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When Energy Trading meets Blockchain in Electrical Power System: The State of the Art
Naiyu Wang, Xiao Zhou, Xin Lu, Zhitao Guan, Longfei Wu, Xiaojiang Du, Mohsen Guizani
TL;DR
Renewable growth is moving energy trading toward distributed participation, but blockchain-based schemes still face efficiency, cost, security, and privacy challenges. This survey identifies those challenges, classifies existing schemes by energy transaction, consensus mechanism, and system optimization, and reviews their unresolved problems and future directions.
Problem
Blockchain-based energy trading faces low efficiency, high transaction costs, and security and privacy challenges as energy markets become more distributed.
Method
The paper surveys blockchain-based energy trading, analyzes its challenges, and classifies existing schemes by energy transactions, consensus mechanisms, and system optimization.
Results
Existing schemes address transaction, consensus, optimization, security, privacy, matching, pricing, cost, and benefit objectives, but unresolved problems remain.
Takeaways & Limitations
Blockchain-based energy trading research is progressing toward more flexible and better-performing markets, while requiring further work on unresolved challenges.
Takeaways & Limitations
The field still lacks incentive and regulatory mechanisms, physical-layer implementation, and solutions to environmental challenges.
Abstract
from arXiv · showhide
With the rapid growth of renewable energy resources, the energy trading began to shift from centralized to distributed manner. Blockchain, as a distributed public ledger technology, has been widely adopted to design new energy trading schemes. However, there are many challenging issues for blockchain-based energy trading, i.e., low efficiency, high transaction cost, security & privacy issues. To tackle with the above challenges, many solutions have been proposed. In this survey, the blockchain-based energy trading in electrical power system is thoroughly investigated. Firstly, the challenges in blockchain-based energy trading are identified. Then, the existing energy trading schemes are studied and classified into three categories based on their main focus: energy transaction, consensus mechanism, and system optimization. And each category is presented in detail. Although existing schemes can meet the specific energy trading requirements, there are still many unsolved problems. Finally, the discussion and future directions are given.
1. Introduction
Energy trading is shifting from centralized utility control toward distributed participation enabled by smart grids, microgrids, and renewable generation. The survey reviews blockchain’s role in this transition, its benefits, and the remaining challenges.
- Smart-grid users can act as both electricity consumers and suppliers, trading excess renewable generation with utilities or other users.
- Traditional energy markets face over-centralization, low efficiency, high costs, and security and privacy problems.
- Distributed energy-market systems support consumer-centered P2P participation, demand-response signals, lower costs, faster operation, and greater scalability.
- Blockchain-based energy trading can support independent node operation, transparent transactions, security through cryptography, and reduced costs.
- The survey analyzes pre- and post-blockchain energy-trading problems, classifies existing research, and highlights unresolved challenges.
2. Preliminaries
The preliminaries describe blockchain’s decentralized transaction process and introduce supporting privacy and computing technologies used in blockchain-based energy trading.
- Blockchain links transactions into a chain using secret keys and timestamps while using proof-of-work to prevent double spending.
- In proof-of-work, nodes collect transactions into blocks, solve a difficult proof, broadcast a solution, and verify the resulting block.
- Zero-knowledge proofs demonstrate possession of knowledge without revealing the solution or exact content being proved.
- Ring signatures generate signatures using a group of public keys and one signer’s private key to provide anonymity.
- Cloud computing remotely provides on-demand computing and storage resources through networks, whereas fog computing uses decentralized edge devices closer to users.
- Onion routing uses layered encryption across successive routers, while garlic routing groups messages through multiple tunnels.
3. Challenges of Blockchain‐based Energy Trading
Blockchain-based energy trading must address weaknesses inherited from traditional markets and limitations introduced by blockchain itself. The survey identifies efficiency, privacy, communication, pricing, physical, and resilience challenges.
- Traditional trading relies on centralized third-party control, increasing operating costs, reducing transparency, and exposing authentication, payment, and data integrity risks.
- Centralized generation, long-distance energy delivery, and one-way power flow reduce flexibility and increase vulnerability to disruptions.
