Blockchain for decentralized transactive energy management system in networked microgrids

This paper provides a strategic solution for enhancing the cybersecurity of power distribution system operations when information and operation technologies converge in active distribution network (ADN). The paper first investigates the significance of Internet of Things (IoT) in enabling fine-grained observability and controllability of ADN in networked microgrids. Given severe cybersecurity vulnerabilities embedded in conventionally centralized energy management schemes, the paper then proposes a cyber-secure decentralized energy management framework that applies a distributed decision-making intelligence to networked microgrids while securing their individual mandates for optimal operation. In particular, the proposed framework takes advantage of software-defined networking technologies that can secure communications among IoT devices in individual microgrids, and exploits potentials for introducing blockchain technologies that can preserve the integrity of communications among networked microgrids in ADN. Furthermore, the paper presents the details of application scenarios where the proposed framework is employed to secure peer-to-peer transactive energy management based on a set of interoperable blockchains. It is finally concluded that the proposed framework can play a significant role in enhancing the efficiency, reliability, resilience, and sustainability of electricity services in ADN.

With increasing penetrations of renewable energy in power distribution systems, operators is facing challenges on reducing renewable energy curtailment, which is caused by supply-demand mismatch, feeder congestion, and nodal voltage limits. Converting surplus renewable electricity into hydrogen by electrolyzors has been recognized a potential way to address this. To this end, we proposed a coordinated operation approach for hydrogen and power distribution systems, considering distribution level power and hydrogen pipeline flows, as well as storage capabilities provided by linepack. The proposed approach can be used to investigate the benefits from our coordinated approach on the basis of current separated practice. Our numerical simulations show that the proposed coordinated dispatch model can utilize the benefit of renewable power to minimum the total cost and improve the utilization of transmission lines.

Large-scale integration of rooftop solar power generation is transforming traditionally passive power distribution systems into active ones. High penetration of such devices creates new dynamics for which the current power distribution systems are inadequate. The changing paradigm of power distribution system requires it to be operated as cyber-physical system. A goal-based holonic multiagent system (HMAS) is presented in this paper to achieve this objective. This paper provides details on design of the HMAS for operation of power distribution systems. Various operating modes and associated goals are discussed. Finally, the role of HMAS is demonstrated for two applications in distribution systems. The first one is associated with control of reactive power at solar photovoltaic installations at individual homes for optimal operation of the system. The second deals with the state estimation of the system leveraging different measurements available from smart meters at homes.

16 - Blockchain-enabled energy sector management

Network reconfiguration is an alternative to reduce power losses and optimize the operation of power distribution systems. In this paper, an encoding scheme for evolutionary algorithms is proposed in order to search efficiently for the Pareto-optimal solutions during the reconfiguration of power distribution systems considering multiobjective optimization. The encoding scheme is based on the edge window decoder (EWD) technique, which was embedded in the Strength Pareto Evolutionary Algorithm 2 (SPEA2) and the Nondominated Sorting Genetic Algorithm II (NSGA-II). The effectiveness of the encoding scheme was proved by solving a test problem for which the true Pareto-optimal solutions are known in advance. In order to prove the practicability of the encoding scheme, a real distribution system was used to find the near Pareto-optimal solutions for different objective functions to optimize.

The Block-chain-based virtual power plant can realize the coordination and integration of distributed energy resources in accordance with peer-to-peer energy transactions. In particular, the smart contract function of the Block-chain can assist energy transactions in the virtual power plant and can enable the local network to meet the clean energy partiality. In order to achieve the above functions, firstly, a virtual power plant transaction model based on smart contracts was constructed, including energy index, energy transaction partiality, and physical constraints. Secondly, a pre-distributing strategy for energy transactions was proposed with smart contracts designed based on the Minimum Cost Programming, using the automatic settling function of smart contracts to omit energytrading transfer stations and to achieve weakly-centralized energy peer-to-peer transactions. Finally, a building virtual power plant was established as a transaction scenario with a typical distribution network topology. The simulation results illustrated that the strategy could satisfy the clean energy partiality of energy transactions to a certain extent, and it could realize weakly-centralized transactions by Block-chain.

