The condition of power imbalance in flexible distribution networks (FDNs) is deteriorated due to the high penetration of distributed generators. Through peer-to-peer (P2P) electricity trading, multiple regions interconnected by soft open points (SOPs) can flexibly exchange power to alleviate power imbalance. As the physical foundation of P2P transactions, SOP regulation guarantees accurate instruction execution. Besides, smart contracts based on distributed ledger technology (DLT) facilitate highly credible P2P transactions. Oriented for the economic operation of interconnected FDNs, this article proposes a DLT-based P2P electricity trading method based on intelligent SOP regulation. First, a smart contract is designed for P2P transactions of FDNs, in which trading solutions are automatically settled with a modified highest combined offer principle. Then, a trading platform is built for the P2P electricity trading of interconnected FDNs. Finally, the effectiveness of the proposed method is verified on a practical FDN with four-terminal SOPs in Tianjin.
Mirza Jabbar Aziz Baig, M. Tariq Iqbal, Mohsin Jamil, Jahangir Khan · 5 authors
With advancements in renewable energy technologies, consumers are becoming prosumers, and renewable energy resources are being used in distributed networks. In an isolated distributed system, peer-to-peer (P2P) energy trading is one of the most promising energy management solutions. In this paper, we propose a P2P energy trading method for micro-grids using open resources and technology. The proposed setup comprises an Internet of Things (IoT) server to transfer energy amongst the peers without human intervention, and an Ethereum based private blockchain is suggested for money transfer in the form of cryptocurrency. The IoT server enables the peers to control and monitor self-produced energy. Arduino UNO, ACS 712 hall-effect current sensor, and a relay are the main components used in the hardware setup. The current sensor data is sent in real- time to Arduino for onward communication to the IoT server. A user-friendly interface has been developed on the server to perform various energy trading tasks. Peers have the choice to access the server remotely to perform energy trading tasks. The energy trading events can be shared amongst peers through e-mail notifications. For financial transactions, we utilized Ganache graphical user interface (GUI) a private Ethereum blockchain eliminating the need for financial institutions. The proposed peer-to-peer energy trading model has been successfully tested for energy trading between two peers. This paper provides details of the proposed hardware and software setup and explains how low-cost P2P energy trading can be achieved.
This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighbouring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.
Recent years have seen a surge of interest in distributed residential batteries for households with renewable generation. Yet, assuring battery assets are profitable for their owners requires a complex optimisation of the battery asset and additional revenue sources, such as novel ways to access wholesale energy markets. In this paper, we propose a framework in which wholesale market bids are placed on forward energy markets by an aggregator of distributed residential batteries that are controlled in real time by a novel Home Energy Management System (HEMS) control algorithm to meet the market commitments, while maximising local self-consumption. The proposed framework consists of three stages. In the first stage, an optimal day-ahead or intra-day scheduling of the aggregated storage assets is computed centrally. For the second stage, a bidding strategy is developed for wholesale energy markets. Finally, in the third stage, a novel HEMS real-time control algorithm based on a smart contract allows coordination of residential batteries to meet the market commitments and maximise self-consumption of local production. Using a case study provided by a large U.K.-based energy demonstrator, we apply the framework to an aggregator with 70 residential batteries. Experimental analysis is done using real per minute data for demand and production. Results indicate that the proposed approach increases the aggregator's revenues by 35% compared to a case without residential flexibility, and increases the self-consumption rate of the households by a factor of two. The robustness of the results to uncertainty, forecast errors and to communication latency is also demonstrated.
