This paper presents an integrated control and transactional framework aimed at enhancing the stability, resilience, and automation of decentralized microgrid systems. The proposed approach combines an advanced Sliding Mode Control (SMC) scheme with blockchain-enabled smart contracts to address critical challenges associated with conventional control strategies, including slow convergence rates, susceptibility to disturbances, and limited scalability. The SMC is augmented with a nonlinear disturbance observer to provide fast transient response, robust disturbance rejection, and reduced control chattering under dynamic operating conditions. A closed-loop interaction between the SMC and blockchain layers enables continuous two-way communication. Real-time operational parameters, such as power imbalances, voltage deviations, and frequency fluctuations, are transmitted from the controller to the blockchain layer. In response, smart contracts autonomously trigger control adjustments and Demand Response (DR) actions, which are fed back to the SMC as reference inputs. This dynamic feedback loop enables the system to adapt to fluctuations and uncertainties in both energy generation and consumption, thereby ensuring consistent power quality and system stability. Experimental results confirm the system’s ability to maintain stability and improve power quality under varying operational conditions. Moreover, the system facilitates coordinated energy exchange among interconnected microgrids, thereby supporting the integration of local renewable energy sources and reducing dependence on centralized grid infrastructure.

Renewable-driven microgrids require transparent and adaptive coordination mechanisms to manage variability in distributed generation and flexible demand. Conventional pricing schemes and centralized demand-side programs are often insufficient to regulate real-time imbalances, leading to inefficient renewable utilization and limited prosumer participation. This work proposes a blockchain-integrated Stackelberg pricing model that combines real-time price regulation, optimal demand-side management, and peer-to-peer energy exchange within a unified operational framework. The Microgrid Energy Management System (MEMS) acts as the Stackelberg leader, setting hourly prices and demand response incentives, while prosumers and consumers respond through optimal export and load-shifting decisions derived from quadratic cost models. A distributed supply–demand balancing algorithm iteratively updates prices to reach the Stackelberg equilibrium, ensuring system-level feasibility. To enable trust and tamper-proof execution, smart-contract architecture is deployed on the Polygon Proof-of-Stake network, supporting participant registration, day-ahead commitments, real-time measurement logging, demand-response validation, and automated settlement with negligible transaction fees. Experimental evaluation using real-world demand and PV profiles shows improved peak-load reduction, higher renewable utilization, and increased user participation. Results demonstrate that the proposed framework enhances operational reliability while enabling transparent and verifiable microgrid energy transactions.

This study proposes a decentralized, blockchain-enabled demand response (DR) framework to address the limitations of traditional centralized DR systems, which often suffer from privacy vulnerabilities, single points of failure, and susceptibility to Sybil attacks. By combining a hybrid Proof-of-Stake (PoS) mechanism with dynamic reputation scoring, the framework ensures secure and Sybil-resilient validator selection for consensus. To preserve privacy, Zero-Knowledge Proofs (ZKPs) ,SNARKs are embedded into smart contracts, enabling verifiable energy transactions without revealing sensitive bid or identity information. A dynamic game-theoretic model is used to capture the strategic interactions of prosumers during DR events, with formal analysis proving convergence to the Nash equilibrium under practical load conditions. The system is implemented using Solidity on the Polygon Mainnet and evaluated with real residential data from the Pecan Street dataset. Experimental results demonstrate significant performance gains, including a 12% reduction in peak demand, a 10% increase in prosumer generation, 83% load-shifting efficiency, and a 5.26% improvement in cost savings compared to static demand-side management (DSM) schemes. Additionally, the framework effectively mitigates 99% of Sybil attacks and achieves consensus within 8 s for up to 1000 nodes, highlighting its scalability, security, and suitability for integration with national DR platforms, carbon credit markets, and autonomous multi-agent energy systems.