Decentralized transactive energy management of multi-microgrid distribution systems based on ADMM

The lack of trust caused by rigid pricing strategies, third-party participation, and transaction default may lead to a decline in transaction willingness and misgivings about the availability of resources among microgrids (MGs). In particular, if large-scale transaction default occurs, it may endanger the safe and stable operation of the power grid. In this paper, a two-stage energy auction model based on blockchain and smart contracts to solve the problem of lack of trust and transaction default, and to increase flexibility in energy transactions among microgrids is proposed. The novelty of the proposed method lies in the transaction incentives and management of payment defaults through smart contracts and the partition management of buyer MGs' energy demands. Partitioning energy demands in the first stage of the auction can increase the diversity of sellers' bidding in the second stage. A credit management model based on the completion of historical transactions is designed to manage defaults. The priority factor affecting transaction order and energy allocation is designed to incentivize transactions. The introduction of blockchain can reduce dependence on trusted third parties and solve the security and privacy issues of transactions. Smart contracts are used to host the entire process of the auction and record, calculate the priority of each microgrid before the auction starts, and allocate energy fairly. In the energy delivery stage, the smart contract determines whether there is a default and automatically realizes the transfer of transaction funds, avoiding any selfish behavior in the transaction. Finally, we verify the effectiveness of the above-mentioned trading method through numerical analysis.

The upward trend in energy prices makes it necessary to find new ways to provide electricity to end consumers. The cooperation between different self-consumption facilities that form an energy community based on networked microgrids can be a more efficient way of managing the available renewable resources. However, the complexity of its associated control problem is bringing unresolved challenges from the point of view of its formulation. The optimization of energy exchanges among microgrids in the day-ahead electricity market needs to generate an optimal profile for the purchase and sale of energy with the main grid, being charged for any deviation from the schedule proposed in the regulation service market. Microgrids based on renewable generation are systems subject to inherited uncertainties in their energy forecast, whose interconnection generates a distributed control problem of stochastic systems. Microgrids are systems of subsystems that can integrate various components, such as hybrid energy storage systems (ESS), generating multiple terms to be included in the associated cost function for its optimization. In this work, the problem of solving complex distributed stochastic systems in the Mixed Logic Dynamic (MLD) framework is addressed, generating a tractable formulation to generate deterministic values for both exchange and output variables in interconnected systems subject to uncertainties using hybrid, stochastic and distributed Model Predictive Control (MPC) techniques.

The urban rail transit traction power supply cable bears the important tasks such as power connection and power transmission among the main substation, the traction and buck stations. Due to the greater length of the power supply cable, the series parallel resonance problem caused by the charging capacitor is a serious threat to the safe and stable operation of the rail transit system. In order to ensure the safe and stable operation of power supply and distribution system of urban rail transit system, this paper studies the design and selection of traction power supply cable for urban rail transit under the harmonic constraint. The method can effectively avoid the safety problem of the harmonic series-parallel resonance due to cable charging capacitance in the traction power supply system for urban rail transit users. At the same time, it also has guiding significance for the design of cable length and charging capacity of other power supply and distribution system.

In recent years, power systems have shifted from centralized generation and one-way transmission toward distributed architectures that are centered on renewable energy, energy storage, and electric vehicle charging. This transition highlights the need for advanced control and operational strategies in microgrids and distribution networks that not only enhance efficiency but also secure stability, flexibility, and reliability. With growing variability and forecasting uncertainties in renewable generation and demand, sophisticated approaches are required to manage uncertainty and sustain system stability.This Special Issue presents nine contributions on control, operation, optimization, energy management systems, and AI-based approaches for microgrids and distribution networks. The papers span theoretical modeling, algorithm development, hardware implementation, and case studies. Highlights include a switched-capacitor inverter reducing common-mode voltage, an ANN-assisted energy management framework integrating load and weather forecasting with DC exchange and storage scheduling, flexible operating envelopes for reverse power flow grids, techno-economic studies of underground systems, seamless AC/DC hybrid microgrid control, deep learning for transformer fault detection, and voltage regulation for inverter-based UPS systems.Collectively, these works reflect the technological trajectory toward more advanced and sustainable power systems. This volume provides researchers and practitioners with insights into the state of the art and points to promising directions for future research and applications.