- Blockchain-based trading faces low efficiency and high transaction costs because transaction speed may not meet system requirements.
- Privacy and security remain challenging because transaction data can support behavior analysis and private keys may leak.
- Large volumes of sensor data create a real-time communication challenge, while appropriate pricing must help buyers and sellers reach agreement.
- Blockchain’s tightly connected network can produce cascading physical faults, and hardware limitations constrain system design.
4. Overview of Blockchain‐based Energy Trading
Blockchain-based energy trading commonly uses P2P networks with blockchain as the system framework, while the survey organizes improvements across transaction stages, consensus, and system optimization.
- P2P energy-trading networks may be structured or unstructured, trading routing efficiency and maintenance requirements against search reliability.
- The survey reviews the trading process first, then examines consensus-mechanism improvements and macro-level system optimization.
5.1. Pre‐trade communication
Pre-trade communication schemes protect users’ identities and private information before energy trading by obscuring addresses, data, routes, and locations.
- 5.1. Pre‐trade communication: Users publish supply and demand before identifying trading partners, creating a need to protect security and privacy.
- 5.1.1. Address fuzzification: Anonymous addresses generate a new pseudonym for each transaction, while multiple pseudonyms can further break links between users and consumption behavior.Bloom filters validate pseudonyms, and zero knowledge verifies their existence.
- 5.1.1. Address fuzzification: Zero-knowledge techniques can hide coins or generate unlinkable wallet addresses by severing connections between users and transactions.
- 5.1.2. Data and information protection: Privacy can also be protected by masking household loads, using virtual power plants, or applying cryptographic signatures against leakage attacks.These approaches respectively blur consumption, avoid sharing private information during negotiation, and address continual-leakage attacks.
- 5.1.3. Communication routing: Garlic routing and public-key-based backbone routing conceal transaction information by controlling route allocation and associating normal nodes with multiple public keys.
5.2. Matching
Matching schemes pair buyers and sellers under security, physical, temporal, and pricing constraints, using auctions, games, optimization, and off-chain processing.
- 5.2. Matching: Homomorphic encryption hides supplier and demander locations until stable matching succeeds, while distance-based preferences support the matching process.
- 5.2.2. Auction mechanism: Distributed auction designs transfer computation to users or controllers to preserve honesty, reduce hub burdens, maximize utility, and improve social welfare.
- 5.2.2. Auction mechanism: Auction mechanisms match buyers and sellers through iterative bidding, price matrices, adaptive quotations, or one-time transactions with guiding prices.
- 5.2.2. Auction mechanism: Game-theoretic and contract-based methods adjust matching, pricing, and energy allocation according to equilibrium strategies or consumers’ distinct preferences.
- 5.2.3. Pricing mechanism: P2P pricing mechanisms use compensation, adaptive trader margins, or mid-market rates to improve participant benefits and coordinate grid purchases and sales.
- 5.2.4. Settlement: Off-chain payments and solvers improve settlement or matching efficiency by reducing on-chain activity while retaining verification through smart contracts.Off-chain payment addresses privacy exposure, low efficiency, and high transaction costs in the cited charging-station model.
- 5.2.4. Settlement: Separate contract and ledger chains, multisignatures, and multisignature wallets strengthen reliability, transaction validity, and conditional settlement.
6. Category II: Consensus Mechanism
Consensus mechanisms determine how blockchain energy-trading participants validate transactions, balancing security, computational requirements, authorization, and energy-specific contributions.
- 6. Category II: Consensus Mechanism: Blockchain energy-trading systems use PoW, PoS, PBFT, Proof-of-Authority, PoB, and PoET, either in traditional or modified forms.
- 6.1. Proof-of-Work: PoW validates blocks by finding a nonce that produces a qualifying hash, making answers easy to verify but requiring substantial computing resources.
- 6.1. Proof-of-Work: Cloud, edge, and fog computing support PoW-based systems because mobile devices face high computational overhead.