The integration of renewable energy sources and distributed energy resources (DERs) has driven the evolution of modernized nested microgrids, enhancing resilience and flexibility in power distribution systems. Grid-following (GFL) and grid-forming (GFM) inverters are central to these systems, with GFL units emulating current sources challenged by uncertain grid impedance, and GFM units emulating voltage sources required to adapt to dynamic load variations. Mode transitions introduce instability through multi-loop control interactions. This work presents a comprehensive dynamical stability analysis of GFL and GFM inverters in nested microgrids, supported by advanced control strategies addressing dynamic response limitations, sensor dependencies, filter fluctuations, and controller complexities. An eigenvalue-based framework identifies dominant oscillatory modes, while online adaptation mitigates disturbances to preserve closed-loop performance. Time-evolution modeling of observables enables enhanced real-time monitoring. A blockchain-enabled decentralized framework ensures secure, transparent, and automated stability actions. Hardware-in-the-loop (HIL) experiments on a modified IEEE 123-node test feeder demonstrate a total harmonic distortion (THD) of 1.75% under weak-grid conditions compared with 2.73%, 4.76%, 8.40%, and 2.2% for other approaches and 0.3% under grid-impedance variation and <0.3% under nonlinear loading. The proposed controller achieves 0.06% tracking error dynamics and 0.02% steady-state error, outperforming classical methods (0.32–0.87% and 0.17–0.38%, respectively), with a computational time of 29 ms. The blockchain layer, implemented on the Polygon network, achieved a measured throughput of 1,572 transactions/s, an average block time of 2.3 s, and transaction fees below $0.01 USD, enabling rapid, economical, and scalable peer-to-peer stability service execution.

In isolated microgrids, distributed energy resources (DERs) such as small-scale generators, energy storage systems, and flexible loads operate independently from the main grid. The challenge is to optimize these resources to minimize user costs while ensuring microgrid stability and efficiency. This paper presents an optimization framework for DERs, leveraging a game-theoretical approach to demand-side management (DSM) in an isolated microgrid environment. Each participant aims to minimize their total cost by strategically managing renewable energy generation, storage, and consumption. The framework models the DSM problem as a noncooperative game, identifying equilibrium points where no user can unilaterally reduce costs. The proximal decomposition algorithm is employed to iteratively update user strategies, ensuring convergence to a Nash equilibrium. Furthermore, a blockchain-based system with smart contracts is integrated to automate critical processes, including registration, event detection, DSM actions, and incentive distribution. This integration enhances transparency, security, and efficiency in the microgrid. During the registration phase, all devices are authenticated and authorized through a secure, transparent blockchain ledger. Event detection is managed by the microgrid Energy Management System (EMS), which continuously monitors voltage and frequency levels, triggering predefined smart contract responses to maintain stability. DSM actions are automatically executed by smart contracts, adjusting energy loads, generation, and storage to balance supply and demand dynamically. The smart contracts also manage the economic incentives that drive participant engagement. They calculate and distribute incentives based on predefined criteria, ensuring accurate and prompt allocation. This process is recorded on the blockchain, providing an immutable and auditable trail of actions and rewards. By leveraging blockchain technology and a game-theoretical approach, the proposed framework ensures continuous optimal operation despite fluctuations in energy demand and renewable generation. This dynamic and adaptive model promotes decentralized and efficient energy management within the microgrid, fostering a resilient and sustainable energy ecosystem.

The paper introduces a novel decentralized electricity market framework tailored for network community microgrid systems, leveraging blockchain technology. It presents a comprehensive model that integrates blockchain with a microgrid energy management system (MEMS) to facilitate peer-to-peer (P2P) energy trading, thereby ensuring optimal power flow and mitigating line congestion. The proposed optimization model takes into account crucial factors such as line flow constraints, market clearance price (MCP) using the double auction method, and social welfare optimization for energy transactions among buyers (consumers) and sellers (prosumers). By incorporating the power transfer distribution factor (PTDF) to calculate service charges associated with distribution network usage, the model safeguards the interests of all market participants while minimizing the risk of line overload. A case study is conducted to illustrate the efficacy of the proposed model, demonstrating the tangible benefits of blockchain integration in effectively managing and optimizing decentralized energy trading within microgrid environments. The proposed blockchain model for P2P energy trading offers a compelling alternative to conventional microgrid energy trading systems. By streamlining trade execution and eliminating intermediaries, it significantly reduces transaction times, with average processing times of around 10 s, highlighting its rapid processing capabilities. Furthermore, its decentralized nature and cryptographic security mechanisms provide robust protection against tampering and fraud, ensuring the integrity of transactions. Additionally, the transparent ledger system guarantees complete audibility and fairness for all participants, distinguishing it from opaque processes typical in traditional models.

