Skip to main content

MINI REVIEW article

Front. Energy Res., 21 April 2021
Sec. Smart Grids
Volume 9 - 2021 | https://doi.org/10.3389/fenrg.2021.671133

Application of Blockchain Technology in Energy Trading: A Review

Hongbiao Li1 Fan Xiao2 Lixin Yin3* Fengtong Wu4
  • 1School of Computer Science, Northeast Electric Power University, Jilin, China
  • 2School of Electrical and Electronic Engineering, North China Electric Power University, Beijing, China
  • 3State Grid Xinyuan Fengman Training Center, Jilin, China
  • 4School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China

As blockchain and energy trading have become hot topics in industry and academia, this paper presents a brief literature regarding the blockchain-based energy trading in the fields of energy trading with blockchain. At first, the background and development process is presented, and then the applications of blockchain in energy trading are surveyed and analyzed. Finally, conclusions are summarized and important directions are highlighted in this field.

Introduction

At present, as the environmental pollution issue is becoming more and more serious, the disadvantages of the centralized energy system, such as the heavy loss of energy in the long-distance transmission and distribution process, and the low fault-tolerant ability of the system, are becoming prominent. The development of decentralized renewable energy technology has gained attention; however, its storage and redistribution process can not be satisfied through the current centralized system. Meanwhile, some researchers put forward the idea of blockchain-based energy trading (Zhang et al., 2017; Pee et al., 2019), and some projects have been successfully implemented (Laszka et al., 2018b; Mengelkamp et al., 2018). The construction of an energy trading platform and trading mechanism based on blockchain has become a hot topic. This paper presents a systematic literature review of studies and projects based on blockchain-based energy trading, as proposed in papers published in recent years. Considering that energy trading based on blockchain is still at an early stage, this paper divides the current research focus into four aspects: (1) construction of trading platform; (2) economy, privacy, and security of transaction mechanism; (3) redundancy and scalability of trading platform; (4) implementation of the specific technology of trading platform.

The rest of this paper is organized as follows. In section The Background and Development Process, the background of the research problem and the development process are introduced. Section Application of Blockchain in Energy Trading describes four key issues and analyzes the corresponding research status. Conclusions and future development trends are explained in section Conclusion.

The Background and Development Process

Microgrid Energy Markets

Renewable energy plays an important role in reshaping the future of energy industry, which can be integrated into power systems, in various forms, such as active distribution networks (Li et al., 2018a), integrated energy systems (Li et al., 2020), and microgrids (Li et al., 2018d). In this context, how to maximize the utilization of renewable energy by managing micro-grid markets is becoming a hot topic from academia to industry. Papaefthymiou and Dragoon (2016) elaborated on how to transform the traditional power systems into systems with 100% renewable energy. Similarly, Hanna et al. (2017) stressed the importance of policy support; to find the optimal operation mode to model the microgrid, Hanna et al. (2017) found that only with the support of policies, the microgrid will be able to achieve the lowest cost operation and environment friendly factors. Li et al. (2018c) presented a scheduling scheme of microgrids with an electric vehicle battery swapping station, taking into consideration, the real-time pricing mechanism. Li et al. (2019) put forward a multi-objective microgrid dispatch strategy considering the user experience. To ensure the benefit of microgrid participants, Kuznetsova et al. (2014) put forward the individual goal of stakeholders to optimize microgrid energy management framework. Furthermore, in terms of economic efficiency optimization, Montuori et al. (2014) proposed the optimization model, hybrid optimization of multiple energy resources (HOMER), to evaluate the economic efficiency of the microgrid with a biomass gasification power plant. Demand response management (DSM) has experienced a renaissance since microgrids require a flexible demand-side to simplify system operations (Palensky and Dietrich, 2011), but the use of DSM in microgrids does not take the advantage of the development of renewable energy sources in the long run, and reflects the needs of socio-economic development. An improved scheme based on the blockchain was put forward by Noor et al. (2018).

