{"title":"Multi-objective optimization method for power supply and demand balance in new power systems","authors":"","doi":"10.1016/j.ijepes.2024.110204","DOIUrl":"10.1016/j.ijepes.2024.110204","url":null,"abstract":"<div><p>The large amount of source and load uncertainty in new power systems poses challenges to the optimization of power supply and demand balance. The traditional optimization methods have not fully considered the uncertainty characteristics of different sources and loads. In this regard, a supply–demand balance optimization method based on ISAO-BiTCN-BiGRU-SA-IPBLS is proposed. Firstly, the ISAO algorithm is introduced into the hyperparameter optimization of BiTCN-BiGRU-SA, and the source and load interval prediction method based on LINMAP selection is proposed. Afterwards, a multi-objective optimization method for power supply and demand balance based on two-stage robust optimization is proposed. The first stage takes the daily planned output of adjustable power sources as the optimization variable, with daily operating cost, renewable energy delivery rate, and maximum loss in extreme scenarios as the optimization objectives. The second stage takes the daily operation of energy storage as the optimization variable and minimizes the maximum loss in the extreme scenario as the optimization objective. Finally, the method is applied to the county-level new power system in Hunan Province, China. The results show that the MAPE of the load and PV point prediction results in this work decreases by 13.43 % and 16.93 % after introducing the ISAO, respectively. Compared with the traditional Gaussian method, the Euclidean distance of error indicators between the load/PV interval prediction results in this work and the ideal results at an 85 % confidence interval decreases by 53.19 %/100 %. Compared with the traditional optimization method only considering economy, the work’s method improves the renewable energy delivery rate by 0.10 and 0.02 respectively, and reduces the maximum loss in extreme scenarios by 76.75 % and 3.62 % respectively on the maximum load day and maximum renewable energy output day.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004253/pdfft?md5=dfc6527c9b209a5a79f1b14f9cc15bac&pid=1-s2.0-S0142061524004253-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A decomposition-based approach to European electricity market clearing","authors":"","doi":"10.1016/j.ijepes.2024.110192","DOIUrl":"10.1016/j.ijepes.2024.110192","url":null,"abstract":"<div><p>This work proposes a methodology to calculate the price of the single pan-European day-ahead electricity market through an iterative process between the markets of two zones: the Iberian Peninsula and the rest of Europe. The motivation for this decomposition-based market clearing procedure is twofold: on the one hand, the two zones considered are weakly connected, due to the peninsular nature of Iberia, electrically connected to the rest of Europe only through the few tie-lines between Spain and France; on the other hand, the types of bids and related constraints are quite heterogeneous in both areas. The proposed algorithm has shown to provide virtually the same results as the official EU Pan-European Hybrid Electricity Market Integration Algorithm (EUPHEMIA), while improving convergence rates and often reducing solution times. The aim is not to replace EUPHEMIA, but rather to provide a more robust alternative that can be run in parallel, capable of providing a solution in cases of difficult convergence caused by the interactions of the complex constraints arising in the markets involved.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004137/pdfft?md5=312887327e28d2c18fac90963fbf450f&pid=1-s2.0-S0142061524004137-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiport converter evaluation for high penetration of renewable generation in distribution grids","authors":"","doi":"10.1016/j.ijepes.2024.110211","DOIUrl":"10.1016/j.ijepes.2024.110211","url":null,"abstract":"<div><p>Electrical power distribution systems are experiencing a deep penetration of renewable energy integration, which is reversing the power flow during some periods and modifying their conventional operation. In this context, the curtailment of renewable distributed generation is needed to consider the electrical limitations of transformers and lines, mainly voltage deviations and power overloads. Multiport converters with energy storage stand as a potential solution for enhancing power flow operation in the distribution system and minimising renewable generation curtailments. This paper presents an optimisation-based methodology to size multiport power converters and a techno-economic comparison to other conventional approaches. The optimisation includes energy storage components and AC power flow constraints. Moreover, specific days are considered to reduce computational requirements. This methodology is evaluated in a case study based on a medium voltage benchmark network from CIGRE to identify the best scenarios where multiport converters can be considered as a potential solution. Results conclude that the multiport converter provides clear advantages and is economically viable specially in scenarios with unbalanced distributed generation in the feeders, where their rated power is around 25 MVA, or if batteries are initially installed in the feeders.