This paper presents a security analysis of blockchain networks with Proof-of-Stake (PoS) consensus mechanisms focusing on mitigating quantum attacks. With the advent of quantum computing, traditional cryptographic algorithms used in blockchain are at risk of being compromised, posing significant vulnerabilities to the integrity, confidentiality, and availability of blockchain systems. We explore the specific threats posed by quantum computing advancements, such as Shor’s algorithm and Grover’s algorithm, which can potentially break public key cryptography and weaken hash functions respectively. In response to these threats, we propose the implementation of quantum-resistant cryptographic solutions to safeguard blockchain networks. Our proposed solutions include the use of Keccak-based cryptographic algorithms, renowned for their robustness and efficiency in resisting quantum attacks. We detail the integration of these algorithms into blockchain platforms, ensuring that the core processes of stake verification, transaction signing, and block validation are secure. Additionally, we design and evaluate the effectiveness of the quantum-resistant Proof-of-Stake (PoS) consensus mechanism which leverages Keccak for hashing and Winternitz One-Time Signature (WOTS) for digital signatures. Through this integration, we aim to strengthen blockchain networks against the computational capabilities of future quantum computers, thus preserving the security and trustworthiness of blockchain systems.

The integration of distributed energy resources (DERs) and digital technologies has accelerated the transition to decentralized energy systems. Among these technologies, blockchain stands out for its ability to facilitate peer-to-peer (P2P) energy trading efficiently and securely. This paper explores the concept of P2P energy trading within community microgrid systems, leveraging blockchain-based smart contracts. The proposed system integrates an incentive-driven demand response program directly into the smart contract framework, offering real-time rewards for load-balancing contributions. By incorporating the microgrid’s Energy Management System (EMS) and transparently recording all transactions on the blockchain, the proposed platform provides detailed data and immediate reward distribution. At the core of our system lies the Supply to Demand Ratio (SDR), ensuring fair energy exchange within the community. Dynamic pricing, enabled by blockchain and Tether (USDT) cryptocurrency, adjusts to real-time market conditions, enhancing transparency and responsiveness in energy trading. This adaptive pricing model fosters a more equitable and efficient trading environment compared to static approaches. Moreover, this system is tailored for community microgrids, emphasizing a community-centric approach. Local prosumers serve as validators in the blockchain network, aligning energy management decisions with community needs and dynamics. This localized engagement promotes efficiency and participation, fostering resilient, sustainable, and user-centric energy landscapes. Through rigorous analysis, we demonstrate the system’s effectiveness in optimizing economic efficiency, reducing operational costs, and increasing compliance rates. By combining blockchain technology with community-focused design principles, the proposed platform represents a significant advancement towards self-sufficiency and resilience in local energy systems.

Through a digital platform, distributed generations can be managed intelligently to increase the overall efficacy of the distribution system. It was made possible by the growing integration of distributed generation with smart meters, IoTs, smart sensors, etc. Decentralized peer-to-peer (P2P) energy trading is a new concept and is encouraged by blockchain technology (BT) due to its transparency, security, and speedy transaction handling. This paper expands on the P2P concept by creating a decentralized energy trading system to demonstrate the benefits of BT in providing a secure and efficient transaction platform for a community microgrid system containing consumers, prosumers, and RES owners. The supply-demand ratio (SDR) method is used to determine the P2P selling and buying prices within the network based on the optimized allocations of the prosumers/ Renewable Energy Sources (RES) owners and consumers. This Paper highlights the participation of miners (validators) in the microgrid ecosystem, specifically local prosumers, and RES owners. By actively participating in the energy trading, miners can enhance energy security, increase system resilience, and enjoy financial incentives. The suggested model designed on the Ethereum platform showcases effective energy management of microgrid system operation, and increased security level through a step-by-step implementation process.

The growing integration of Information and Communication Technologies (ICT) in smart grids has increased their vulnerability to cyber threats. Traditional security measures often struggle to protect against advanced attacks that target the decentralized nature of smart grids. This paper proposes a blockchain-based security framework designed to enhance data integrity and automate access control within smart grids. The framework leverages a permissioned blockchain to ensure scalability and performance while employing smart contracts to enforce security policies in real-time. Key elements include an optimized consensus mechanism for low-latency processing and smart contracts for dynamic security enforcement. Simulation results show an average transaction processing time of 0.0457 seconds, demonstrating the framework's ability to handle a high volume of transactions efficiently. Additionally, the framework achieved a 100% success rate in device authorization and incident response tasks, with zero transaction failures. Gas usage and transaction costs were also maintained at minimal levels, ensuring resource efficiency. These findings indicate that the proposed blockchain-based approach provides a scalable, efficient, and resilient security solution tailored to the dynamic environment of smart grids.

