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Citation: Yang, Qing, and Hao Wang. “Privacy-Preserving Transactive Energy Management for IoT-aided Smart Homes via Blockchain.” IEEE Internet of Things Journal (2021).
Figure 1: Schematic diagram of vertical and horizontal transactions in the transactive energy management system proposed.
- Smart grid systems collect and distribute data from smart home meters.
- These systems collectively can be thought of as an “energy Internet of Things (IoT)”.
- Smart grid systems lend themselves to blockchain-based transactive energy management (TEM) systems.
- TEMs improve energy efficiency and reduce grid load by allowing users to exchange energy.
- Energy can be exchanged between homeowners and the grid (vertical transactions) and between homeowners peer-to-peer (horizontal transactions). See Figure 1 above.
- Currently, transactive energy systems (TEMs) suffer from a number of problems.
- Efficiency: TEMs have not reached peak efficiency levels.
- Privacy and Security: TEMs suffer from “data leakage” and a lack of effective security.
- Efficient Transactive Energy System: A vertical (smart home to grid) and horizontal (smart home to smart home) energy transaction system can improve efficiency.
- Privacy and security: Hybrid smart contracts and Chainlink oracles within a blockchain-based IoT integration transactive energy platform offer solutions to these problems by providing users with the ability to optimally manage parallel energy usage securely and privately.
Table 1: Comparison of this paper with existing research on transactive energy management systems. Please refer to the original paper for references.
Existing energy management systems do not maximize energy efficiency because they do not have the infrastructure to provide for both horizontal (smart home to smart home) and vertical (smart home to grid) energy transactions in a secure manner.
Can a blockchain-based system powered by smart contracts and oracles solve these problems in the context of an effective TEM system?
The authors take a three-part approach toward building and evaluating the TEM proposed in the paper.
- Theoretical Transactive Energy Management Model
- Transactions: Explication of vertical and horizontal transactions along with estimated transfer quantities are derived.
- IoT Blockchain Integration With Smart Meters: description of how smart meters will act as nodes within a blockchain-based system. Consensus protocols, block structure, and the roles of oracles and smart contracts are discussed here.
- Algorithm Design
- An optimization algorithm implementing elements discussed in the theoretical model is derived.
- Performance Evaluation
- Real-world scenario: The system developed is tested on a real network of IoT devices.
- Numerical simulations: Numerical simulations with energy usage data are conducted.
- Vertical transactions:
- Smart home → grid energy transfers are conducted using the feed-in tariff (FIT) reward model. In this model, the smart home, n, receives a reward, R, equivalent to the amount of renewable energy, e, that they contribute to the grid at time t.
- Horizontal transactions:
- Smart home → smart home transfers are conducted through the sale and purchase of energy between homes at a given price p. The reward for a smart home trader, n, is simply the amount of energy sold to other smart homes, e, multiplied by the price, p.
The IoT blockchain is designed to run on smart meters. It requires a network connection of some sort (Wi-Fi, Ethernet, LoRa).
Blockchain will serve three purposes: (1) as a transparent, decentralized platform to facilitate transactions; (2) as a low-cost, secure, and efficient data network using oracles and smart contracts; (3) as a convenient payment tool for receiving and transmitting rewards through a native token.
The most significant benefit of this design is that no new hardware is needed. Trusted, secure Chainlink decentralized oracle networks can be easily integrated into a smart meter IoT blockchain system.
Figure 2: Proposed practical Byzantine fault tolerance (PBFT) consensus protocol.
The authors choose a practical Byzantine fault tolerance (PBFT) protocol illustrated in Figure 2 because of its low computational complexity, feasibility for IoT devices, and immediate transaction finality.
Figure 3: Block structure of the proposed IoT blockchain.
Authors choose a block structure similar to Ethereum, as shown in Figure 3.
The authors design a distributed optimization algorithm using smart contracts to achieve maximum efficiency and privacy. This is accomplished by decomposition of the algorithm into two tasks: (1) a user local task (ULT) and; (2) a smart contract task (SCT). The ULT is generated by smart home users to create an optimized power usage schedule. The SCT aggregates user decisions and executes a system-wide optimal trading decision.
Smart contracts in this study were written in Solidity.
Figure 4: IoT blockchain test network with two types of Raspberry Pi nodes. Node types are meant to represent variation in smart meter hardware types.
The authors built a test network of 11 Raspberry Pi devices to assess the performance of the IoT blockchain discussed in the paper using two types of nodes to represent variation in smart meter hardware as shown in Figure 4.
Performance was measured in terms of transaction delay, block confirmation time, and transactions per second (TPS). On all counts, the authors found that their system performed well with a 5-millisecond delay, a 100-millisecond block confirmation time, and a peak of 700 transactions per second in the network.
Energy data is used to conduct a series of simulations within the framework of the transactive energy management system proposed here. Figures 5 and 6 provide examples of simulated vertical transactions and peer-to-peer energy transactions of “typical” simulated users. Both demonstrate that each of the mechanisms operate to effectively allocate energy throughout the system under normal grid operation conditions.
Figure 5: Optimal simulated smart home to grid (vertical) transactive energy of users for (a) feed-in solar panel energy and; (b) demand response service to the grid.
Figure 6: Optimal peer-to-peer (horizontal) energy trading of two typical users (a) user #6 (b) user #8.
The authors here propose a fascinating, detailed energy management system and test that system using real-world energy data and a fabricated mini-network. While this is a great paper that goes a long way toward developing a detailed outline for a smart energy system, there are some questions that it leaves unanswered which need to be addressed, perhaps in a follow-up piece.
These include answers to questions relating to:
Assuming that we could build the most efficient, secure, and private transactive energy management system, such a system would require investment in additional infrastructure and a great deal of uncertainty about whether these systems would effectively deliver a constant flow of energy and have a low probability of failure.
Authors who propose these systems need to assuage the concerns of risk-averse entities who are interested in adopting these transactive energy management systems but are concerned about the probability of failure and whether these systems would actually deliver a more sustainable energy environment.
Current energy regulatory frameworks are centered around centralized energy grid control. What aspects of current regulatory frameworks must be reconsidered to accommodate transactive energy systems (TEMs)?
Having more information about problems and inefficiencies in these novel energy systems can be beneficial to other energy management systems. How can we balance privacy and security systems with more transparency that can potentially be beneficial to all?