Li and Li (2019) proposed a microgrid dispatch strategy taking into account, the demand response of electric vehicles. By combing the advantages of DSM and blockchain technology, Li and Li (2019) presented a game-theoretic model for DSM within microgrid networks that were enhanced by blockchain, and which realized payment mechanisms and intelligent decentralized control.

Blockchain Technology

Blockchain technology provides a powerful tool for implementing energy trading. In 2019, Nakamoto (2019) presented a peer-to-peer (P2P) network, which employed proof-of-work to record a public history of the transaction, and this consensus mechanism can enforce any needed rules and incentives. That was the beginning of the blockchain-based research. Dong et al. (2018) described the blockchain as a distributed, redundant, chain-connected, ledger-sharing database, in which each node in the network is fault-tolerant and can achieve point-to-point communication.

There are four key characters of blockchain: (1) decentralized distributed nodes and storage; (2) consensus, smart contract, and asymmetric encryption, which enable it to have huge potential in many domains, such as finance, computer software, and computer applications; (3) the information economy and postal economy, such as investment and securities; (4) the shared health-care data framework, generation, and distribution in the citizen-level microgrid which may benefit from the widespread dissemination of blockchain transactions (Giungato et al., 2017).

Andoni et al. (2019) presented an overall review of blockchain technology, which involved 140 blockchain research projects and initiatives. However, most of the related studies are still in their infancy. Some social factors, such as laws and policies will also have an impact on the later development of blockchain technology. More specifically, Ali et al. (2018) presented an extensive survey of the application of blockchain in the internet of things (IoT), demonstrating the potential advantages of blockchain in some aspects, such as privacy, secured communications, identity, and data management as well as monetization of IoT data and resources. Fan et al. (2018) modeled the pricing and transaction of energy-internet electricity, based on the blockchain and big data, which provided a reference for the parties involved, including producers, consumers, and managers.

Application of Blockchain in Energy Trading

Since most studies related to energy trading based on blockchain are still in the initial stage, according to different research focuses, this paper divides relevant studies into the following four aspects: (1) construction of trading platform; (2) study on the economy, privacy, and security of transaction mechanism; (3) the latency and scalability of trading platform; (4) implementation of the specific technology of trading platform.

Design and Construction of a Trading Platform

Integrated demand response (IDR) has been proven to be effective in improving the operating flexibility of the system and energy utilization efficiency through optimization of the operations of flexible loads, energy conversion, and storage equipment on the demand side (Li et al., 2021). To make the full use of the integrated scattered IDR resources, Zhao et al. (2018a,b) presented an energy transaction mechanism based on the blockchain technology. Moreover, Mannaro et al. (2017) have launched the Crypto-Trading Project, where, they highlighted the key role of blockchain technology and smart contracts in the management and control of innovation typology of the energy market.

Privacy, Security, and Economy of Transaction Mechanism

To solve the privacy problem of energy transactions, Zhou et al. (2018), Laszka et al. (2018a), and Tan et al. (2019) proposed different solutions, respectively. Aiming at the security and privacy issues of large scale vehicle to grid (V2G) energy trading, Zhou et al. (2018) developed a consortium of blockchain-based energy trading mechanism and an edge computing-based task offloading for V2G and local energy aggregators (LEAGs), respectively, and the validation of the proposed framework was proved from the perspectives of task offloading and security. Laszka et al. (2018a), considered not only privacy but also resilience problem, and they provided a novel distribution application platform. Tan et al. (2019) designed a model for privacy-preserving energy scheduling based on the energy blockchain network in which they solved the problem by using Lagrangian relaxation and smart contracts.

In terms of the economy of the trading platform, Park et al. (2018) suggested a blockchain-based P2P energy transaction platform and provided simulation results that calculated and compared the economic benefit of the platform. Considering the huge operational overhead resulted from a high-frequency transaction, Hou et al. (2019) designed a scheme that enabled nodes to satisfy their power loads through locally stored energy (self-sufficiency), before participating as sellers, if they still had considerable surplus electricity. Alcarria et al. (2018) presented a blockchain-based authorization system for trustworthy resource monitoring and trading.

