Sustainable Energy Grids & Networks最新文献

{"title":"A multi-agent energy management framework for decentralised and deregulated operation of next-generation port terminals","authors":"Shitikantha Dash,&nbsp;Anupam Trivedi,&nbsp;Dipti Srinivasan","doi":"10.1016/j.segan.2025.101978","DOIUrl":"10.1016/j.segan.2025.101978","url":null,"abstract":"<div><div>Energy consumption in future ports is expected to be quite significant and therefore necessitates careful resource management to ensure profitability and carbon neutrality. This paper explores the possibility of implementing a new energy management framework (EMF) among multiple agents—namely, terminal operators, port authority, and the grid—within a large and complex seaport system. The primary objective of this EMF is to reduce overall energy procurement costs for the port authority through a fair allocation of internal distributed energy resources (DERs) while providing better computational scalability, information privacy, and communication cybersecurity. To achieve this goal, first, dissimilar DERs available with the agents are generically profiled based on their operation time, flexibility and power level. Second, an alternating direction method of multipliers (ADMM)-driven local energy market (LEM) is established to efficiently manage the surplus and deficit of available DERs among the terminals in a decentralised manner. Then, a unique dynamic penalty mechanism is utilised to enhance the ADMM’s convergence speed by reducing the number of communication rounds among agents. The feasibility and profitability of the proposed EMF are systematically compared on multiple fronts against traditionally established frameworks. The simulations are carried out on the MATLAB programming platform and the Gurobi optimisation solver, utilising a real port’s modified operational data. The obtained results have shown that the proposed decentralised multi-agent LEM model can clear the market with outcomes closely comparable to those of the centralised LEM model, and this is achieved through a fair utilisation of the internal distributed resources without sharing the agents’ confidential information. Further, the heuristically varying dynamic penalty has reduced the iteration count to 510 (190 s), compared to 1800 iterations (1110 s) in conventional EMF, which increases difficulty for an attacker in obtaining confidential information. Therefore, the proposed EMF can be considered (1) beneficial for the management of the port’s DERs and (2) secure against any short-term cyber attacks.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101978"},"PeriodicalIF":5.6,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121138","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smart energy supply scheduling for green remote telecom with data-driven deep reinforcement learning","authors":"Shaohui Ma,&nbsp;Yu Pan","doi":"10.1016/j.segan.2025.101974","DOIUrl":"10.1016/j.segan.2025.101974","url":null,"abstract":"<div><div>The backbone of modern mobile communication networks is comprised of wireless telecom base stations, which serve vital functions. A significant challenge arises in remote or underdeveloped regions where power supply to these base stations is often unreliable or entirely absent. Integrated energy systems, combining solar, wind, diesel generators, and the electrical grid, present a promising solution. Effective and intelligent scheduling of these systems is paramount for ensuring uninterrupted base station operation, maximizing the integration of renewable energy, and lowering overall energy expenses. The inherent dual uncertainty of energy demand and supply poses a primary obstacle to intelligent scheduling. This research proposes a robust energy scheduling modeling framework for integrated energy systems, grounded in empirical risk minimization (ERM), forecasting methodologies, and deep reinforcement learning (DRL). This framework strategically coordinates the activation of various energy sources – grid, solar, diesel generators, and battery storage – to meet fluctuating base station power demands. By seamlessly blending predictive control with DRL, utilizing rolling forecasts as system state indicators, and employing the proximal policy optimization (PPO) algorithm for training, the proposed model demonstrably surpasses traditional predictive control and rule-based methods in both renewable energy utilization efficiency and total energy cost, as evidenced by real-world data from remote telecom base stations.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101974"},"PeriodicalIF":5.