Julia Groza, Seyyed Ali Sadat, Koami Soulemane Hayibo, Joshua M. Pearce
To assist electric utilities to overcome limitations of centralized billing and encourage distributed production of solar photovoltaic (PV) electricity, this study designs and assesses a novel open-source autonomous virtual utility to monitor users and enable peer-to-peer trading. This study provides system design and software implementation of the concept using blockchain technology written in Solidity and Truffle. A set of smart contracts adds users to a system and monitors their demand, PV generation, and facilitates transactions between users on an hourly basis when one user has PV-generated excess electricity, and another has demand. Unit tests for each of the contracts’ methods are developed in Solidity, and data on gas usage and costs is collected. Once the contracts have been written and evaluated, a JavaScript simulation is developed to use the contracts on real load and PV generation data for one year on an hourly basis. The results of two case studies are quantified: 1) true peers, where all houses are prosumers with rooftop PV, and 2) intermittent transition case, where PV deployment and demand are more varied. The results found that with ten users in the system, the true peers case study resulted in an uneconomic number of exchanges, but the intermittent transition case study resulted in more than a factor of twenty increases in exchanges and net cost savings. The savings more than doubles for both cases when time of use pricing is in effect. The system utility increases with more variability of PV production across participating users and is recommended for utilities targeting increases in distributed generation during the energy transition.
Abdullah Umar, Deepak Kumar, T. K. Ghose, Thamer A. H. Alghamdi · 5 authors
The integration of distributed energy resources (DERs) and digital technologies has accelerated the transition to decentralized energy systems. Among these technologies, blockchain stands out for its ability to facilitate peer-to-peer (P2P) energy trading efficiently and securely. This paper explores the concept of P2P energy trading within community microgrid systems, leveraging blockchain-based smart contracts. The proposed system integrates an incentive-driven demand response program directly into the smart contract framework, offering real-time rewards for load-balancing contributions. By incorporating the microgrid’s Energy Management System (EMS) and transparently recording all transactions on the blockchain, the proposed platform provides detailed data and immediate reward distribution. At the core of our system lies the Supply to Demand Ratio (SDR), ensuring fair energy exchange within the community. Dynamic pricing, enabled by blockchain and Tether (USDT) cryptocurrency, adjusts to real-time market conditions, enhancing transparency and responsiveness in energy trading. This adaptive pricing model fosters a more equitable and efficient trading environment compared to static approaches. Moreover, this system is tailored for community microgrids, emphasizing a community-centric approach. Local prosumers serve as validators in the blockchain network, aligning energy management decisions with community needs and dynamics. This localized engagement promotes efficiency and participation, fostering resilient, sustainable, and user-centric energy landscapes. Through rigorous analysis, we demonstrate the system’s effectiveness in optimizing economic efficiency, reducing operational costs, and increasing compliance rates. By combining blockchain technology with community-focused design principles, the proposed platform represents a significant advancement towards self-sufficiency and resilience in local energy systems.
N. B. Sai Shibu, Aryadevi Remanidevi Devidas, S. Balamurugan, Seshaiah Ponnekanti · 5 authors
Power outages can severely affect individuals, businesses, and communities, leading to disruptions, economic losses, and safety risks. The existing power recovery strategies often fail to adequately address the challenges associated with such outages. These challenges encompass a range of complexities, including resource allocation disparities, efficient prosumer integration, energy demand variability, and isolated generators. This paper presents a microgrid-centric power recovery strategy that leverages IoT, blockchain, smart contracts, and optimisation techniques for peer-to-peer energy sharing within the microgrid. The proposed strategy comprehensively addresses the challenges associated with the existing power recovery strategies. The paper outlines the system architecture for IoT and blockchain-enabled microgrids, discusses the mathematical modelling for energy sharing, and explores cost-optimal power restoration strategies. An incentive mechanism motivates prosumers to support restoration strategies during outages. Furthermore, the paper describes a blockchain smart contract facilitating peer-to-peer energy exchange in regions affected by power outages. This approach can mitigate the disruptive impact of power outages by providing reliable and community-centric power recovery solutions. Through validation with real-world data from our university’s distribution grid test bed, Mean Time To Recover (MTTR) analysis and performance evaluations using the Hyperledger Caliper benchmark tool, this paper demonstrates its feasibility and effectiveness, paving the way for enhanced power recovery strategies and increased resilience in the face of energy disruptions.