Latency and Scalability of Trading Platform

To solve the issues of latency resulted from processing the energy trading decisions at remote control centers and the security concerns, while trading the energy, Jindal et al. (2019) proposed a blockchain-based edge-as-a-service framework, which used a software-defined network (SDN) architecture to reduce the latency and secured the underlying trading transactions by blockchain. Blom and Farahmand (2018) modeled a local energy market using Ethereum platform and concluded that the given market with 600 participants and a trading frequency of one transaction every 5 min can be processed by the Ethereum protocol. Besides, Liu et al. (2019) provided the off-chain energy trading method and asynchronous transaction recoding mechanism, which are supported by a local energy trading cyber-physical system.

Implementation of Specific Technology of Trading Platform

In addition to the research and analysis of the characteristics of blockchain, the implementation of the algorithm is also the focus of the current research problem. Kang et al. (2018) exploded a renewable energy trading platform using smart contract of Ethereum, proved its scalability and adaptability utilizing coding transaction process and contents of smart contracts, and presented a simple scenario for two nodes. Pipattanasomporn et al. (2018) presented the laboratory scale implementation of the blockchain network for the exchange of solar energy. Tai et al. (2016) provided an improved algorithm of distributed security checking and proved the feasibility by a case consisting of six nodes.

However, all the schemes mentioned above are in the initial exploration stage, and the verified schemes and scale are in an ideal environment or laboratory environment. Therefore, there is still a way to go before the blockchain-based energy trading platform can be widely used in practical applications.

Conclusion

As an emerging and powerful technology, energy trading based on blockchain has attracted a growing attention of many scholars. After studying the existing literature, this paper summarizes the key issues into the following four points: (1) construction of trading platform; (2) economy, privacy, and security of transaction mechanism; (3) redundancy and scalability of trading platform; (4) implementation of the specific technology of trading platform.

Since most studies are in the primary stage, the construction of an energy trading platform and efficient algorithm implementation will be important research directions in the future. Another interesting topic is to apply machine learning to blockchain-based applications (Shi et al., 2008; Li et al., 2018b; Tanwar et al., 2019).

Author Contributions

HL, FX, and LY contributed to conception and design of the study. HL and FX performed the statistical analysis. HL wrote the first draft of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

Alcarria, R., Bordel, B., Robles, T., Martín, D., and Manso-Callejo, M. Á. (2018). A blockchain-based authorization system for trustworthy resource monitoring and trading in smart communities. Sensors 18:3561. doi: 10.3390/s18103561

PubMed Abstract | CrossRef Full Text | Google Scholar

Ali, M. S., Vecchio, M., Pincheira, M., Dolui, K., Antonelli, F., and Rehmani, M. H. (2018). Applications of blockchains in the internet of things: a comprehensive survey. IEEE Commun. Surv. Tutor. 21, 1676–1717. doi: 10.1109/COMST.2018.2886932

CrossRef Full Text | Google Scholar

Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., et al. (2019). Blockchain technology in the energy sector: a systematic review of challenges and opportunities. Renew. Sustain. Energy Rev. 100, 143–174. doi: 10.1016/j.rser.2018.10.014

CrossRef Full Text | Google Scholar

Blom, F., and Farahmand, H. (2018). “On the scalability of blockchain-supported local energy markets,” in 2018 International Conference on Smart Energy Systems and Technologies (SEST) (Seville: IEEE), 1–6. doi: 10.1109/SEST.2018.8495882

CrossRef Full Text | Google Scholar

Dong, Z., Luo, F., and Liang, G. (2018). Blockchain: a secure, decentralized, trusted cyber infrastructure solution for future energy systems. J. Mod. Power Syst. Clean Energy 6, 958–967. doi: 10.1007/s40565-018-0418-0