The need for effective and secure energy management systems has arisen as a result of increased demand for energy, the increasing use of renewable energy sources (RES), and the introduction of decentralized power generation. Here, we explore the urgent issues and exciting possibilities posed by traditional centralized energy networks, with a special focus on three crucial dimensions: achieving supply-demand equilibrium, seamlessly integrating renewable energy sources, and maintaining participant trust and transparency. This paper suggests leveraging blockchain technology (BT) to create a decentralized network grid energy management system to address these issues. Individual participants can directly exchange energy with one another within the Decentralized Network Grid through peer-to-peer (P2P) trading. The network microgrid model’s mathematical optimization is designed to balance supply and demand, improve network microgrid stability, and optimize energy distribution. The aforementioned optimization uses information from grid constraints, usage patterns, and energy pricing to make wise decisions in real time. The concept aims to achieve energy efficiency, cost savings, and seamless integration of renewable energy sources by utilizing the capabilities of blockchain smart contract and proposed optimization algorithm.

A digital platform can be used to intelligently manage the distributed generations to improve the overall performance of the distribution system. It became possible by the growing integration of distributed generation with smart meters, IoTs, smart sensors, etc. The adoption of blockchain technology (BT) for decentralized Peer-to-Peer (P2P) energy trading is encouraged because of its transparency, security, and fast transaction processing. This paper expands on the P2P concept by creating a decentralized energy trading system to demonstrate the benefits of BT in offering a secure and efficient transaction platform for a community microgrid system having consumers, prosumers and RES owners. The supply-demand ratio (SDR) approach is used to estimate the P2P purchasing and selling pricing within the microgrid. In order to meet the community's energy demands in the most effective way, the proposed P2P design framework mentioned in this paper has targeted the development of a community trading market using Blockchain Smart Contract. Additionally, ELEC (Electrify. Asia) cryptocurrency is considered in P2P energy trading simulation that is successfully mined and published on the blockchain network.

The concept of the microgrid is developing due to the increased use of distributed energy resources at the community level. The benefits from microgrid enable the concept of a community microgrid. The community microgrid system helps in the energy management and operation on its own thus making it a decentralized system. Peer-to-Peer (P2P) energy trading is the most common and efficient way of exchanging power within the community, or with the neighbor community, or with the grid thus making the whole system easy. This paper proposes an energy management system of the local community in a decentralized manner and therefore proposes a model for power trading using the blockchain approach. In this paper, we considered all aspects of the systems like using Demand response programs. This results in a cost-effective way by verifying using simulations.

The growing integration of distributed generations and battery storage equipped with smart meters paves a way to smartly manage the Distributed Energy Resources (DER) using a digital platform to improve the overall performance of the microgrid system. The deployment of distributed energy resources, particularly solar photovoltaic and wind generation, has transformed conventional power consumers into active prosumers. As a result of the expansion and digitalization of power distribution infrastructures, peer-to-peer (P2P) energy intra-trading has evolved as a new paradigm in electricity trade in the community microgrid system. Blockchain is being used to encourage P2P energy intra-trading amongst prosumers, consumers, and Renewable Energy Sources (RES) owners because of its transparency, security, and speed in completing transactions. This P2P concept is further extended in this work to establish a self-sustained community microgrid system in energy trading with a case study to showcase the merits of blockchain technology in providing a secure and effective trading platform for mass users. As a result, the proposed work presents a solution for a secured energy management system that uses blockchain technology to create a decentralized microgrid energy market model that depicts P2P energy transactions with the incorporation of a battery storage system. Again, the microgrid P2P market settles the clearing price considering the probable response of customers when the price varies and incentive is paid to customers and prosumers to change the pattern of using of loads. According to the findings, end-users benefit from energy savings and self-sufficiency due to the combination of automated P2P trade and storage flexibility. Furthermore, a sort of crypto-currency “Cosmos (Atom)” is simulated in the P2P market model and published via the blockchain's mining mechanism. The proposed design framework presented in this paper has addressed the implementation of an effective energy management platform for developing a self-sustained microgrid system using distributed energy resources.