Nebojša Horvat, Dušan Gajić, Petar Trifunović, Veljko Petrović · 6 authors
Distributed ledger technology (DLT) and blockchain-based energy trading solutions are often labeled as resource-hungry, excessive power consumers which consequently create a significant carbon footprint. Using this approach to energy trading, without simultaneously minimizing energy consumption, defeats the purpose of using such trading solutions to encourage renewable energy production and may even cancel out any ecological benefits. This paper demonstrates that it is possible to create a DLT-based energy trading system which provides security, transparency, autonomy, scalability, and decentralization, provided by using a DLT, but with significantly lower penalties than other previously known solutions. This is best illustrated through the fact that the carbon footprint per transaction of the solution presented in this paper is 0.19 grams of$CO_{2}$compared to 20 grams of$CO_{2}$created by single transaction of similar complexity on the Ethereum blockchain. This makes per-transaction carbon footprint of our system approximate 100 times smaller than that of the most commonly used Ethereum blockchain. We present the architecture and features of the proposed platform, as well as a thorough analysis of its performance, including power consumption and estimated carbon footprint. All experiments are done on a dedicated Beowulf cluster comprised of general-purpose computers. The cluster mimics a microgrid environment and presents a testing ground for real-world performance and power consumption analysis of a system used for trading energy predominantly produced from prosumers and their renewable sources.
In the 21st century, transitioning to renewable energy sources is imperative, with fossil fuel reserves depleting rapidly and recognizing critical environmental issues such as climate change, air pollution, water pollution, and habitat destruction. Embracing renewable energy is not only an environmental necessity but also a strategic move with multiple benefits. By shifting to renewable energy sources and supporting their production through the acquisition of renewable energy certificates, we foster innovation and drive economic growth in the renewable energy sector. This, in turn, reduces greenhouse gas emissions, aligning with global efforts to mitigate climate change. Additionally, renewable energy certificates ensure compliance with regulations that mandate the use of renewable energy, enhancing legal adherence while promoting transparency and trust in energy sourcing. To monitor the uptake of renewable energy, governments have implemented Renewable Energy Certificates (RECs) as a tracking mechanism for the production and consumption of renewable energy. However, there are two main challenges to the existing REC schema: 1) The RECs have not been globally adopted due to inconsistent design; 2) The consumer privacy has not been well incorporated in the design of blockchain. In this study, we investigate the trading of RECs between suppliers and consumers using the directed acyclic graph (DAG) blockchain system and introduce a trading schema to help protect consumer information. Our results demonstrate lower transaction time by 41\% and energy consumption by 65\% compared to proof-of-stake.
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.
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.
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.
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}.
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.
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.
Transactive Energy Markets (TEM) have the potential to reduce wasted energy, increase the utilisation of renewable energy resources and enable independence in the energy sector. Blockchain has been utilised in TEMs in the literature aiming to acquire transparency, security and trustless operations. Though public blockhain enables leveraged transparency and fairness, the majority of proposals suggest adoption of private or consortium blockchains mainly due to performance concerns. In this paper, we created a TEM environment where consumers, prosumers and suppliers bid for price agreement upon a game theory model and then deployed it on localised Ethereum blockchain infrastructure. To compare the performance, we created a centralized TEM environment keeping all the settings the same. The obtained results show that public blockchains may be adaptable to TEMs to enhance system transparency and fairness as well as automated and trustless transactions. Conducted test results show that our proposal exhibit a similar scalability trend as the referenced centralized system.
Mikhak Samadi, Sushmita Ruj, Henry Schriemer, Melike Erol‐Kantarci
Demand response (DR) has been studied widely in the smart grid literature, however, there is still a significant gap in approaches that address security, privacy, and robustness of settlement processes simultaneously. The need for security and robustness emerges as a vital property, as Internet of Things (IoT) devices become part of the smart grid; in the form of smart meters, home energy management systems (HEMSs), intelligent transformers, and so on. In this paper, we use energy blockchain to secure energy transactions among customers and the utility. In addition, we formulate a mixed-strategy stochastic game model to address uncertainties in DR contributions of agents and achieve optimal demand response decisions. This model utilizes the processing hardware of customers for block mining, stores customer DR agreements as distributed ledgers, and offers a smart contract and consensus algorithm for energy transaction validation. We use a real dataset of residential demand profiles and photovoltaic (PV) generation to validate the performance of the proposed scheme. The results show the impact of electric vehicle (EV) discharging and customer demand reduction on increasing the probability of successful block mining and improving customer profits. Moreover, the results demonstrate the security and robustness of our consensus algorithm for detecting malicious activities.
