Liaqat Ali, M. Imran Azim, Nabin B. Ojha, Jan Peters · 8 authors
Peer-to-peer (P2P) trading in a local energy market (LEM) offers various participants the opportunity to negotiate and strike energy deals among themselves using a distributed ledger technology called blockchain. In this paper, a new local model is presented using a layer-2 scalability solution for second-generation (Gen2) blockchain technology to enable P2P trading among four types of participants: consumers, prosumers with solar photovoltaic (PV) systems, prosumers with solar PV systems and battery energy storage systems (BESSs), and electric vehicles (EVs). The proposed LEM trading platform involves several critical steps, including the creation of typical forecasting profiles for load consumption, solar generation, and battery state-of-charge (SOC) through a forecasting solution. Next, the LEM participants place their pricing bids using a trading agent service, and the trading engine collects the profiles data and bid prices, which performs matchmaking in a forward-facing market. The output of the trading engine consists of dispatch signals for prices and energy values that are sent to each participant to execute actual trading. Furthermore, the trading engines store the accepted and past bidding data and energy values of P2P trades for each participant in blockchain technology, which can be retrieved and displayed on the LEM user interface screens of participants and administrators using their blockchain addresses at any time during the trading process. This study focuses on simulating proposed LEM models, incorporating functional limitations and market rules. These rules aim to reduce energy costs, enhance margins for utilities and retailers, and mitigate grid congestion through BESSs, resulting in reduced operational and capital expenditure. LEM outcomes are analysed and compared with a Business-as-usual (BAU) model. Participants’ energy trading behaviour, cost-revenue dynamics, grid impact, and blockchain implementation costs are explored. The study highlights LEM benefits in terms of reduced CO2 emissions by 984 kg CO2, increased self-sufficiency by 2.2%, and improved financial benefits of all participants by 21.6%. The use of modern blockchain technology guarantees secure data storage and rapid, cost-effective energy trading, thereby making the proposed LEM platform a viable solution in the distribution market.
Md Moniruzzaman, Abdulsalam Yassine, M. Shamim Hossain
Next-generation consumer electronics and electric vehicle (EV) energy charging technology promise transformative advancements in the automotive industry. One of the main challenges that hinders consumers’ experience is range anxiety particularly relevant in locales where the installation of fixed charging stations (FCSs) is beset by logistical hurdles, notably in rural regions. With the advancement of consumer electronics especially in the design of Mobile Charging Stations (MCSs), EV drivers can now access these MCSs to exchange energy. However, concerns regarding data security and the best strategies to select an MCS to trade energy may negatively impact consumer experiences. This paper delves into the conception of intelligent remedies by proposing the integration of reinforcement learning and blockchain technology to empower EV drivers to access and securely exchange energy with MCSs. We design a Proof of MCSs (PoMCS) as a consensus protocol to select the winning MCSs as block miners in the blockchain. The results of our experiment show that the average gain for the MCSs increases when using the proposed model and therefore inclined to serve more EVs.
The need for effective and secure energy management systems has arisen as a result of increased demand for energy, the increasing use of renewable energy sources (RES), and the introduction of decentralized power generation. Here, we explore the urgent issues and exciting possibilities posed by traditional centralized energy networks, with a special focus on three crucial dimensions: achieving supply-demand equilibrium, seamlessly integrating renewable energy sources, and maintaining participant trust and transparency. This paper suggests leveraging blockchain technology (BT) to create a decentralized network grid energy management system to address these issues. Individual participants can directly exchange energy with one another within the Decentralized Network Grid through peer-to-peer (P2P) trading. The network microgrid model’s mathematical optimization is designed to balance supply and demand, improve network microgrid stability, and optimize energy distribution. The aforementioned optimization uses information from grid constraints, usage patterns, and energy pricing to make wise decisions in real time. The concept aims to achieve energy efficiency, cost savings, and seamless integration of renewable energy sources by utilizing the capabilities of blockchain smart contract and proposed optimization algorithm.