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004320/pdfft?md5=6134e3e592ac9cfb8660f67406aa8b9d&pid=1-s2.0-S0142061524004320-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148890","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Research on the dynamic energy conversion and transmission model of renewable energy DC off-grid hydrogen system","authors":"","doi":"10.1016/j.ijepes.2024.110221","DOIUrl":"10.1016/j.ijepes.2024.110221","url":null,"abstract":"<div><p>The dynamic response characteristics between the multiple energy flows of electricity-hydrogen-heat in the renewable energy DC off-grid hydrogen production system are highly coupled and nonlinear, which leads to the complexity of its energy conversion and transmission law. This study proposes a model to describe the dynamic nonlinear energy conversion and transmission laws specific to such systems. The model develops a nonlinear admittance framework and a conversion characteristic matrix for multi-heterogeneous energy flow subsystems, based on the operational characteristics of each subsystem within the DC off-grid hydrogen production system. Building upon this foundation, an energy hub model for the hydrogen production system is established, yielding the electrical, thermal, and hydrogen energy outputs along with their respective conversion efficiencies for each subsystem. By discretizing time, the energy flow at each time node within the hydrogen production system is computed, revealing the system’s dynamic energy transfer patterns. Experiments were conducted using measured wind speed and irradiance data from a specific location in eastern China. Results from selected typical days were analyzed and discussed, revealing that subsystem characteristics exhibit nonlinear variation patterns. This highlights the limitations of traditional models in accurately capturing these dynamics. Finally, a simulation platform incorporating practical control methods was constructed to validate the model’s accuracy. Validation results demonstrate that the model possesses high accuracy, providing a solid theoretical foundation for further in-depth analysis of DC off-grid hydrogen production systems.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004423/pdfft?md5=5769f1dac9ba8d3ddd7821788f039439&pid=1-s2.0-S0142061524004423-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142148889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Hybrid Spatio-Temporal scale decentralized restoration strategy for interdependent electricity and gas systems to enhance restoration efficiency and security","authors":"","doi":"10.1016/j.ijepes.2024.110214","DOIUrl":"10.1016/j.ijepes.2024.110214","url":null,"abstract":"<div><p>The ever-increasing couplings between electricity and gas systems highlight the coordinated restoration decisions for interdependent electricity and gas system (IEGS) to enhance resilience. However, the distinct timescales of power and gas flow rates as well as information privacy concern cause additional complexities in making restoration decisions, and large calculation scale and nonconvexity also results in computational obstacles. To address these issues, this paper proposes a hybrid spatio-temporal scale decentralized restoration strategy for IEGS to enhance restoration efficiency and security. First, in the spatial scale, the network sectionalizing and the restoration processes in sectionalized electricity and gas systems are coordinated in a decentralized manner with limited boundary information interactions to respect information privacy. Next, the impacts of distinct timescales of power and gas flow rates are explored to accelerate restoration, and a linear gas flow dynamics model is also proposed to capture the gas transmission dynamics with high accuracy, enhancing restoration security. Furthermore, a decomposition-based alternating direction method of multipliers algorithm is proposed to efficiently solve the proposed IEGS restoration strategy, showing good calculation time and convergence performance. Finally, the effectiveness of the proposed restoration strategy is validated in a T118N20 test system and a real-world system, demonstrating the enhanced restoration efficiency, security alongside commendable computational performance.