Blockchain Technology Applied in IoV Demand Response Management: A Systematic Literature Review
Abstract
:1. Introduction
- Collects and filters the available literature, in an attempt to present current perspectives and research efforts on blockchain-enabled DRM in IoV.
- Critically analyzes and reports the review’s outcomes, in an attempt to discuss the various IoV DRM solutions and scenarios and provide a taxonomy of demand response programs.
- Focuses on the perspectives and research efforts around the demand response management in the IoV, taking into consideration the application of blockchain technology.
- Provides a comprehensive list of observations and research challenges of blockchain technology in the IoV DRM.
2. Systematic Literature Review Methodology
- Plan the review: Determine the rationale of the review, define the research questions and create the review process.
- Conduct the review: Carry out the established protocol, select studies and assess their quality.
- Report the review: Presents the review findings.
2.1. Plan the Review
SLR Question: How can blockchain technology assist the area of demand response management in IoV-assisted smart grids?
2.2. Conduct the Review
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- Authors, publication year, paper type, publishing location and digital object identifier were all required fields.
- ●
- Evaluation of the study in terms of research knowledge, including the following:
- ○
- The study’s issues;
- ○
- The study’s results and key findings;
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- The study’s limitations and/or research approaches.
2.3. Report the Review
3. Current Perspectives and Research Efforts on Blockchain-Enabled IoV
3.1. P2P Trading and Management in Energy Blockchain
3.2. Blockchain-Based Demand Response Programs and Optimization Models
- Time-based DR: In the time-based DR, consumers are provided time-varying pricing depending on the cost across various time periods.
- Incentive-based DR: Customers in incentive-based DR schemes are offered fixed or time-varying payments to encourage them to reduce their electricity usage during times of system stress [66,67,68], but they are also subject to specific constraints or are penalized if they do not participate in the program.
3.3. Electric Vehicles Charging Scheduling Using Blockchain
4. Discussion
- Research Challenges and Suggestions 1:
- Research Challenge 1: EV information is exposed, resulting in privacy and security issues.
- Suggestion 1: Blockchain infrastructure and identity management for secure information exchange in IoV.
- Description: The existing charging coordination mechanisms suffer from their relation to a single entity (e.g., the charging coordinator), which can reveal private information about the owners of the EVs (e.g., patterns and drivers’ profiles). Thus, the integration of blockchain in the IoV should guarantee the privacy of all participants and the security of the exchanged information.
- Research Challenges and Suggestions 2:
- Research Challenge 2: Demand and response in IoV are affected by energy generation and consumption.
- Suggestion 2: V2V/V2G Energy Trading considering EVs’ Charging Scheduling addressing the Demand Response Problem.
- Description: The widespread use of unpredictable dispersed RES and uncoordinated EVs creates problems for smart energy management. Current studies are investigating the optimization of the charging scheduling of EVs, although they do not consider the regional energy balance, leading to demand–response gaps and energy imbalances. Thus, emphasis should be given to the energy demand and response of the EVs in specific regions of a smart grid (e.g., considering social events and/or accidents).
- Research Challenges and Suggestions 3:
- Research Challenge 3: EV charging profiling from an EV user perspective is not investigated.
- Suggestion 3: EV profiling for optimal charging scheduling and DR balance.
- Description: EV charging profiling from an EV user perspective is not sufficiently investigated. This means that each EV user should be aware of and declare its charging preferences and also to update this information in a continuous manner. In order to successfully control the charging/discharging schedule in comparison to IoV metrics and stability, a certain amount of smartness should be considered.
- Research Challenges and Suggestions 4:
- Research Challenge 4: Due to a lack of incentives, EVs with excess energy are not encouraged to act as energy marketers.
- Suggestion 4: Incentive provisioning through rewards and penalties.
- Description: There is too little work conducted in the area of incentivization mechanisms. The majority of the studies do not consider any incentive mechanism to encourage EV drivers to participate in a blockchain-enabled DRM scheme. Therefore, it is necessary to provide an effective incentivization scheme that will give the appropriate rewards and/or penalties to the IoV participants and exploit the blockchain related activities.