Generation of renewable energy by participants in the electricity market is used for self-consumption and for local trade. Energy savings can be turned into negative watts-negawatts- and can be traded with peers as the right to purchase electricity. Combining both kilowatt and negawatt trading would enhance the local energy market by providing peers with better access to energy and economic benefits. Trust in the market could be managed effectively with the help of blockchain technology. Market transactions are recorded into immutable, transparent, and distributed ledgers, with added security provided by tokenization. In this work, a combined kiloWatt and negawatts trading is attempted in a local market with solar electricity generation, enabled by smart contract deployed on public blockchain. Smart contracts are written in Solidity language and deployed on Sepolia test network for Ethereum public blockchain.
Jun Gu, Jing Shen, Tianle Li, Ying Jin · 5 authors
With the development of intelligent power systems, the ecological community of microgrid community power autonomous organizations has become increasingly active. However, the uncertainty of renewable energy within the microgrid has led to energy coordination issues within the community, posing a threat to the sustainable development of microgrid community energy. And blockchain technology, with its characteristics of decentralization, tamper resistance, and distributed storage, is highly compatible with decentralized and autonomous microelectronic networks. This article utilizes intelligent contract automation to achieve optimal allocation and utilization of power resources. Proposed a blockchain-based energy storage time-sharing trading model Blockchain time-of-use energy storage (BLES-TOU). After processing the data through smart contracts, we provide feedback to the subject information. We adjust the electricity consumption strategy by constructing a Stackelberg game model. Finally, we design a smart contract testing plan based on the caliper and obtain the throughput and performance analysis of the smart contract.
Bitcoin, the most valuable and energy-consuming cryptocurrency, has recently been at the center of a heated debate over its environmental impact. This controversy has caught the public’s attention, prompting us to investigate the energy consumption of Bitcoin. In this paper, we have conducted a review of the literature on various aspects of Bitcoin mining, including its mechanisms, energy consumption, mining sites, and the potential for renewable energy use. Our findings reveal that the power consumption of Bitcoin is bound to increase with the continued adoption of the proof-of-work (PoW) consensus algorithm. Nonetheless, the growing availability of affordable renewable energy sources worldwide brings hope that Bitcoin mining will shift towards cleaner energy in the near future.
Mohammad Seyfi, Mehdi Mehdinejad, Behanm Mohammadi-Ivatloo, Jamshid Aghaei
Power systems undergoes a massive change in power delivery and consumer-side production, e.g., penetration of renewable energy resources (RES) and reshaping of consumers to form prosumers, in which the Peer-to-Peer (P2P) energy trading markets are among the most promising solutions for handling these changes. In this paper, a fully decentralized smart contract-based P2P energy token trading market for active retailers and prosumers is presented. Active retailers in this market play as a connection between the local P2P market and upstream markets, which enables the participation of small-scale prosumers in the energy and ancillary markets. They can optimize their decision-making strategy to gain the most profit from energy markets. This model can first encourage retailers to participate in the local P2P energy token market, and consequently, the utilization of renewable energy resources in the power systems is facilitated. The simulation results showed the importance of the demand response program and the effectiveness of the DR program on the independence of the local P2P energy token trading market.
The concept of peer-to-peer local energy trading holds the promise of fostering a more sustainable and efficient energy ecosystem, aligning with the global goals of environmental responsibility, energy conservation, and the advancement of renewable energy sources. As such, it has attracted lots of attention from researchers seeking to revolutionize the energy sector and address the challenges associated with traditional centralized energy models. However, to effectively set up a local energy market, two vital components are needed – a robust transaction infrastructure and a welldefined set of market and auction rules. In this paper, our proposed solution relies on the Ethereum blockchain and smart contracts, thereby exploiting the benefits of blockchain technology to meet the requirements for secure and decentralized energy trading within a community, all without the need for a trusted third party. We propose an Ethereumbased framework to facilitate secure and decentralized peer-topeer electricity trading among the members of a smart community. The framework implements smart contract auction with filters at different stages throughout the process to ensure the integrity of data, maintain data confidentiality, and safeguard user identity privacy on the network. We also performed a thorough security assessment of our smart contract using MythX by Consensys - a security analysis tool for Ethereum smart contracts to identify and rectify any potential security threat and vulnerabilities in our proposed framework and auction process.