The emergence of distributed energy and prosumers has greatly promoted the reform of the energy market. Blockchain technology provides a very potent solution for distributed energy transactions, however, blockchain technology still develops slowly in the energy field due to the unstable performance of the imperfect system. This paper aims to narrow this gap by the following steps. First, a function-driven integration method is proposed to combine the merit of blockchain distributed ledger and traditional centralized databases. Then a hybrid energy blockchain system architecture is designed, including the blockchain layer, smart contract layer, database layer, and client layer. Further, a peer-to-peer market mechanism considering energy storage arbitrage and fully automated matchmaking is developed on the hybrid blockchain system. The case study proves the effectiveness and safety of the system. The proposed architecture of combined blockchain and database technologies effectively paves the way for constructing a more reasonable and feasible distributed energy trading platform.
Intelligent predictive models are fundamental in peer-to-peer (P2P) energy trading as they properly estimate supply and demand variations and optimize energy distribution, and the other featured values, for participants in decentralized energy marketplaces. Consequently, DeepResTrade is a research work that presents an advanced model for predicting prices in a given traditional energy market. This model includes numerous fundamental components, including the concept of P2P trading systems, long-term and short-term memory (LSTM) networks, decision trees (DT), and Blockchain. DeepResTrade utilized a dataset with 70,084 data points, which included maximum/minimum capacities, as well as renewable generation, and price utilized of the communities. The developed model obtains a significant predictive performance of 0.000636% Mean Absolute Percentage Error (MAPE) and 0.000975% Root Mean Square Percentage Error (RMSPE). DeepResTrade’s performance is demonstrated by its RMSE of 0.016079 and MAE of 0.009125, indicating its capacity to reduce the difference between anticipated and actual prices. The model performs admirably in describing actual price variations in, as shown by a considerable R2 score of 0.999998. Furthermore, F1/recall scores of [1, 1, 1] with a precision of 1, all imply its accuracy.
With the rapid development of blockchain technology, blockchain-based neural network short-term power demand forecasting has become a research hot spot in the power industry. This paper aims to combine neural network algorithms with blockchain technology to establish a trustworthy and efficient short-term demand forecasting model. By leveraging the distributed ledger and immutability features of blockchain, we ensure the security and reliability of power demand data. Meanwhile, short-term power demand forecasting research using neural networks has the potential to increase the stability of the power system and offer opportunities for improved operations. In this paper, the root mean-square-error model evaluation indicator was used to compare the back propagation (BP) neural network algorithm and the traditional forecasting algorithm. The evaluation was performed on the randomly selected five household power datasets. The results show that, by comparing the long short-term memory network (LSTM) model with the BP neural network model, it was determined that the average prediction impact increases by about 25.7% under stable power demand. The short-term power prediction model of the BP neural network has the average error values more than two times lower than the traditional prediction model. It was shown that the use of the BP neural network algorithm and blockchain could increase the accuracy of short-term power demand forecasting, allowing the neural network-based algorithm to be implemented and taken into account in the research on short-term power demand forecasting.
The rapid adoption of hydrogen as an eco-friendly energy source has necessitated the development of intelligent power management systems capable of efficiently utilizing hydrogen resources. However, guaranteeing the security and integrity of hydrogen-related data has become a significant challenge. This paper proposes a pioneering approach to ensure secure hydrogen data analysis through the integration of blockchain technology, enhancing trust, transparency, and privacy in handling hydrogen-related information. By combining blockchain with intelligent power management systems, the efficient utilization of hydrogen resources becomes feasible. The utilization of smart contracts and distributed ledger technology facilitates secure data analysis, real-time monitoring, prediction, and optimization of hydrogen-based power systems. The effectiveness and performance of the proposed approach are demonstrated through comprehensive case studies and simulations. Notably, our prediction models, including ABiLSTM, ALSTM, and ARNN, consistently delivered high accuracy with MAE values of approximately 0.154, 0.151, and 0.151, respectively, enhancing the security and efficiency of hydrogen consumption forecasts. The blockchain-based solution offers enhanced security, integrity, and privacy for hydrogen data analysis, thus contributing to the advancement of clean and sustainable energy systems. Additionally, the research identifies existing challenges and outlines potential future directions for further enhancing the proposed system. This study adds to the growing body of research on blockchain applications in the energy sector, with a specific focus on secure hydrogen data analysis and intelligent power management systems.