The power distribution sector has transformed from passive to active and smart networks with the incorporation of a new technological evolution like IoTs, digital technology like machine learning, AI, Blockchain Technology, etc. This transformation has brought the concept of the microgrid in the distribution side where consumers or prosumers (consumers having active energy sources like PV solar, wind energy, etc.) can interact directly with the generation-side (main grid or prosumers). Microgrid with smart meters, IoTs enabled technology can form a new trading environment i.e., Peer-to-Peer (P2P) energy trading, unlike the traditional grid feed-in trading system. The P2P trading provides a community microgrid system towards a selfsustained and self-reliant in meeting their energy demand in which RES owners, prosumers, and consumers play an important role in achieving microgrid net demand-generation balance. Smart contract in blockchain helps the microgrid network to manage energy trading in an efficient, fast, easy implementation in a secure and automated manner for P2P energy trading. Microgrid Energy Management System (MEMS) manages the whole network to see the technical parameters violation check and opens the trading market through the Smart Contract in the blockchain as Network Administrator to facilitate the user’s friendly trading environment and works as an entity of the Distribution System Operator (DSO). Step by step procedure for implementing this concept has been explained and justifies the suitability of using blockchain technology to achieve net demand-generation balance, saving in cost, green energy towards an approach for the self-sustained microgrid system.

Information and communication technology (ICT) used in smart grid to operate, monitor and control data to achieve high efficiency, reliability, economics and sustainability. However, smart grids are more vulnerable to security attacks compared to traditional grids because they connect to the Internet and wireless networks. Key management is important security challenge to achieve data confidentiality and integrity in smart grid. Many key management solutions have been devised to fulfil these requirements but they have weakness such as lack of flexibility, scalability and support message communication. This paper describes existing security challenge issues and their solutions for smart grid and SCADA system and also discussed their limitations.

Robust control has emerged as a new field of control engineering research that primarily deals with obtaining system robustness in presences of uncertainties. In this paper, a graphical design method for obtaining the entire range of PI controller gains that robustly stabilize a non reheat AGC plant in presence of additive uncertainty is discussed. This design method mainly depends on the frequency response of the system which can serve to reduce the complexities involved in plant modelling. We have applied our design method to a single area non-reheat steam generation unit. The results were found satisfactory and robust stability was achieved for the said plant.

This paper presents an efficient and reliable interior point approach to obtain optimal power flow (OPF) problem solution. The Interior Point method (IP) is found to be the most efficient algorithm for optimal power flow solution. The IP algorithm is coded in MATLAB and the performance is tested on IEEE 14 bus test system with fuel cost minimization as objective function. It maintains good accuracy while achieving the high speed of convergence when compared to other known linear programming methods. The solution obtained by this algorithm proves to be robust to solve the OPF problem of power grid.

The smart grid can be viewed as a digital upgrade of the existing electricity infrastructure to allow for dynamic optimization of current operations as well as incorporate dynamic gateways for alternative sources of energy production. The smart grid is the modern day power transmission system with non conventional energy resources and FACTS controllers. The modern day power transmission system is a network of interconnection which connects systems at intra-regional, inter-regional and national level. Due to deregulation of the power sector, the basic transmission challenge is to provide a network capable of delivering contracted power from power supplies to consumers over a large geographical area. Power transfer in most integrated transmission system is constrained by transient and voltage stability. The power transfer capability of any transmission line largely depends on the reactance of the line keeping the transmission voltages constant. The mismatch of reactance between a group of transmissions lines result in uneven power sharing between them which may cause one or more lines to be overloaded beyond its rating. FACTS controllers can be effectively used to manage the flow of active and reactive powers of transmission systems such that no line is overloaded. This paper discusses the use of Series FACTS controllers in order to change line reactance and phase angle for controlling the power flow in a transmission system.

Since the very beginning of FACTS controllers, congestion management is one of the parameters we control through it. This paper provides the control of power flow and bus voltages in grid using the FACTS controllers. In AC transmission line, power flow can be controlled by injecting a compensating voltage in series with the line. We consider the steady state model of two FACTS Controllers - SSSC, UPFC and SSSC with POD (Power Oscillation Damper) for series voltage compensation, and evaluating their range of power flow control for power grid management. Power flow control ranges are evaluated for a standard 5 bus system. The process of reducing the congestion on power system using FACTS devices are not new, but a combination of POD and FACTS devices are rare. In this research paper, the transmission lines are decongested using this combination and thus the power capability of the transmission system increases. Results are reported to compare the effectiveness of the different FACTS controllers.