The future distribution grid is a peer-to-peer (P2P) community formed by a large number of active energy agents (AEAs), and renewable energy certificate (REC) trading is an efficient way to realize a low-carbon AEA community. AEAs can trade not only electricity but also RECs among themselves to economically and efficiently meet the renewable portfolio standard (RPS) requirements. Aiming to lower the market barrier and increase the trading benefits for market participants, this paper proposes a blockchain-based renewable energy certificate (BCREC) that supports divisible and multiple transactions. The trade process includes four stages: setup, pre-transaction, transaction, and post-transaction. A scheme based on blockchain oracles and smart contracts is implemented to achieve decentralized BCREC issuance and transaction and to support a more flexible trading market. By exploring two typical market scenarios, we verify the advantages of BCREC trading and evaluate its impacts on AEA profits and market efficiency.
Abstract: The problem we are facing is how to efficiently use renewable energy sources like solar and wind, which are sometimes unpredictable. Current energy systems struggle to handle this unpredictability, which can lead to wasted energy and more pollution. There is also a lack of trust and transparency in the energy market. The effective tracking and management of renewable energy present complex challenges. Traditional energy tracking systems often lack transparency, security and trust among stakeholders, hindering the realization of a fully sustainable energy ecosystem. To fix these issues, we are looking at using blockchain technology. Blockchain is like a secure and transparent digital ledger. It can help automate energy trading and make it more trustworthy. By using smart contracts, we can make sure energy transactions happen quickly and with fewer costs. We will also use data analytics and devices that connect to the internet to better predict when we will have energy and how to use it efficiently. Our solution is to create a platform for renewable energy trading using blockchain. We will use technologies like Hyperledger Fabric and Ethereum to make sure everything works securely. Smart contracts will help with automatic energy trading, and AI will help us predict when we will have energy. Devices connected to the internet will give us real-time data to manage the energy grid better. With this plan, we want to make renewable energy trading easy and help the world switch to cleaner energy sources faster
In most domestic buildings, gas and electricity are supplied by energy and utility companies through centralised energy systems. This often results in a high burden on central management systems and has adverse effects on energy prices. Blockchain-based peer-to-peer energy trading platforms can deliver strategic operation of decentralised multi-energy network among multiple domestic buildings to reduce global greenhouse gas emissions and address global climate change issues. However, prevailing blockchain-based energy trading platforms focused on system implementation for peer-to-peer electricity trading while lacking predictive control and energy scheduling optimisation. Therefore, this paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy (i.e., heat and electricity) allocation and transmission, among multiple domestic buildings. Machine learning is harnessed to predict day-ahead energy generation and consumption patterns of prosumers and consumers within the multi-energy network. The proposed blockchain and machine learning-based decentralised energy management framework will establish optimal and automated energy allocation among multiple energy users through peer-to-peer energy transactions. This approach focuses on energy-matching from both the supply and demand sides while encouraging direct energy trading between prosumers and consumers. The security and fairness of energy trading can also be enhanced by using smart contracts to strictly execute the energy trading and bill payment rules. A case study of 4 real-life domestic buildings is introduced to determine the economic and technical potential of the proposed framework. In comparison to prevailing approaches, a key benefit from the proposed approach is an improved computational load/failure of a single point, energy trading strategy, workload, and capital cost energy. Findings suggest that energy costs reduced between 7.60%-25.41% for prosumer buildings and a fall of 5.40%-17.63% for consumer buildings. In practical applications, the proposed approach can involve a larger number of prosumer and consumer buildings within the community to decentralise multiple energy trading, thus significantly contributing to the reduction of greenhouse gas emissions and enhancing environmental sustainability.
