buildings data exchange, management and real-time processing. This multi-disciplinary big data environment enables the integration of cross-domain data, combined with emerging artificial intelligence algorithms and distributed ledgers technology. Semantically enhanced, interlinked and multilingual repositories of heterogeneous types of data are coupled with a set of visualization, querying and exploration tools, suitable application programming interfaces (APIs) for data exchange, as well as a suite of configurable and ready-to-use analytical components that implement a series of advanced machine learning and deep learning algorithms. The results from the pilot application of the proposed framework are presented and discussed. The data-driven architecture enables reliable and effective policymaking, as well as supports the creation and exploitation of innovative energy efficiency services through the utilization of a wide variety of data, for the effective operation of buildings.