CrossRef Full Text | Google Scholar

Fan, T., He, Q., Nie, E., and Chen, S. (2018). “A study of pricing and trading model of Blockchain & Big data-based Energy-Internet electricity,” in IOP Conference Series: Earth and Environmental Science (Chongqing: IOP Publishing), 052083. doi: 10.1088/1755-1315/108/5/052083

CrossRef Full Text | Google Scholar

Giungato, P., Rana, R., Tarabella, A., and Tricase, C. (2017). Current trends in sustainability of bitcoins and related blockchain technology. Sustainability 9:2214. doi: 10.3390/su9122214

CrossRef Full Text | Google Scholar

Hanna, R., Ghonima, M., Kleissl, J., Tynan, G., and Victor, D. G. (2017). Evaluating business models for microgrids: interactions of technology and policy. Energy Policy 103, 47–61. doi: 10.1016/j.enpol.2017.01.010

CrossRef Full Text | Google Scholar

Hou, W., Guo, L., and Ning, Z. (2019). Local electricity storage for blockchain-based energy trading in industrial internet of things. IEEE Trans. Ind. Inform. 15, 3610–3619. doi: 10.1109/TII.2019.2900401

CrossRef Full Text | Google Scholar

Jindal, A., Aujla, G. S., and Kumar, N. (2019). SURVIVOR: a blockchain based edge-as-a-service framework for secure energy trading in SDN-enabled vehicle-to-grid environment. Comput. Netw. 153, 36–48. doi: 10.1016/j.comnet.2019.02.002

CrossRef Full Text | Google Scholar

Kang, E. S., Pee, S. J., Song, J. G., and Jang, J. W. (2018). “A blockchain-based energy trading platform for smart homes in a microgrid,” in 2018 3rd International Conference on Computer and Communication Systems (ICCCS) (IEEE), 472–476. doi: 10.1109/CCOMS.2018.8463317

CrossRef Full Text | Google Scholar

Kuznetsova, E., Li, Y. F., Ruiz, C., and Zio, E. (2014). An integrated framework of agent-based modelling and robust optimization for microgrid energy management. Appl. Energy 129, 70–88. doi: 10.1016/j.apenergy.2014.04.024

CrossRef Full Text | Google Scholar

Laszka, A., Eisele, S., Dubey, A., Karsai, G., and Kvaternik, K. (2018b). “TRANSAX: a blockchain-based decentralized forward-trading energy exchanged for transactive microgrids,” in 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS) (Singapore: IEEE), 918–927.

Google Scholar

Laszka, A., Eisele, S., Dubey, A., Karsai, G., and Kvaternik, K. (2018a). “TRANSAX: a blockchain-based decentralized forward-trading energy exchanged for transactive microgrids,” in 2018 IEEE 24th International Conference on Parallel and Distributed Systems (ICPADS) (IEEE), 918–927. doi: 10.1109/PADSW.2018.8645001

CrossRef Full Text | Google Scholar

Li, Y., Feng, B., Li, G., Qi, J., Zhao, D., and Mu, Y. (2018a). Optimal distributed generation planning in active distribution networks considering integration of energy storage. Appl. Energy 210, 1073–1081. doi: 10.1016/j.apenergy.2017.08.008

CrossRef Full Text | Google Scholar

Li, Y., and Li, K. (2019). Incorporating demand response of electric vehicles in scheduling of isolated microgrids with renewables using a bi-level programming approach. IEEE Access 7, 116256–116266. doi: 10.1109/ACCESS.2019.2936487

CrossRef Full Text | Google Scholar

Li, Y., Wang, C., Li, G., and Chen, C. (2021). Optimal scheduling of integrated demand response-enabled integrated energy systems with uncertain renewable generations: a Stackelberg game approach. Energy Convers. Manag. 235:113996. doi: 10.1016/j.enconman.2021.113996