В статье рассматривается технология работы алгоритмов распределенного реестра (блокчейн) и смарт-контрактов в применении к индустрии энергетики. Показано, как преимущества технологии могут способствовать оптимизации энергетической отрасли в свете продолжающегося энергоперехода, рассмотрены примеры мировых проектов внедрения блокчейн в существующие или новые энергосистемы, обсуждаются риски и препятствия, связанные с имплементацией решений платформ блокчейн в энергетические системы. The article discusses the technology of operation of distributed ledger algorithms (blockchain) and smart contracts as applied to the energy industry. It is shown how the advantages of technology can help optimize the energy industry amid ongoing energy transition, examples of global projects for implementing blockchain into existing or new energy systems are reviewed, and risks and obstacles associated with the implementation of blockchain platform solutions in energy systems are discussed.
The paper introduces an advanced Decentralized Energy Marketplace (DEM) integrating blockchain technology and artificial intelligence to manage energy exchanges among smart homes with energy storage systems. The proposed framework uses Non-Fungible Tokens (NFTs) to represent unique energy profiles in a transparent and secure trading environment. Leveraging Federated Deep Reinforcement Learning (FDRL), the system promotes collaborative and adaptive energy management strategies, maintaining user privacy. A notable innovation is the use of smart contracts, ensuring high efficiency and integrity in energy transactions. Extensive evaluations demonstrate the system's scalability and the effectiveness of the FDRL method in optimizing energy distribution. This research significantly contributes to developing sophisticated decentralized smart grid infrastructures. Our approach broadens potential blockchain and AI applications in sustainable energy systems and addresses incentive alignment and transparency challenges in traditional energy trading mechanisms. The implementation of this paper is publicly accessible at \url{https://github.com/RasoulNik/DEM}.
: Power generation in today’s world is of utmost importance, due to which blockchain is used for the categorization and formation of decentralized structures. This paper has proposed decentralized energy generation using a nester, i.e., energy sharing without third-party intervention. Decentralized blockchain technology is applied to ensure power sharing between buyer and seller, and also to achieve efficient power transmission between prosumer and consumer. Energy management is associated with controlling and reducing energy consumption. Blockchain technology plays a major role in distributed power generation, for example, power-sharing (solar and wind energy), price fixation, energy transaction monitoring, and peer-to-peer power-sharing. These are operations performed by blockchain in renewable power generation. Solar power generation using blockchain technology can obtain an impact resting upon the power generation system. Distributed ledger is the key area of blockchain technology for recording and tracking each transaction in the distribution system to improve the efficiency of the overall transmission system. A smart contract is another important tool in the blockchain technology, which is issued to confirm an assent between buyer and seller before starting any energy transaction without external intervention and also to avoid time delay. Maximum power point tracking is conducted in PV cells using blockchain technology. Blockchain influences energy management systems to improve the utilization of energy, optimize energy usage, and also to reduce the cost.
The traditional power generation rights trading (GRT) market is faced with the problems of weak interconnection of electricity‑carbon market and low security. Using smart contracts in the blockchain , the idea of establishing a weakly centralized GRT structure is proposed in this paper. The carbon emission factor was introduced to improve the GRT model, and carbon emission market is used to further stimulate the emission reduction vitality of generating units. The empirical results show that compared with the benchmark model and improved model 1, the improved GRT model proposed by us has the best emission reduction effect. The contribution of this paper is to make up for the existing research that cannot fully consider the impact of carbon peak and carbon neutralization on the GRT market, as well as the information security issues brought by big data trading on the GRT platform. This paper puts forward some policy implications for the decarbonization and green development of the electricity market advocated by the Chinese government.