Moayad Aloqaily, Ouns Bouachir, Öznur Özkasap, Faizan Safdar Ali
Abstract Growing intelligent cities is witnessing an increasing amount of local energy generation through renewable energy resources. Energy trade among the local energy generators ( aka prosumers) and consumers can reduce the energy consumption cost and also reduce the dependency on conventional energy resources, not to mention the environmental, economic, and societal benefits. However, these local energy sources might not be enough to fulfill energy consumption demands. A hybrid approach, where consumers can buy energy from both prosumers (that generate energy) and also from prosumer of other locations, is essential. A centralized system can be used to manage this energy trading that faces several security issues and increase centralized development cost. In this paper, a hybrid energy trading system coupled with a smart contract named SynergyGrids has been proposed as a solution, that reduces the average cost of energy and load over the utility grids. To the best of our knowledge, this work is the first attempt to create a hybrid energy trading platform over the smart contract for energy demand prediction. An hourly energy data set has been utilized for testing and validation purposes. The trading system shows 17.8% decrease in energy cost for consumers and 76.4% decrease in load over utility grids when compared with its counterparts.
Zahra Foroozandeh, Sérgio Ramos, João Soares, Zita Vale
This paper proposed a Mixed Binary Linear Programming (MBLP) approach to find the optimal size of some components of a Smart Building (SB) attempting to reduce the overall cost. The considered SB is equipped with local resources such as Photovoltaic (PV) panels, Electrical Vehicles (EVs), and the Battery Energy Storage System (BESS). Moreover, the SB is only connected with the grid by an Energy Management System (EMS) in which the whole SB has a single Contract Power (CP) such that EMS manages the power flow among external grid, local resources, apartments, and common services, for the goal of reducing the electricity bill. Hence, the wrong choice of CP and BESS capacity will impose unnecessary charges on the electricity bill. As a results, EMS has played a crucial role in SB in determining the best CP and BESS values. The obtained results of this work show the efficiency of the model in which by finding the optimal capacity of CP and BESS, the electricity bill improves by a 34% reduction.
Yang Xu, Ziming Liu, Cheng Zhang, Ju Ren · 6 authors
Renewable energy sources (RES) and low-carbon technology users play a vital role in modern power systems. However, RES generation is easily affected by the environment. Meanwhile, the load, such as electric vehicles (EVs) and prosumers, accounts for most low-carbon technology users. Their power is usually superimposed on peak loads without dispatching, which also exacerbates the instability of the power system. Current optimal dispatching mechanisms mainly rely on centralized organizations, while their dispatching process is not open and transparent. In this article, we propose a blockchain-based trustworthy dispatching approach for the distribution network in high renewable energy penetrated power systems. We first develop an optimal dispatching model considering EVs’ charging behavior and the prosumers’ economic benefits. With the model, prosumers can be dispatched to balance power and consume renewable energy, reducing the impact of disorderly charging on the grid and the abandonment of RES generation. An orderly charging iteration optimization (OCIO) algorithm is proposed to implement orderly EV charging while considering the charging cost and the period. We also propose a modified particle swarm optimization (mPSO) algorithm to publish dispatching tasks based on real-time power balance. Furthermore, blockchain is applied as an open and transparent ledger to record each entity’s power generation and consumption information, ensuring that the dispatching process is trustworthy. Finally, the effectiveness of the dispatching approach is verified in the modified IEEE 33-bus test system and Ethereum-based smart contracts.
Mohamed A. Mohamed, Seyedali Mirjalili, Udaya Dampage, Saleh H. Salmen · 6 authors
The impressive furtherance of communication technologies has exhorted industrial companies to link-up these developments with their own abilities with the target of efficiency enhancement through smart supervision and control. With this in mind, the blockchain platform is a prospective solution for merging communication technologies and industrial infrastructures, but there are several challenges. Such obstacles should be addressed to effectively adopt this technology. One of the most recent challenges relative to adopting blockchain technology is the energy consumption of miners. Thus, providing an accurate approach that addresses the underlying cause of the problem will carry weight in the future. This work addresses managing the energy consumption of miners by using the advantage of distributed generation resources (DGRs). Along the same vein, it appears that achieving the optimal solution requires executing the modified reconfirmation of DGRs and miners (indeed, mining pool systems) in the smart grid. In order to perform this task, this article utilizes the Intelligent Priority Selection (IPS) method since this method is up to snuff for corporative allocation. In order to find practical solutions for this problem, the uncertainty is also modeled as a credible index highly correlated with the load and generation. All in all, it can be said that the outcome of this research study can help researchers in the field of enhancement of social welfare by using the proposed technology.