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
DER | Distributed Energy Recourse |
DR | Demand Response |
DRM | Demand Response Management |
DRP | Demand Response Problem |
EV | Electric Vehicle |
IoT | Internet of Things |
IoV | Internet of Vehicles |
ITS | Intelligent Transportation Systems |
P2P | Peer to Peer |
RES | Renewable Energy Sources |
RSU | Road Side Unit |
SLR | Systematic Literature Review |
V2G | Vehicle-to-Grid |
V2V | Vehicle-to-Vehicle |
V2X | Vehicle-to-Everything |
Appendix A
Title | Problem Description | Study Outcomes/Objectives | Limitations |
---|---|---|---|
[38] | Different prices based on demand and response, privacy issues and detection of customers’ and EVs’ position. | A reliable, automated and privacy-preserving selection of charging stations based on pricing and distance to the electric vehicle. | Possibility of denial-of-service attack. Charging stations are not fully utilized or EVs are not guaranteed a time slot. |
[39] | Uncoordinated usage and unregulated energy demand from EVs may increase the demand–supply gap between the service providers and the consumers. | A Peer-to-Peer (P2P) energy trading scheme between EVs and the SPs to manage the demand response in V2G environment, providing incentives to EVs. Consortium blockchain is used to ensure secure energy transactions between EVs and the SPs without a trusted third-party intervention. | Energy scheduling is not considered; Optimal EV charging is not considered |
[40] | Sustainable microgrids that simultaneously address economic benefits, environmental and social issues have not been broadly explored by researchers. | Leveraging blockchain technology to provide real-time-based demand response programs. | Blockchain-based smart contracts should be considered in sustainable microgrids to ensure a fair deal for various stakeholders. |
[41] | Random dynamic nature of electric vehicle charging and routing cause issues in the electric vehicles’ load and could challenge the power distribution operators and utilities. | A real-time system that incorporates the concepts of prioritization and cryptocurrency to incentivize electric vehicle users to collectively charge with a renewable energy-friendly schedule. The study incorporated a blockchain-based cryptocurrency component in order to incentivize users with monetary and non-monetary means in a flat-rate system. | The study was designed based on a photovoltaic generation system and is not evaluated in IoV scenarios. |
[42] | The rising demand for electric vehicles will necessitate an increase in charging infrastructures, both to ensure charging system absorption and to disperse energy demand. | A blockchain-based approach for smart charging of electric vehicles, in which a software agent determines whether to load a machine, in what order or whether it is preferable to sell energy to the retail market. The agent adjusts to the individual prosumers of electric vehicles, learning their preferences and mobility habits, so that owners of electric vehicles choose to participate in the system. | Real-time demand is not addressed and blockchain incentives are not clear enough. |
[43] | Demand response procedures are transmitted in the smart city with the use of communication infrastructures, which can lead to a variety of attacks in which a malicious user can exploit security flaws in the network. | A safe demand response management system based on blockchain that secures energy trade choices for controlling the total load of domestic, commercial and industrial sectors. | The latency of the proposed system should be decreased and throughput should be increased. Incentives are not present. |
[44] | While electricity trading plays an important role in P2P trading, the existing studies have not analyzed the interaction among prosumers regarding pricing. | A game-theory-based pricing model in PBFT-based consortium blockchain is proposed, as well as a rule-based iterative pricing algorithm to obtain the equilibrium prices. | Energy profiles are not taken into consideration neither scheduling algorithms are in place. |
[45] | A large amount of data are generated every day in demand response systems from different sources, such as energy production (e.g., wind turbines), transmission and distribution (e.g., microgrids) and load management (e.g., smart meters and electric vehicles). | Analysis of deep learning applications in smart grids and demand response, including electric load forecasting, state estimation, energy theft detection and energy sharing and trading. | Aspects such as dynamic pricing for demand response. load forecasting in smart grids and EV scheduling are not discussed. |