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"When smart charging meets smart users: How price-sensitive plug-in behavior reshapes EV integration","authors":"Fabian Brockmann ,&nbsp;Rieke S. Kohn ,&nbsp;Mattia Marinelli","doi":"10.1016/j.segan.2025.101977","DOIUrl":"10.1016/j.segan.2025.101977","url":null,"abstract":"<div><div>The rapid adoption of electric vehicles (EVs) presents both opportunities and challenges for energy systems. While smart charging algorithms have been widely studied to optimize EV charging schedules, the role of EV users' plug-in behavior that precedes any smart charging remains largely unexplored. This study addresses this critical gap by approximating the human plug-in decision-making process through an agent-based simulation model, capturing how EV users adjust their plug-in behavior in response to status of charge and dynamic electricity prices. Furthermore, we evaluate the impact of plug-in behavior on EV users' charging cost, battery lifetime, and EV fleet peak power demand. Our numerical analysis reveals that a price-sensitive plug-in behavior can substantially decrease charging cost and generally extend battery lifetime, though some users may experience shorter battery lifespans due to deeper discharge cycles. Moreover, this behavior also leads to synchronized charging patterns, increasing peak power demand, and potentially straining grid infrastructure. These findings reveal the trade-off between user benefits and grid operation drawbacks, underscoring the need for holistic approaches in the assessment of EV user behavior. Furthermore, our study highlights the importance of user engagement in smart charging technologies.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101977"},"PeriodicalIF":5.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cable pooling to add renewables amid grid congestion: Exploring optimal integration of solar and batteries with existing onshore wind under cost uncertainty","authors":"Emiel van Druten ,&nbsp;Seth van Wieringen","doi":"10.1016/j.segan.2025.101971","DOIUrl":"10.1016/j.segan.2025.101971","url":null,"abstract":"<div><div>Grid congestion caused by the swift expansion of wind and solar photovoltaics (PV) installations obstructs additional renewable integration. This study investigates cable pooling, a mechanism where multiple energy assets share a single grid connection, as a potential solution. A case study was conducted to model the integration of solar PV and batteries with an existing 10 MW wind farm and 10 MW grid connection. The design and dispatch were optimized for maximal profit, while exploring the implications of cost uncertainty and future cost reductions for solar PV and batteries. The findings indicate that cable pooling can significantly increase renewable electricity output from a single grid connection. The integration of solely solar PV results in an optimal capacity of 19 MWp, with 9 % of production curtailed. Integrating a 43 MWh, 7 MW battery (with a 6-hour duration) facilitates the storage of otherwise curtailed energy, increases the optimal solar PV deployment to 28 MWp, and reduces curtailment to 7 %. Batteries convert the project from weather-dependent to semi-dispatchable, enabling charging during high wind and/or solar production and discharging when hourly electricity prices are high. Anticipated cost reductions for solar PV and batteries further strengthen the economic rationale, facilitating increased deployment of these technologies.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101971"},"PeriodicalIF":5.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145121131","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An electric vehicle charging demand prediction approach based on a Graph-based Spatio-temporal Attention Network","authors":"Dong Jiang ,&nbsp;Xiaoqiang Gong ,&nbsp;Yanyan Wei ,&nbsp;Bo Peng ,&nbsp;Zhengsong Xu","doi":"10.1016/j.segan.2025.101975","DOIUrl":"10.1016/j.segan.2025.101975","url":null,"abstract":"<div><div>The accelerated adoption of electric vehicles (EVs) is fundamentally reshaping urban transportation and energy systems. However, the growing charging demand creates significant stress on urban power grids, particularly during peak hours in megacities like Shenzhen. Accurate short-term prediction of charging demand is crucial for optimizing infrastructure layout, maintaining grid stability, and supporting data-driven energy policies for sustainable urban development. This study proposes a novel Graph-based Spatio-Temporal Attention Network (G-STAN) that integrates graph convolutional networks and attention mechanisms to address the dynamic spatio-temporal characteristics of EV charging demand. The model employs a Residual Temporal Convolution Network (Res-TCN) to capture short-term load fluctuations, a Simple Graph Convolution Attention (Sim-GCA) module to model spatial interactions across 247 traffic zones, and a Temporal Pattern Attention (TPA) module to focus on peak hours and key functional areas. Evaluated on a real-world citywide charging dataset, G-STAN outperforms existing models by improving RMSE, MAE, and MAPE by 21.92 %, 36.96 %, and 16.92 %, respectively. With a lightweight design and multimodal input integration, the proposed framework enables efficient, scalable, and policy-responsive forecasting. This study proposes a novel prediction paradigm