Sama Almubarak, Hasan Ibrahim, Dev Singhania, Prasad Enjeti
This paper presents an in depth study of electric energy consumption and power quality analysis in Bitcoin mining facilities in Texas. The study includes energy consumption, voltage, current, power and current harmonics analysis from measured data on both grid connected and standalone facilities (powered by flared gas). Additionally, these results are also compared to the data gathered on an identical laboratory mining machine. Since large MW range Bitcoin mining loads are termed as "flexible loads" by the grid operators, the paper discusses examples of their potential role in participating in ancillary services to help stabilize the grid. Laboratory test results on voltage ride-through of Bitcoin machines is also presented and discussed. Analysis is also included on how large Bitcoin mining facilities can earn substantial additional revenue via their participation in ancillary services. Finally experimental data collected on a 3.5 kW S19 Pro Bitcoin miner installed in the laboratory and a 2.2 MW commercial mining facilities is tabulated and discussed.
In today’s smart communities, small-scale energy systems are essential for sustainable development and efficient resource management. However, ensuring the confidentiality, safety, and accurate prediction of energy consumption patterns in energy trading is a major challenge. To address these issues, an innovative solution that synergistically combines two cutting-edge technologies: blockchain and machine learning is proposed. This paper unveils a novel approach that harmoniously merges blockchain with the Recalling-Enhanced Recurrent Neural Network (RERNN) to revolutionize energy trading systems called ‘Blockchain-Enhanced Energy Trading with Recalling-Enhanced Recurrent Neural Network (BET-RERNN).’ Data from IoT-enabled smart devices is securely stored in blockchain blocks, ensuring data integrity and immutability. Blockchain’s decentralized nature creates a trust-less environment for energy trading, protecting the privacy and anonymity of participants while maintaining transparency. At the heart of our system lies the advanced machine-learning capabilities of the RERNN model. By processing the data stored on the blockchain, RERNN accurately predicts optimal power generation for small-scale energy systems, enabling smart communities to make informed decisions and optimize their energy consumption. The BET-RERNN scheme provides a plethora of strengths. First, participants can securely engage in energy trading without compromising sensitive information, fostering a more resilient and efficient market. Second, blockchain technology ensures that all energy-related data is protected from tampering and unauthorized access, ensuring system reliability and trust. An in-depth comparison of RERNN’s performance to traditional General Regression Neural Network (GRNN) and Gradient Boost Decision Tree (GBDT) methods is conducted. To verify the strategy’s effectiveness, MATLAB simulations are employed, demonstrating its real-world applicability and scalability. By combining blockchain and machine learning, a secure and privacy-preserving smart community is established, promoting sustainable energy practices for a greener future.
Through a digital platform, distributed generations can be managed intelligently to increase the overall efficacy of the distribution system. It was made possible by the growing integration of distributed generation with smart meters, Internet of Things, smart sensors, etc. Decentralized peer-to-peer (P2P) energy trading is a new concept and is encouraged by blockchain technology (BT) due to its transparency, security, and speedy transaction handling. This article expands on the P2P concept by creating a decentralized energy trading system to demonstrate the benefits of BT in providing a secure and efficient transaction platform for a community microgrid system containing consumers, prosumers, and renewable energy source (RES) owners. The supply–demand ratio method is used to determine the P2P selling and buying prices within the network based on the optimized allocations of the prosumers/RESs owners and consumers. This article highlights the participation of miners (validators) in the microgrid ecosystem, specifically local prosumers and RES owners. By actively participating in the energy trading, miners can enhance energy security, increase system resilience, and enjoy financial incentives. The suggested model designed on the Ethereum platform showcases effective energy management of microgrid system operation and increased security level through a step-by-step implementation process.
The rapid pace of development of the Internet of Things and the requirements of various devices have allowed us to perform calculations at the edge, especially in terms of consumer electronics. Such progress makes it possible to design new solutions for energy distribution and prediction for smart homes. In this paper, we propose a solution that can be used to optimize energy distribution by analyzing the energy demand in individual homes. The proposed methodology is based on edge technology, where a dedicated LSTM network with a multi-head self-attention network is trained with measurement data from different sensors for predicting energy demand. Training of this network is extended to a decentralized learning process with an additional aggregation decision module (that allows rejection of the model in case of worst adaptation to private data). In order to increase data security, we added a blockchain network with a Byzantine strategy and Proof of Stake (PoS) consensus. The solution was tested for a publicly available database in order to demonstrate the possibilities and advantages of such an architecture.