[46] | The untrustworthy centralized nature of energy markets and EV charging infrastructures expose EV users’ personal information to a number of privacy and security risks. | A blockchain-based charging station selection mechanism for electric vehicles, that ensures EV users’ confidentiality and privacy, availability of reserved time slots at the charging stations, Quality of Service (QoS) and improved EV user comfort. | The use of dynamic pricing is restricted. Although it is a vital part in unleashing EVs’ flexibility potential, which is necessary for the future grid integration of EVs and renewable energy. |
[47] | Demand response necessitates the use of a central agent, which raises security and trust concerns. Furthermore, during incentive pricing, disparities in user response cost features are not considered, affecting the equitable participation of users in DR and increasing expenses. | A blockchain-enabled demand response scheme with an individualized incentive pricing mode is proposed. | More market-realistic scenarios, such as more than one power retail firm engaging in demand response and a higher number of consumers, must be considered. Investigate game and solution models that are appropriate for market-realistic scenarios. |
[48] | Increasing available supply to match the projected peak usage value requires the energy operator to over-provision the generation capacity, which can be expensive. | A blockchain-based and data-driven approach for incentive-based peak mitigation. | The study was not implemented in the context of IoV. Additionally, real-time re-scheduling based on unforeseen events was not considered. |
[12] | Due to their selfishness and mistrust, smart vehicles with excessive computational power may be hesitant to join in the trading process. | To ensure transaction security and anonymity, a consortium blockchain approach is used. The authors used a consortium blockchain approach to show how to trade safe computing resources and entice individual smart automobiles to join the system. | Energy scheduling is not sufficiently analyzed, neither sufficient incentives are provided to participate in the blockchain demand response network. |
[49] | Heterogeneous entities on the demand side pose a risk to the power system’s reliability and security. | For demand side management, a blockchain-enhanced price incentive demand response is presented. Data verification is recommended to check the validity of the data completed by each user, based on blockchain capabilities, to ensure the credibility of the best energy schedule. All users retain data that are visible, traceable and tamper-proof. | Energy scheduling is not sufficiently analyzed. |
[50] | Peak demand times provide a problem to the grid operator since they may need over-provisioning the grid capacity in order to preserve system stability, raising the marginal cost of energy. | Present a unified blockchain-based energy asset transaction system for prosumers, electric cars, power companies and storage providers, incorporating fungible and non-fungible tokens. | Focusing on token incentives, but not on the demand scheduling. |
[51] | Because centralized approaches in smart grid management are no longer effective, the necessity for innovative decentralized techniques and designs are generally acknowledged. | A distributed ledger storage and management solution based on blockchain for energy data gathering from IoT and smart metering devices. Self-enforcing smart contracts are also proposed for programmatically specifying the expected energy flexibility at the prosumer level, the related incentives or penalties and the rules for balancing energy demand with energy output at the grid level. | It was pointed that currently the Distributed System Operator is still on control in a centralized manner. |
[52] | There are several challenges that consumers and smart grids face when it comes to user’s data, including traceability, authorization, data integrity, data security and single point of failure. | The decentralized nature of the local market is highlighted by the usage of a distributed blockchain technology. Through the Periodic Double Auction method, the study provides a decentralized market platform for trading locally without the need for a central middleman. | Decentralized storage is not present. |
[53] | Demand response program acceptance is still lacking owing to consumers’ lack of understanding, fear of losing control and privacy over their energy data, and other factors. | A decentralized solution for demand response programs on top of a public blockchain that uses zero-knowledge proofs to protect the privacy of the prosumer’s energy data and uses smart contracts to validate the prosumer’s behavior inside the program on the blockchain. | Smart grid services have varying response time requirements, which affects the accuracy required for energy data monitoring and the costs of integrating an energy blockchain. |