that not only significantly improves the prediction accuracy compared to state-of-the-art models, but also enhances model interpretability, scalability, and responsiveness to policy signals. It provides an actionable framework for real-time intelligent regulation of EV charging behaviors, supporting the synergy between urban energy management and sustainability goals in smart city ecosystems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101975"},"PeriodicalIF":5.6,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimal operation and revamping of a battery storage integrated with photovoltaic in renewable energy communities: A dynamic programming approach","authors":"Asja Alic ,&nbsp;Alessandra Spada ,&nbsp;Silvia Zordan ,&nbsp;Antonio De Paola ,&nbsp;Vincenzo Trovato","doi":"10.1016/j.segan.2025.101976","DOIUrl":"10.1016/j.segan.2025.101976","url":null,"abstract":"<div><div>This paper presents a novel Dynamic Programming algorithm designed to optimize the operation of an Integrated-Photovoltaic Battery Storage System arbitraging in the Wholesale Energy Market and participating in the Capacity Market. The optimization takes into account the energy capacity degradation of the battery and envisages the possibility of revamping actions to replace battery cells and ensure delivery of the discharge capacity contracted in the Capacity Market over the whole optimization horizon. The correctness of the proposed model is validated against an existing Mixed-Integer Linear Programming solution. The model is then further extended to simulate the operation of the Integrated Photovoltaic Battery System within a Renewable Energy Community, offering useful insights about the techno-economic advantages of fostering the local self-consumption. A comprehensive set of case studies has been conducted over a 10-years planning horizon with hourly granularity, considering the Italian energy markets and the applicable regulatory framework. Additional sensitivity studies expand the results by assessing the impact of different input parameters, geographical locations and number of participating members of the Renewable Energy Community.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101976"},"PeriodicalIF":5.6,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Affine optimization method for probability interval power flow of distribution network based on holomorphic embedding","authors":"Liao Xiaobing ,&nbsp;Wei Hanqi ,&nbsp;Li Zicheng ,&nbsp;Zhang Yiming ,&nbsp;Yang Jie ,&nbsp;Yang Meng","doi":"10.1016/j.segan.2025.101972","DOIUrl":"10.1016/j.segan.2025.101972","url":null,"abstract":"<div><div>With the large-scale integration of renewable energy into distribution networks, the impact of uncertainty on power systems is becoming increasingly significant. Addressing uncertainty in power flow calculations is critical for analyzing how the integration of distributed energy resources such as photovoltaic and wind power affects power flow distribution in distribution networks. This paper proposes an affine optimization method for probability interval power flow of distribution network based on holomorphic embedding. First, the affine model of system bus voltage and power is established, and an embedding factor introduced to construct the holomorphic embedding affine optimization power flow model. The focal element model of distributed photovoltaic output is established, transforming the probabilistic interval power flow model based on the focal element model into the holomorphic embedding affine optimization power flow model. The hybrid box-ellipsoid set correlation model for interval variables is established to describe distributed photovoltaic output correlation; this model is converted into affine constraints for joint solution within the holomorphic embedding affine optimization power flow model. Finally, the probabilistic boundaries of the distribution network probabilistic interval power flow solution are obtained based on evidence theory. Simulation results demonstrate the holomorphic embedding affine optimization power flow algorithm exhibits lower conservatism than the Taylor expansion affine power flow algorithm, making it more suitable for uncertain power flow analysis in larger fluctuation intervals. Simultaneously, the hybrid box-ellipsoid set correlation model achieves higher accuracy than other models and effectively reflects the influence of correlation coefficients on the calculation results.