Alexander Barajas-Ritchie, Derek Jackson, E. Cotilla-Sánchez, Yue Cao
{"title":"Open-Source Steady-State Models for Integration of Wave Energy Converter into Microgrids","authors":"Alexander Barajas-Ritchie, Derek Jackson, E. Cotilla-Sánchez, Yue Cao","doi":"10.1109/FES57669.2023.10182796","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182796","url":null,"abstract":"This paper proposes a software framework, WEC-Grid, for integrating wave energy converters (WECs) into power flow software, such as Siemens PSS®E, to aid the integration of alternative energy sources into Microgrids. While integrating alternative sources such as WECs presents specific challenges such as cost, power quality, and power variability, wave energy is a promising renewable energy resource. Evaluating the integration of WECs into the power grid is a complex and nuanced problem that requires seamless communication between a WEC model and power flow software. The presented WEC-Grid software framework bridges and extends the functionality of WEC-Sim, an open-source WEC modeling package for MATLAB, through a wave-to-wire (W2W) electro-mechanical power conversion and processing model. WEC-Grid acts as a software wrapper, handler, and communication layer between the W2W modeler and power flow software. The software is designed to represent each grid system as a class object, allowing power system operators to perform power system duties such as contingency planning and dispatch operations. The integration of WECs with PSS®E’s power flow calculations workflow is demonstrated with an IEEE RTS case study.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114966182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Busarello, Marcelo Simoes, H. Laaksonen, K. Kauhaniemi
{"title":"Simplified Control Strategies for Power Converters in a Grid-Connected Hybrid DC-AC Microgrid","authors":"T. Busarello, Marcelo Simoes, H. Laaksonen, K. Kauhaniemi","doi":"10.1109/FES57669.2023.10182409","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182409","url":null,"abstract":"Many typical converter control strategies used in microgrids are complex or require modifications in the power structure. The complexities are due coupling effects among controllers and time-delay caused in exchanging information in the system. This paper proposes simplified control strategies for power converters in a grid-connected hybrid DC-AC microgrid, aiming to ensure precise voltage and current regulation. The used controllers are proportional-resonant, integral-double-lead, proportional-integral and single integral controller. In this paper, the methodology for tuning each controller is carefully described in detail and recommendation for choosing their bandwidth is given. Then, the designed controllers are discretized through the Backward-Euler approximation. The power converters of the microgrid are an inverter, a Buck, a Boost and a bidirectional DC-DC. A case study is conducted through simulations with Matlab/Simulink. Results show that the controlled variables follow their reference signals with negligible steady-state error, proving the efficacy of the simplified control strategies and allowing an stable operation of the microgrid.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"82 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123239952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emely Cruz-De-Jesús, J. Martínez-Ramos, A. Marcolini
{"title":"Stochastic Programming Model for the Provision of Flexibility by Energy Communities","authors":"Emely Cruz-De-Jesús, J. Martínez-Ramos, A. Marcolini","doi":"10.1109/FES57669.2023.10183285","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10183285","url":null,"abstract":"This research work presents the stochastic optimization of an Energy Community that provides upward and downward reserves to the grid operator. The resources available are a community storage system, a community photovoltaic plant, flexible loads, and interruptible loads of a higher education institution. Two optimization programs are analyzed, considering the sequence of energy and reserve markets in Spain. In the first stage, there is uncertainty in energy prices, PV generation, and demand. In the second stage, energy prices are known, and stochastic optimization is performed considering uncertainty in reserve prices, demand load, and PV generation. A two-stage stochastic optimization is used in both stages. The models are developed in the mathematical optimization software GAMS. A comparison is made on the advantages of stochastic resource scheduling. The results show that the community receives greater benefits by participating in the reserve market.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125263651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hamed Mirsaeedi, Alireza Hassankashi, Mahsa Sajjadi, P. Siano