T. Yuvaraj, K.R. Devabalaji, S. Srinivasan, Natarajan Prabaharan · 7 authors
The electric power distribution plays a crucial part in the power systems to maintain the power quality and stability of the system for loss mitigation and voltage regulation. The reactive power compensators like a capacitor, DG, and DSTATCOM play a vital role in power quality and stability improvement by providing proper reactive power in the distribution system. This article provides a critical review and comparative analysis of various compensating devices allocation to achieve power loss mitigation and voltage regulation in the radial distribution system (RDS). The Bat Algorithm (BA) and Voltage Stability Index (VSI) are utilized for determining the optimal size and site of the compensating devices in the RDS. Further, the application of Blockchain technology is utilized for voltage regulation of energy trading RDS. To show the effectiveness of the present study, an IEEE 33 test system is considered. All three compensators are implemented in IEEE 33 test system and compared with existing approaches. The present study is very much helpful to the Distribution Network Operators for selecting the suitable compensator in real-time applications.
Mingyu Yan, Mohammad Shahidehpour, Ahmed Alabdulwahab, Abdullah Abusorrah · 9 authors
This paper proposes a blockchain application for transacting energy and carbon allowance in networked microgrids (MGs). MGs submit trading energy and carbon allowance data to the centralized distribution system operator (DSO) operation, which would optimize the provision of energy and carbon allowance trading among MGs for satisfying power distribution network constraints. The hourly demand response along with onsite MG generation and the DSO’s trading exchanges with ISO are considered among market options to maximize MG payoffs and satisfy distribution network constraints. A cooperative game with externalities is applied to model the market behavior of networked MGs. A two-stage payoff allocation problem is devised to allocate the grand coalition payoff to participating MGs. A solution algorithm is proposed which consists of column-and-constraint generation (C&CG) and Karush-Kuhn-Tucker (KKT) conditions to solve the proposed two-stage market optimization problem with acceptable computational performance. Also, blockchain is applied to provide secure and effective transaction settlements and transparent distribution market operations in the proposed transactive energy and carbon allowance trading strategy. The proposed centralized transactive market is tested on a 4-MG system, the IEEE 33-bus system, and the IEEE 123-bus system. The numerical results show the effectiveness of the proposed method in incentivizing MGs to trade energy and carbon allowance while satisfying the distribution network constraints.
The grid connected photovoltaic (PV) power plants (PVPPs) are booming nowadays. The main problem facing the PV power plants deployment is the intermittency which leads to instability of the grid. In order to stabilize the grid, either energy storage device - mainly batteries - or a power curtailment technique can be used. The additional cost on utilizing batteries make it not preferred solution, because it leads to a drop in the return on investment (ROI) of the project. A good alternative, is using a customized load (such as; cryptocurrency-based loads) which consumes the surplus energy. This paper investigating the usage of a customized load - cryptocurrency mining rig - to create an added value for the owner of the plant and increase the ROI of the project. These devices are widely used to perform the required calculations for validating the transactions on the network of the Blockchain. A comparison between the ROI of the mining rig and the battery have been conducted in this study. Based on this study the mining rig has superior ROI of 7.7% - in the case with the lowest ROI - compared to 4.5% for battery. Moreover, an improved controlling strategy is developed to combine both the battery and mining rig in the same system. The developed strategy is able to keep the profitability as high as possible during the fluctuation of the mining network.
This work presents the design and implementation of a blockchain system that enables the trustable transactive energy management for distributed energy resources (DERs). We model the interactions among DERs, including energy trading and flexible appliance scheduling, as a cost minimization problem. Considering the dispersed nature and diverse ownership of DERs, we develop a distributed algorithm to solve the optimization problem using the alternating direction method of multipliers (ADMM) method. Furthermore, we develop a blockchain system, on which we implement the proposed algorithm with the smart contract, to guarantee the transparency and correctness of the energy management. We prototype the blockchain in a small-scale test network and evaluate it through experiments using real-world data. The experimental results validate the feasibility and effectiveness of our design.