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101972"},"PeriodicalIF":5.6,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Synergistic operation of multi-resource networks through the mutual interaction of carbon and green certificates","authors":"Xu Li,&nbsp;Jianhua Deng,&nbsp;Jichun Liu","doi":"10.1016/j.segan.2025.101962","DOIUrl":"10.1016/j.segan.2025.101962","url":null,"abstract":"<div><div>Against the backdrop of China’s \"dual carbon\" strategy, this study proposes measures to facilitate the coupling, scheduling and transaction of energy, carbon and green certificates at the policy and technical levels, respectively. At the policy level, the second interaction channel for carbon and green certificates is opened based on the character of carbon quotas promoting green certificate issuance. It can promote the fair development and deep coupling of carbon quota transactions and green certificate transactions. Subsequently, a complete linkage system for energy-carbon-green certificates is constructed based on this interaction foundation. At the technical level, integrated pricing models for energy-carbon-green certificates are proposed considering carbon emission intensity and transaction intensity, providing a unified price guidance signal for coupled market transactions. Finally, five schemes are proposed to validate the effectiveness of the proposed technical approaches in facilitating the coupling of multi-resource networks, reducing carbon emissions and enhancing transaction vitality.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101962"},"PeriodicalIF":5.6,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A modular approach to handle asynchronous heterogeneous measurements in distribution system state estimation","authors":"Himani Mattoo ,&nbsp;Dnyaneshwar H. Patale ,&nbsp;Krupa Ananda Reddy Medapati ,&nbsp;J.G. Sreenath ,&nbsp;Praveen Tripathy","doi":"10.1016/j.segan.2025.101967","DOIUrl":"10.1016/j.segan.2025.101967","url":null,"abstract":"<div><div>State estimation in power systems is a fundamental task, and the state estimator has become an essential component in power system monitoring, even at the distribution level. Due to the limited number of measurement devices in the system, the available number of measurements is quite low. To address this issue and make real-time state estimation feasible and less complex at the distribution level, measurements from various types of sensors, such as micro-phasor measurement units (<span><math><mi>μ</mi></math></span>PMUs), remote terminal units (RTUs), and smart meters (SMs), need to be utilized. However, the measurements received from these different types of devices are asynchronous, meaning they are not synchronized to a central clock. In this paper, a modular two-level state estimation algorithm is proposed, which processes hybrid measurements from <span><math><mi>μ</mi></math></span>PMUs, RTUs, and SMs, taking into account the asynchronous nature of the measurements. Additionally, the developed algorithm considers the different refresh rates of these measurement devices when combining the measurements to evaluate the states of the system. The effectiveness of the algorithm is then verified using the IEEE 33-bus and 123-bus systems.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101967"},"PeriodicalIF":5.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145059893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A blockchain-enabled framework for secure synchronization and resilient energy distribution in networked microgrids against false data attacks","authors":"Kunal Kumar ,&nbsp;Prince Kumar ,&nbsp;Susmita Kar","doi":"10.1016/j.segan.2025.101880","DOIUrl":"10.1016/j.segan.2025.101880","url":null,"abstract":"<div><div>To enhance grid flexibility, resilience, and distributed energy coordination, Networked Microgrids (NMGs) have emerged as a scalable alternative to traditional centralized systems. However, their reliance on real-time synchronization of voltage magnitude, frequency, and phase angle across Points of Common Coupling (PCCs) exposes them to significant cybersecurity risks particularly False Data Injection Attacks (FDIAs). This paper proposes a blockchain-integrated detection framework designed to address synchronization-targeted FDIAs using synchronized µPMU measurements from both ends of each PCC. These measurements are securely logged on a blockchain, where a smart contract evaluates three differential change metrics: Differential Change in Voltage Magnitude (DCVM), Differential Change in Phase Angle (DCPA), and Differential Change in Frequency (DCF). An OR-based detection logic flags any block as compromised if thresholds are exceeded, ensuring real-time identification of FDIA events. The framework is validated through comprehensive MATLAB Simulink simulations that consider both cyber-attacks and NMG operational disturbances, along with smart contract implementation in Ethereum Remix IDE. The obtained results demonstrate strong differentiation between cyber-attacks and typical operational events. Statistical analysis and ROC curve evaluation yield an Area Under the Curve (AUC) of 0.96, confirming the framework’s robustness, low false-positive rate, and practical feasibility for securing synchronization in NMG environments.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"44 ","pages":"Article 101880"},"PeriodicalIF":5.6,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145099865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}