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004356/pdfft?md5=862144327f15c23cbd5ea53ae99b3157&pid=1-s2.0-S0142061524004356-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142149516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Internal clock errors in synchrophasor ambient data: Effects, detection, and a posteriori estimation-based correction","authors":"","doi":"10.1016/j.ijepes.2024.110208","DOIUrl":"10.1016/j.ijepes.2024.110208","url":null,"abstract":"<div><p>Synchrophasor data from real world power systems are exposed to numerous adverse cyber-and-physical operating conditions that can negatively impact their fitness for use in PMU applications. Although the most significant impairments such as GPS loss, instrument transformer failure, data drop-off, etc., have been studied in the literature, there exist other more complex nuisances that impact PMU data quality. This is the case of differences in how clock synchronization, time disciplining, and phasor estimation is performed by different PMU vendors, which have important implications on the PMUs’ data fitness for use in PMU applications. In particular, ambient data applications, which have increasingly become a focus for tracking grid performance indicators, are extremely sensitive to periodic clock errors. Using synchrophasor and waveform data from Dominion Energy’s power system, this article provides an in-depth analysis of the effect of seemingly minor device clock errors on the measurement signals’ content. Finally, a method to distinguish clock errors from normal system dynamics and to correct them is proposed.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004290/pdfft?md5=2286360e28800786f5abc3eae2352060&pid=1-s2.0-S0142061524004290-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sand cat swarm optimization based maximum power point tracking technique for photovoltaic system under partial shading conditions","authors":"","doi":"10.1016/j.ijepes.2024.110203","DOIUrl":"10.1016/j.ijepes.2024.110203","url":null,"abstract":"<div><p>Maximum power point tracking (MPPT) plays a crucial role in photovoltaic systems (PVS). In partial shading conditions (PSCs), the P-V characteristic curves of PVS exhibit multiple peaks. Traditional MPPT algorithms, like perturbation and observation (P&O), may fall into local maximum power points (LMPP) and fail to identify the global maximum power point (GMPP). To address the drawbacks of conventional optimal search algorithms, this paper introduces a bio-inspired approach named Sand Cat Swarm Optimization (SCSO) for maximizing the power output of individual PVS. The SCSO can mitigate the adverse effects of partial shadows on PVS performance by precisely identifying the GMPP. In comparison to other bio-inspired algorithms, SCSO exhibits lower complexity and higher efficiency by utilizing only one optimization parameter. SCSO’s performance is evaluated in four scenarios: uniform irradiance, complex partial shading conditions, step-varying stochastic irradiance, and gradual irradiance. A comparative analysis is conducted with Particle Swarm Optimization (PSO), Cuckoo Search Algorithm (CSA), Grey Wolf Optimization (GWO), Whale Optimization Algorithm (WOA), Moth-Flame Optimization (MFO), Crow Search Algorithm (CSA), Slap-Swarm Optimization (SSA) and P&O, focusing on factors such as high efficiency, accuracy, convergence time, and implementation simplicity. Simulation results demonstrate that, on average, the tracking time improves by 19.91%, achieving an efficiency of over 98% while maximizing energy yield. Simultaneously, experimental results indicate that the SCSO is capable of tracking to a larger power output in a shorter time, with an average tracking efficiency improvement of 3.16%.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004241/pdfft?md5=9ec01bfb0eead5132542c3a691c8a706&pid=1-s2.0-S0142061524004241-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137231","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A security-aware dynamic hosting capacity approach to enhance the integration of renewable generation in distribution networks","authors":"","doi":"10.1016/j.ijepes.2024.110210","DOIUrl":"10.1016/j.ijepes.2024.110210","url":null,"abstract":"<div><p>Hosting capacity (HC) describes the electricity network’s ability to accommodate distributed generation (DG) without deteriorating electrical performance indicators. Distribution system operators typically express their networks’ HC as a single threshold, called static hosting capacity (SHC). SHC is determined via conservative regulatory criteria, increasing connection costs and time. This paper explores the potential for additional energy injection into the network via dynamic hosting capacity (DHC). A network node’s DHC is derived from the hourly operation of the network, accounting for the time variability of existing distributed generation (DG) output and demand. The methodology considers the network assets’ N-1 contingencies and their probabilities, defining the security-aware DHC (SDHC). The SDHC definition is technologically neutral. Through a case study of a radial medium voltage distribution network, the paper highlights the significant limitations of SHC due to conservative calculation criteria mandated by regulators. Annual injectable energy is increased by 62% to 76% when comparing DHC to SHC. Variations between average DHC and SDHC are below 0.01% due to low N-1 probabilities. This finding points out the potential of dynamic hosting capacity definitions, allowing more efficient use of the existing network and facilitating the integration of new DG capacity with reduced connection costs and time.