Blockchain technology and renewable energy links can realize the fusion of energy flow and information flow. The combination of the two has a high degree of matching, and the related research is also increasing. Although experts have expanded their research on renewable energy and blockchain, there are still restrictions and gaps in the existing research. In this paper, 920 articles from 2016 to 2023 were chosen and visualized using bibliometrics and CiteSpace software to analyze the research field's development base, collaborative groups, hot topics and evolutionary trends. Based on the foregoing research, we summarized the pertinent literature in the area of “Renewable energy & Blockchain” and thoroughly analyzed the current hot issues in depth to determine the future development direction. The findings show that, first, related research in the field increased rapidly in 2016–2023, the research topics and hotspots of “Renewable energy & Blockchain” focus on energy system optimization, clean energy technologies, circular development and renewable energy trading. Second, all subjects have a specific strength and influence contribution in the field, from the micro to the macro level. Among them, China, the United States and their universities have relatively mature research experience and research ability. Third, research gaps in blockchain-based renewable energy application, technology, and policy, as well as potential trends in energy internet, energy management, energy systems, green certificate trading, and green power trading. This study provides researchers with a theoretical foundation for gaining a thorough understanding of current research efforts and future research directions in this field.
As the current global environment is deteriorating, distributed renewable energy is gradually becoming an important member of the energy internet. Blockchain, as a decentralized distributed ledger with decentralization, traceability and tamper-proof features, is an important way to achieve efficient consumption and multi-party supply of new energy. In this article, we establish a blockchain-based mathematical model of multiple microgrids and microgrid aggregators’ revenue, consider the degree of microgrid users’ preference for electricity thus increasing users’ reliance on the blockchain market, and apply the one-master-multiple-slave Stackelberg game theory to solve the energy dispatching strategy when each market entity pursues the maximum revenue. The simulation results show that the blockchain-based dynamic game of the multi-microgrid market can effectively increase the revenue of both microgrids and aggregators and improve the utilization of renewable energy.
Xiaole Su, Yuanchao Hu, Liu Wei, Zhipeng Jiang · 7 authors
Abstract The extension of emerging renewable energy sources such as wind and water turbines, solar panels, and the increasing usage of electric vehicles requires the supply and distribution of energy in a small device on local scale and it has created new methods of supplying and selling electricity. Middle buyers and end users can obtain the local energy with the peer‐to‐peer trading method in this large and hierarchical market. This method enables market to manage and exchange the electricity between major suppliers and medium and local levels. Blockchain technology is developing in peer‐to‐peer exchange of electricity and acts as a reliable, efficient, and safe technology in the electricity trading market. In this method, while preserving the privacy of electricity users, by using smart contracts and by removing intermediaries in the energy supply and demand market, direct commercial interactions between energy suppliers and consumers are done. The blockchain technology, while creating trust between the parties in the energy market, reduces the cost of electricity trading and increases its scalability with using the intermediate energy aggregators. In this research, the blockchain‐based model, is presented for distribution and peer‐to‐peer transactions in the energy market. The suggested model provides the possibility of registration low‐cost instant transactions at the power grid in any specific period of time. The above method, unlike periodic payments, provides immediate access to bills and small payments. Since the transactions outside the blockchain chain are not recorded, this system guarantees its honest and independent operation without fraud and failure. The smart contract method based on blockchain, reduces the transaction fees and speeds up electricity trading. Also, the experimental investigation in 20 nodes shows the time required to determine the exchange contract in the blockchain method. The average is improved by 49.7% in this method. Also, the negotiation convergence time has become 47% faster.
J. P. Gupta, Sanskar Jain, Suprava Chakraborty, Владимир Панченко · 6 authors
Advancing the sustainable energy transition is a major need in nations that are constantly evolving and developing in terms of their energy economy. India has been chosen for the purpose of analysis due to the heterogenous nature of its polity, topographies, infrastructural capabilities and diverse framework. In accordance with the sustainable development goals proposed by the UN, a metamorphosis is observed within the renewable energy sector of the nation. Blockchain technology that facilitates a transparent transition is incorporated on various upcoming platforms. This is backed up by peer-to-peer trading of energy providing a prosumer with an autonomous environment. The goal of this paper is to highlight the struggles and challenges faced by the energy sector as it takes up unconventional and non-traditional approaches within the country. It also aims to discover potential ways that would help a nation like India facilitate such a transition by studying its ongoing trends. The need is eminent for a practical study that is specific to a developing nation like India in terms of P2P energy trading enabled by blockchain technology to promote the use of open-sourced electricity and achieve a decentralized system.