CrossRef Full Text | Google Scholar

Li, Y., Wang, C., Li, G., Wang, J., Zhao, D., and Chen, C. (2020). Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings. Energy Convers. Manag. 207:112526. doi: 10.1016/j.enconman.2020.112526

CrossRef Full Text | Google Scholar

Li, Y., Wang, J., Zhao, D., Li, G., and Chen, C. (2018b). A two-stage approach for combined heat and power economic emission dispatch: Combining multi-objective optimization with integrated decision making. Energy 162, 237–254. doi: 10.1016/j.energy.2018.07.200

CrossRef Full Text | Google Scholar

Li, Y., Yang, Z., Li, G., Mu, Y., Zhao, D., Chen, C., et al. (2018c). Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: a bi-level programming approach via real-time pricing. Appl. Energy 232, 54–68. doi: 10.1016/j.apenergy.2018.09.211

CrossRef Full Text | Google Scholar

Li, Y., Yang, Z., Li, G., Zhao, D., and Tian, W. (2018d). Optimal scheduling of an isolated microgrid with battery storage considering load and renewable generation uncertainties. IEEE Trans. Ind. Electron. 66, 1565–1575. doi: 10.1109/TIE.2018.2840498

CrossRef Full Text | Google Scholar

Li, Y., Yang, Z., Zhao, D., Lei, H., Cui, B., and Li, S. (2019). Incorporating energy storage and user experience in isolated microgrid dispatch using a multi-objective model. IET Renew. Power Gener. 13, 973–981. doi: 10.1049/iet-rpg.2018.5862

CrossRef Full Text | Google Scholar

Liu, S., Chen, F., Shen, L., Hu, Y., and Ding, Y. (2019). A high-performance local energy trading cyber-physical system based on blockchain technology. Earth Environ. Sci. 227:032009. doi: 10.1088/1755-1315/227/3/032009

CrossRef Full Text | Google Scholar

Mannaro, K., Pinna, A., and Marchesi, M. (2017). “Crypto-trading: blockchain-oriented energy market,” in 2017 AEIT International Annual Conference (Cagliari: IEEE), 1–5. doi: 10.23919/AEIT.2017.8240547

CrossRef Full Text | Google Scholar

Mengelkamp, E., Gärttner, J., Rock, K., Kessler, S., Orsini, L., and Weinhardt, C. (2018). Designing microgrid energy markets: a case study: the brooklyn microgrid. Appl. Energy 210, 870–880. doi: 10.1016/j.apenergy.2017.06.054

CrossRef Full Text | Google Scholar

Montuori, L., Alcázar-Ortega, M., Álvarez-Bel, C., and Domijan, A. (2014). Integration of renewable energy in microgrids coordinated with demand response resources: economic evaluation of a biomass gasification plant by Homer Simulator. Appl. Energy 132, 15–22. doi: 10.1016/j.apenergy.2014.06.075

CrossRef Full Text | Google Scholar

Nakamoto, S. (2019). Bitcoin: A Peer-to-Peer Electronic Cash System. Manubot.

Google Scholar

Noor, S., Yang, W., Guo, M., van Dam, K. H., and Wang, X. (2018). Energy demand side management within micro-grid networks enhanced by blockchain. Appl. Energy 228, 1385–1398. doi: 10.1016/j.apenergy.2018.07.012

CrossRef Full Text | Google Scholar

Palensky, P., and Dietrich, D. (2011). Demand side management: demand response, intelligent energy systems, and smart loads. IEEE Trans. Ind. Inform. 7, 381–388. doi: 10.1109/TII.2011.2158841

CrossRef Full Text | Google Scholar

Papaefthymiou, G., and Dragoon, K. (2016). Towards 100% renewable energy systems: uncapping power system flexibility. Energy Policy 92, 69–82. doi: 10.1016/j.enpol.2016.01.025

CrossRef Full Text | Google Scholar

Park, L. W., Lee, S., and Chang, H. (2018). A sustainable home energy prosumer-chain methodology with energy tags over the blockchain. Sustainability 10:658. doi: 10.3390/su10030658