Sachi Chaudhary, Riya Kakkar, Mohammad S. Obaidat, Rajesh Gupta · 6 authors
The extensive deployment of electric vehicles (EVs) globally has become an alternative to fossil-fuel or gasoline vehicles to tackle harmful greenhouse gas emissions. But, huge EV charging demand can bring challenges to the charging infrastructure by destabilizing the grid stability and affecting efficient EV charging. Thus, the aforementioned challenges can be addressed by facilitating the energy trading (ET) between EVs which can act as prosumers or consumers. Thus, we have proposed a blockchain-based secure ET scheme for EVs coordination using Interplanetary File System (IPFS) protocol to mitigate the data storage cost issues of the blockchain. Opportunistically, we have considered various ET scenarios to coordinate the communication between prosumer and consumer based on the waiting time and priority levels. Moreover, the data communication between EVs is considered via a 5G communication network for highly reliable and efficient ET. Finally, the proposed scheme is evaluated by executing the smart contract using Remix Integrated Development Environment (IDE) with various performance metrics such as gas consumption (SF5 acquires maximum value of 186571 gas) and cost (execution (SF5 acquires maximum value of 120371 gas) and transaction cost (SF4 acquires maximum value of 124865 gas) ) analysis. Additionally, security analysis of the proposed scheme is tested using Echidna tool which shows the working of the smart contract without any vulnerability and bug.
With the rapid development and technological innovation in the energy market, peer-to-peer (P2P) energy trading, as a decentralised and efficient trading model, has been widely studied and practically applied. However, in P2P energy transactions involving multiple prosumers, there are challenges such as information asymmetry, trust issues, and transaction transparency. To address these challenges, blockchain technology, as a distributed ledger technology, provides solutions. In this paper, we propose a blockchain technology-based prosumer–virtual power plant (VPP) two-tier interactive energy management framework to assist P2P energy transactions between multiple prosumers. In this framework, the virtual power plant acts as a leader and sets differentiated tariffs for different prosumers to equal the distribution of social welfare. The various prosumers act as followers and respond to the leader’s decisions in a cooperative manner. Blockchain’s immutability and transparency enable prosumers to participate in P2P energy trading with greater trust, share idle energy, and share revenues based on contribution. In addition, given the uncertainty of renewable energy, this paper employs a stochastic planning approach with conditional value at risk (CVaR) to describe the expected loss of VPP. Ultimately, as verified by the arithmetic simulation, the blockchain co-governance transaction model effectively supports energy coordination and optimization of complementarities while ensuring the utility of each transaction node. This model promotes the application of renewable energy in local consumption, while facilitating the innovation and sustainable development of the energy market.
The rise of distributed energy generation through solar panels in homes and businesses sparks the creation of fresh energy markets. This shift removes the old boundaries between energy suppliers and users, leading to the emergence of energy “prosumers.” Blockchain technology enhances safe and affordable direct energy swaps within a decentralized setup, employing encryption and consensus checks. The research utilized a unique approach called “Agent-Based Modeling (ABM) along with Geographic Information System (GIS)” to assess energy trading within the real estate sector. This process encompassed gathering and analyzing data about daily energy consumption to grasp market dynamics and construct a decentralized energy trading approach. The initial simulation involved five key stages: collecting, processing, predicting, analyzing, confirming, and evaluating performance. The primary actors in this model were individuals, consumers, energy providers, and producers. The outcomes from the experiments indicated that one could assess the distinct households' features by incorporating GIS data and an agent-centric model. Harnessing high-performance computing makes it possible to manage large-scale simulations involving multiple participants. Generally, this approach is anticipated to enhance the model's efficiency and offer a flexible environment for scrutinizing how energy blockchain impacts finance, technology, and society.