- 6.2. Energy-based consensus: Energy-specific consensus can use data contribution frequency, energy contribution rates, or measured PHEV energy output to assign energy currencies and incentives.
- 6.3. Consortium and optimized consensus: Consensus-based optimization and access control encryption support trusted demand-response strategies and resistance to conspiracy attacks.
- 6.4. Proof-of-Stake: PoS reduces CPU requirements by selecting block creators from validators according to their stake in the grid.
- 6.5. Delegated Byzantine fault tolerance: Reputation-based delegated Byzantine fault tolerance coordinates ordinary and consensus nodes through leader proposals and state-set comparison.
7. Category III: System Optimization
System-optimization research improves blockchain-based energy trading through structural redesigns, storage integration, cost and welfare objectives, privacy protection, and game-theoretic coordination.
- 7.1. Structural optimization: Structural optimization models improve energy-trading performance through interactive control, parallel processing, cloud or fog computing, and blockchain-supported service architectures.
- 7.2. Storage optimization: Storage-oriented models address intermittent generation and load variation through dynamic pricing, distributed storage trading, and hybrid public-private blockchain architectures.
- 7.3. Cost optimization: Cost optimization targets individual or total energy costs using mixed integer linear programming, atomic meta-transactions, and distributed convex optimization.
- 7.4. Social welfare optimization: Auction mechanisms such as Kelly and double auctions allocate energy or shares to improve social welfare and reduce efficiency loss from price expectations.
- 7.4. Social welfare optimization: Smart contracts, cloud-based auctions, edge computing, and deep learning optimize welfare while accounting for bids, payment rules, truthfulness, and privacy.
- 7.5. Privacy optimization: Noise-based privacy models hide transaction-distribution trends and address risks from link attacks or malicious data mining on stored blockchain data.
- 7.6. Multi-objective and game-theoretic optimization: Other optimization objectives include user satisfaction, producer profit, consumer cost, microgrid benefits, operator utility, and cloud-miner benefits.
- 7.6. Multi-objective and game-theoretic optimization: Distributed controllers and centralized auctions can ensure maximum market-user welfare without requiring users’ personal information.
8. Discussion and Future Directions
Blockchain-based energy trading has improved flexibility and performance, but unresolved incentive, consensus, privacy, regulatory, physical-layer, and real-world validation challenges remain. Broader energy-market applications, including green blockchain, warrant further exploration.
- Current status: Blockchain-based energy trading has brought greater flexibility and better performance, serving either as the system framework or as an implementation tool.As a framework, blockchain stores transaction data and supports security.
- Unresolved challenges: Incentive systems remain underdeveloped because many architectures overlook node participation, transaction-fee design, and end-user benefits.The survey notes increasing attention to ordinary consumers in optimization.
- Unresolved challenges: Proof-of-work consensus can require long agreement times and high computational overhead, while alternatives such as proof-of-stake and PBFT are not widely used.The survey also links proof-of-work with a large carbon footprint in one discussed system.
- Unresolved challenges: Limited route-hiding technologies create privacy and security concerns during energy-data transmission.The issue concerns protecting users while transaction information is transmitted.
- Deployment barriers: Real-world deployment still requires substantial experimental and simulation testing, alongside regulatory mechanisms and physical-layer implementation.The survey highlights missing laws and regulations and limited consideration of hardware constraints.
- Future directions: Future work should address unresolved challenges and explore blockchain applications across other energy-market functions, such as carbon-emissions registration and renewable-energy promotion.Green blockchain is cited as an example of a broader environmental application.
9. Conclusions
The paper surveys improvements across the stages of blockchain-based energy trading, from distributed control and security to matching, pricing, and system optimization. It concludes by identifying unresolved problems and outlining future directions.
- Conclusion: The survey covers improvements across transaction stages, including decentralized architecture, security and privacy, transaction matching, auction pricing, cost minimization, and benefit maximization.It organizes the discussion around the full energy-trading process.
- Conclusion: The paper highlights unsolved problems and provides insights for future directions.The conclusion frames these issues as the remaining agenda for blockchain-based energy trading.