[54] | Internet of electric vehicles lacks incentive mechanism and suffers from privacy leakage and security threats. | A blockchain-enabled safe energy trading system for privacy and security in the Internet of vehicles. | Given that the data in a block are encrypted using asymmetric encryption techniques, decrypting them without knowing the secret key is extremely expensive. The computation resources required to determine a block are prohibitive, preventing the widespread adoption of blockchain-based energy trade. |
[55] | The extensive deployment of EVs can bring challenges to the grid if not properly integrated. | Propose blockchain-based smart contracts that allow decentralized energy trading among EVs, considering the users’ preferences for the charging scheduling models. | Real-time rescheduling of the charging procedure is not considered. |
[56] | Increased demand–response gaps and poor service quality of contemporary ICT-based smart grid in industry 4.0 are caused by the exponential rise in energy demand, necessitating the urgent need for an effective Demand Response Management system to address the aforementioned issues. In terms of peak load reduction, customer satisfaction and data security concerns, the available options are insufficient. | A Demand Response Management algorithm is suggested, combined with a customer incentive system, to minimize peak energy usage. The authors propose an Ethereum-based smart contract to address security concerns and the InterPlanetary File System (IPFS) to address data storage costs. | Dynamic pricing strategies, as well as real-time rescheduling concerns, should be explored. |
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Keyword | Query |
---|---|
blockchain | blockchain AND “demand response” AND (IoV OR “Internet of Vehicles” OR “Smart Grid” OR “Smart City”) AND (applications OR challenges) |
IoV | |
Internet of Vehicles | |
smart grid | |
smart city | |
demand response | |
applications | |
challenges |
Inclusion Criteria | Exclusion Criteria |
---|---|
Peer-reviewed studies | Grey literature |
Academic theoretical and empirical research | White papers and material from non-academic sources |
Full-text available | Full-text not available |
Written in the English language | Not written in the English language |
Published in 2017 onwards | Published before 2017 |
Relevant to blockchain and the IoV concept | Diverged from the field of blockchain and the IoV concept |
Concept addressed by means of a valid methodology |
Reference (Selected Studies) | Blockchain-Based Privacy | Demand Response Management | V2V/V2G Energy Trading | Charging Scheduling | Incentive Mechanism | EV Profiles |
---|---|---|---|---|---|---|
[38] | ● | ● | ● | |||
[39] | ● | ● | ● | |||
[40] | ● | |||||
[41] | ● | ● | ● | |||
[42] | ● | ● | ||||
[43] | ● | ● | ||||
[44] | ● | |||||
[45] | ● | ● | ● | |||
[46] | ● | ● | ||||
[47] | ● | ● | ||||
[48] | ● | ● | ||||
[12] | ● | ● | ● | |||
[49] | ● | ● | ● | ● | ||
[50] | ● | |||||
[51] | ● | ● | ● | |||
[52] | ● | ● | ||||
[53] | ● | |||||
[54] | ● | ● | ||||
[55] | ● | ● | ● | |||
[56] | ● | ● | ● | |||
This SLR | ● | ● | ● | ● | ● | ● |
Category | Similarities | Differences |
---|---|---|
Incentivization | Blockchain incentives are needed to encourage participation | Focus on Non-Fungible Tokens (NFTs) as a mean for incentivization scheme |
Privacy and Security | Blockchain technology is mostly used for security and privacy | Data analytics scheme for security-aware DRM using blockchain |
Demand Response Management | Real-time demand management is not investigated | Incorporate deep learning for intelligent demand response |
EV drivers’ profile | Drivers’ preferences are not considered | n/a |
Generic | Consortium blockchain is common in the DRM applications | The proposition is not directly applied in EVs |
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Kapassa, E.; Themistocleous, M. Blockchain Technology Applied in IoV Demand Response Management: A Systematic Literature Review. Future Internet 2022, 14, 136. https://doi.org/10.3390/fi14050136
Kapassa E, Themistocleous M. Blockchain Technology Applied in IoV Demand Response Management: A Systematic Literature Review. Future Internet. 2022; 14(5):136. https://doi.org/10.3390/fi14050136
Chicago/Turabian StyleKapassa, Evgenia, and Marinos Themistocleous. 2022. "Blockchain Technology Applied in IoV Demand Response Management: A Systematic Literature Review" Future Internet 14, no. 5: 136. https://doi.org/10.3390/fi14050136