CrossRef Full Text | Google Scholar

Pee, S. J., Kang, E. S., Song, J. G., and Jang, J. W. (2019). “Blockchain based smart energy trading platform using smart contract,” in 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC) (Okinawa: IEEE), 322–325. doi: 10.1109/ICAIIC.2019.8668978

CrossRef Full Text | Google Scholar

Pipattanasomporn, M., Kuzlu, M., and Rahman, S. (2018). “A blockchain-based platform for exchange of solar energy: laboratory-scale implementation,” in 2018 International Conference and Utility Exhibition on Green Energy for Sustainable Development (ICUE) (IEEE), 1–9. doi: 10.23919/ICUE-GESD.2018.8635679

CrossRef Full Text | Google Scholar

Shi, Z. B., Yu, T., Zhao, Q., Li, Y., and Lan, Y. B. (2008). Comparison of algorithms for an electronic nose in identifying liquors. J. Bionic Eng. 5, 253–257. doi: 10.1016/S1672-6529(08)60032-3

CrossRef Full Text | Google Scholar

Tai, X., Sun, H., and Guo, Q. (2016). Electricity transactions and congestion management based on blockchain in energy internet. Power Syst. Technol. 40, 3630–3638. doi: 10.13335/j.1000-3673.pst.2016.12.002

CrossRef Full Text | Google Scholar

Tan, S., Wang, X., and Jiang, C. (2019). Privacy-preserving energy scheduling for ESCOs based on energy blockchain network. Energies 12:1530. doi: 10.3390/en12081530

CrossRef Full Text | Google Scholar

Tanwar, S., Bhatia, Q., Patel, P., Kumari, A., Singh, P. K., and Hong, W. C. (2019). Machine learning adoption in blockchain-based smart applications: the challenges, and a way forward. IEEE Access 8, 474–488. doi: 10.1109/ACCESS.2019.2961372

CrossRef Full Text | Google Scholar

Zhang, J., Gao, W. Z., Zhang, Y. C., Zheng, X. H., Yang, L. Q., Hao, J., et al. (2017). Blockchain based intelligent distributed electrical energy systems: needs, concepts, approaches and vision. Acta Automat. Sin. 43, 1544–1554. doi: 10.16383/j.aas.2017.c160744

CrossRef Full Text | Google Scholar

Zhao, S., Li, Y., Wang, B., and Su, H. (2018a). “Research on the blockchain-based integrated demand response resources transaction scheme,” in 2018 International Power Electronics Conference (IPEC-Niigata 2018-ECCE Asia) (IEEE), 795–802. doi: 10.23919/IPEC.2018.8507866

CrossRef Full Text | Google Scholar

Zhao, S., Wang, B., Li, Y., and Li, Y. (2018b). Integrated energy transaction mechanisms based on blockchain technology. Energies 11:2412. doi: 10.3390/en11092412

CrossRef Full Text | Google Scholar

Zhou, Z., Tan, L., and Xu, G. (2018). “Blockchain and edge computing based vehicle-to-grid energy trading in energy internet,” in 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2) (IEEE), 1–5. doi: 10.1109/EI2.2018.8582652

CrossRef Full Text | Google Scholar

Keywords: energy trading, blockchain, review, transaction mechanism, platform construction

Citation: Li H, Xiao F, Yin L and Wu F (2021) Application of Blockchain Technology in Energy Trading: A Review. Front. Energy Res. 9:671133. doi: 10.3389/fenrg.2021.671133

Received: 23 February 2021; Accepted: 15 March 2021;
Published: 21 April 2021.

Edited by:

Liang Chen, Nanjing University of Information Science and Technology, China

Reviewed by:

Wei He, Nanjing University of Information Science and Technology, China
Jia Cui, Shenyang University of Technology, China

Copyright © 2021 Li, Xiao, Yin and Wu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Lixin Yin, ylx_SGXFTC@163.com

Download