The growth of photovoltaic distributed generation has introduced significant challenges to both the operation and planning of power distribution systems. Currently, operational problems, power quality issues, and protection concerns are very common, directly associated with the high penetration of solar photovoltaic generation systems. Among the most commonly faced problems are voltage violations, exceeding thermal limits of transformers and conductors, increased voltage unbalances and harmonic distortions, as well as high technical losses and improper operation of overcurrent protection systems. In this context, this work aims to present contributions to the analysis of the impacts of photovoltaic distributed generation on power distribution systems through: (a) characterization, through experimental tests, of inverters used in photovoltaic distributed generation, in terms of harmonic and inter-harmonic emissivity, injection of direct current, and short-circuit contribution, since such information is rarely found in manufacturer catalogs; (b) development and construction of a voltage sag generator for conducting short-circuit contribution tests of the tested inverters; (c) development of a methodology for analyzing the hosting capacity of photovoltaic distributed generation considering a stochastic allocation approach in low-voltage circuits involving the most frequently encountered impacts in the distribution system, as well as the application of traditionally adopted mitigation methods; (d) development of a computational tool with a graphical interface for processing hosting capacity analyses; (e) development of a methodology for studying the impact of photovoltaic distributed generation on the protection of power distribution systems, considering a time-domain approach. As a result, important solutions and discussions are presented to assist engineers in better planning and management of photovoltaic distributed generation, contributing to the sustainability and efficiency of distribution networks in the face of the growing use of photovoltaic solar energy.

The world today has realized the vast technological evolution that has greatly shaped the production and management functions of business enterprises. Traditional contracts can take weeks or even months to initiate, and there have been numerous instances of breaches and lack of trust for contracts in both the private and public sector. A smart contract can be defined as a self-executing contract that utilizes blockchain technology to digitally enforce, verify, or facilitate the performance or negotiation of a contract. Owing to the security and decentralized system exhibited by blockchain technology, smart contracts can foster transaction credibility between contracting parties without the necessity of third parties as exhibited in traditional contracts. Any business organization that aims at achieving greater heights in management and production dimensions must consider utilizing robust technologies that are aimed at bolstering its competitive edge. Owing to the newness of smart contracts, characterized by very few studies on the same, this research reviews how smart contracts through blockchain technology can be implemented in an organization to enhance performance and outlines the applications, benefits, and limitations associated with such contracts. Keywords: Blockchain technology; smart contracts; smart contract applications; smart contract benefits; smart contract implementation; cryptography; cryptocurrency DOI : 10.7176/JIEA/9-5-07 Publication date :September 30 th 2019

The reliability and efficiency of transformers are crucial for the stable operation of power distribution systems. This project focuses on the Condition Monitoring of Transformers Based on IoT Technology, enabling real-time monitoring of critical parameters such as temperature, oil level, voltage. By integrating sensors, Arduino Uno, and the NodeMCU ESP8266 WiFi module, the system continuously collects data and transmits it to a cloud-based platform for remote monitoring and analysis. The implementation of IoT technology enhances predictive maintenance, reducing unexpected failures and minimizing downtime. Additionally, data-driven insights help optimize transformer performance, extend its lifespan, and reduce maintenance costs. This approach ensures a more efficient, reliable, and cost-effective power distribution network.

The selection of power sub-station location and distribution line routing in power systems is one of the important strategic decisions for both private and public sectors. In general, contradictory factors such as availability, and cost, affects the appropriate selection which adheres to vague and inexact data. The work presented in this research deals with the development of models and techniques for planning and operation of power distribution system. The work comprises a wider framework from the siting of a sub-station to load flow analysis. Work done also shows the application of quantum- geographic information system (Q-GIS) in finding load point coordinates and existing sub-station locations. The proposed integrated approach provides realistic and reliable results, and facilitates decision makers to handle multiple contradictory decision perspectives. To accredit the proposed model, it is implemented for power distribution planning in Bihar which consists of 9 divisions. A Cubic Spline Function-based load flow analysis method is developed to validate the proposal.