Distributed optimization algorithms for security-constrained economic dispatch (SCED) problems have been the subject of significant research interest in recent years. However, existing distributed SCED algorithms can be ineffective in the presence of malicious participants and inefficient in the absence of a coordinator. On the other hand, blockchain, an emerging technique known as the trust machine, has not shown its potential to address the above challenges in state-of-the-art literature. This paper proposes a blockchain-based distributed SCED algorithm. Using blockchain to form a coordination committee and enable balance among committee members, the proposed method allows the use of hierarchical SCED algorithms in the absence of a coordinator and can disable malicious participants. Numerical results show the robustness and necessity of the proposed blockchain-based SCED algorithm, by comparing the SCED results with and without blockchain.
The advent of distributed energy resources (DERs), such as distributed renewables, energy storage, electric vehicles, and controllable loads, \rv{brings} a significantly disruptive and transformational impact on the centralized power system. It is widely accepted that a paradigm shift to a decentralized power system with bidirectional power flow is necessary to the integration of DERs. The virtual power plant (VPP) emerges as a promising paradigm for managing DERs to participate in the power system. In this paper, we develop a blockchain-based VPP energy management platform to facilitate a rich set of transactive energy activities among residential users with renewables, energy storage, and flexible loads in a VPP. Specifically, users can interact with each other to trade energy for mutual benefits and provide network services, such as feed-in energy, reserve, and demand response, through the VPP. To respect the users' independence and preserve their privacy, we design a decentralized optimization algorithm to optimize the users' energy scheduling, energy trading, and network services. Then we develop a prototype blockchain network for VPP energy management and implement the proposed algorithm on the blockchain network. By experiments using real-world data-trace, we validated the feasibility and effectiveness of our algorithm and the blockchain system. The simulation results demonstrate that our blockchain-based VPP energy management platform reduces the users' cost by up to 38.6% and reduces the overall system cost by 11.2%.
This paper proposes an energy scheduling mechanism among multiple microgrids (MGs) and also within the individual MGs. In this paper, electric vehicle (EV) energy scheduling is also considered and is integrated in the operation of the microgrid (MG). With the advancements in the battery technologies of EVs, the significance of Vehicle-to-Grid (V2G) is increasing tremendously. So, designing the strategies for energy management of electric vehicles (EVs) is of paramount importance. The battery degradation cost of an EV is also taken into account. Vickrey second price auction is used for truthful bidding. To enhance the security and trust, blockchain technology can be incorporated. The market is shifted to decentralized state by using blockchain. To encourage the MGs to generate more, contribution index is allotted to each prosumer of a MG and to the MGs as a whole, depending on which priority is given during auction. The system was simulated using IEEE 118 bus feeder which consists of 5 MGs, which in turn contain EVs and prosumers.
Decomposing the large distribution grids into interconnected microgrids (MGs) can potentially enhance the power system's efficiency, sustainability, resiliency, and reliability. However, energy management within the entire network would be more complicated and challenging. This article develops a novel energy management framework for interconnected MGs based on a blockchain technology. Utilizing the blockchain technology can potentially enhance the system security, and also reduce the system risks, mitigate financial fraud, and cut down the operational cost. A priority list is first defined to get into an efficient energy tradeoff within the interconnected MGs. Moreover, the incentive contract is proposed to provide a price discount for a party that purchases more power from one sub-MG. A stochastic framework based on the unscented transform technique is also established to manage the uncertainties associated with hourly load demands and output power of renewable energy sources. The proposed model is formulated as a mixed-integer linear programming problem and solved through the blockchain-based energy/power management algorithm. The case study includes residential, industrial, and commercial MGs-namely, three residential, one commercial, and one critical load (hospital). The simulation results show the high efficiency and effectiveness of the proposed model and validate its economic and reliability merits.