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004319/pdfft?md5=67017ef80cd29d00ee513427c5d8585b&pid=1-s2.0-S0142061524004319-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142137230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Time-of-use (TOU) electricity rate for vehicle-to-grid (V2G) to minimize a charging station capacity","authors":"","doi":"10.1016/j.ijepes.2024.110209","DOIUrl":"10.1016/j.ijepes.2024.110209","url":null,"abstract":"<div><p>This paper introduces a framework to yield an electricity rate for vehicle-to-grid (V2G) charging station (CS) to minimize installation capacity of a charging station considering electric vehicle (EV) arrival/departure time distribution. Two different layers are designed to avoid an obstacle encountered when formulating the problem as a convex optimization and to represent an EV aggregator and an electricity rate decision maker – a regulator. The EV aggregator layer focuses on increasing the profit and the regulator minimizes the peak load of the V2G CS. Linear programming was formulated for the former layer, and a modified particle swarm optimization (PSO) method was developed for the latter. Modification of the PSO approach allowed for easier escape of local minima, resulting in a new electricity rate for the V2G CS based on the EV arrival/departure time distribution data. The algorithm employs new matrices devised in this paper to accommodate EV information in the optimization process. In a simulation study, two distinct CSs with V2G operations were evaluated, each with a different EV arrival/departure time distribution. The simulation revealed that the peak load and the profit of the aggregator vary dramatically depending on the arrival/departure time distributions.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004307/pdfft?md5=f2dcc17718c6c2c53535fe449669d0b8&pid=1-s2.0-S0142061524004307-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122331","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Augmenting time series data: An interpretable approach with metric learning and variational autoencoders","authors":"","doi":"10.1016/j.ijepes.2024.110190","DOIUrl":"10.1016/j.ijepes.2024.110190","url":null,"abstract":"<div><p>In the field of time series classification, deep learning techniques have shown remarkable performance; however, their effectiveness is often compromised when confronted with challenges of insufficient data and class imbalance. To address this challenge, we propose an interpretable time series data augmentation algorithm integrating variational autoencoders (VAE) and metric learning. The core contribution of this algorithm is manifested in three aspects: First, it eliminates the heteroscedasticity and non-stationarity of the data, ensuring that the data satisfies the hypothesis of normal distribution in the potential space of the encoder, and effectively avoids the approximation error of the real data distribution; Secondly, the algorithm constructs a discriminant VAE potential space, suitable for data augmentation, with metric learning, ensuring that the hidden variable distribution accurately reflects the characteristics of the original data. Finally, this paper explores the multi-seasonal decomposition algorithm of time series to seamlessly integrate the structural features of the original time series in the generated data, thereby enhancing the interpretability of data generation. Through experimental verification on four multivariate time series data sets, including the electrical energy data set, the results demonstrate that the proposed algorithm outperforms existing methods in fidelity and prediction performance, exhibiting high stability and generalization ability, particularly in cases of limited data volume. The introduction of this algorithm not only contributes to enhancing the overall performance of time series classification models but also substantially reduces the cost of data collection and labeling, thereby demonstrating its significant value in practical applications.</p></div>","PeriodicalId":50326,"journal":{"name":"International Journal of Electrical Power & Energy Systems","volume":null,"pages":null},"PeriodicalIF":5.0,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0142061524004113/pdfft?md5=bf17053ff336be46efb7fbce1a29123d&pid=1-s2.0-S0142061524004113-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142122424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}