{"title":"A Mixed-Integer Linear Programming Approach to Maintenance Budgeting in Electrical Distribution Networks Considering Repair Time Uncertainty","authors":"Hamed Mirsaeedi, Alireza Hassankashi, Mahsa Sajjadi, P. Siano","doi":"10.1109/FES57669.2023.10182631","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182631","url":null,"abstract":"As a component of asset management strategies, maintenance management is essential for improving the reliability of the Electrical Distribution Networks (EDNs). To increase system efficiency, electricity companies invest a significant effort to assign their financial sources to important system components. In this paper, a mixed-integer linear programming approach to maintenance budgeting considering restoration time uncertainty is suggested. The suggested technique finds the optimal budget for doing maintenance tasks in distribution network feeders. The objective is to reduce overall cost, which includes total interruption cost of customer $left(boldsymbol{T} boldsymbol{C}_{boldsymbol{C I C}}right)$, total energy not supplied ${cost}left(T C_{E N S}right)$, total cost of materials and labor for repair $left(T C_{R E P}right)$, and total cost of maintenance $left(T C_{P M}right)$. Three cases are also taken into account to observe the effectiveness of the suggested maintenance method: Case I assumes that no maintenance actions are performed in the system, in Case II, maintenance budget for each distribution feeder is taken into consideration equally, in Case III, according to constraints, the suggested formulation allocates the optimal maintenance budget. The Roy Billinton test system’s bus number two (RBTS2) is subjected to the proposed reliability improvement approaches, and the results are discussed.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129844932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vahid Shahbazbegian, Hamid Hosseininesaz, M. Shafie‐khah, M. Elmusrati
{"title":"Forecasting Crude Oil Prices using a Hybrid Model Combining Long Short-Term Memory Neural Networks and Markov Switching Model","authors":"Vahid Shahbazbegian, Hamid Hosseininesaz, M. Shafie‐khah, M. Elmusrati","doi":"10.1109/FES57669.2023.10182444","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182444","url":null,"abstract":"Given the significant impact of crude oil prices on the global economy, accurately predicting their fluctuations is essential for effective decision-making in the energy sector. Therefore, this research aims to develop a hybrid model that can comprehensively capture the nonlinear and volatile characteristics of crude oil prices and provide accurate predictions. The proposed approach involves segmenting the time series into multiple sub-series, which capture the nonlinear and volatile characteristics of crude oil prices. The nonlinear sub-series is predicted using Long Short-Term Memory neural networks, while the volatile and fluctuating sub-series are forecasted using a Markov Switching model. The results of these predictions are combined using a linear combination to estimate the crude oil price time series. The proposed hybrid model provides a comprehensive understanding of the various factors that drive crude oil price fluctuations, making it a valuable tool for decision-making in the energy sector.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128414395","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Safe Reinforcement Learning-Based Control in Power Electronic Systems","authors":"Daniel Weber, Maximilian Schenke, O. Wallscheid","doi":"10.1109/FES57669.2023.10182718","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182718","url":null,"abstract":"Data-driven approaches such as reinforcement learning (RL) allow a controller design without a priori system knowledge with minimal human effort as well as seamless self-adaptation to varying system characteristics. However, RL does not inherently consider input and state constraints, i.e., satisfying safety-relevant system limits during training and test. This is challenging in power electronic systems where it is necessary to avoid overcurrents and overvoltages. To overcome this issue, a standard RL algorithm is extended by a combination of constrained optimal control and online model identification to ensure safety during and after the learning process. In an exemplary three-level voltage source inverter for islanded electrical power grid application, it is shown that the approach does not only significantly improves safety but also improves the overall learning-based control performance.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129536755","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Timon Benz, Aline Kirsten Vidal de Oliveira, M. Aghaei, M. Rehm, R. Rüther
{"title":"Extracting Cell Images from Ultraviolet Fluorescence Images of Photovoltaic Modules","authors":"Timon Benz, Aline Kirsten Vidal de Oliveira, M. Aghaei, M. Rehm, R. Rüther","doi":"10.1109/FES57669.2023.10182797","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182797","url":null,"abstract":"With the expanse of large-scale photovoltaic power plants, the need for automatized and cost-effective inspection methods keeps increasing. Aerial PV inspection using drones and optical methods has become very popular. Ultraviolet Fluorescence (UVF) is an effective inspection technique that detects faults on the encapsulant of the PV cell. The encapsulant is a polymer material called Ethylene-Vinyl Acetate (EVA). The ageing of the PV module/cell, notably oxygen and humidity entering can create fluorescence in the encapsulant. The fluorescence pattern can indicate both the ageing process and encapsulant defects. In this paper, a low-cost experimental setup was used to acquire UVF images in the state of Santa Catarina, Southern Brazil. An automatized image-processing pipeline has been developed using contour detection, perspective correction and cropping of module and cell images. In the future, databases of UVF cell images can be created and used to for Deep Learning applications for automatized fault detection.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129117638","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yuchen Duan, Quan Chen, Qian Zhang, Changbao Zheng, Qile Zheng, Long Cheng
{"title":"Identification and Prevention of Collusion among Power Producers in Power Market Based on Decision Tree","authors":"Yuchen Duan, Quan Chen, Qian Zhang, Changbao Zheng, Qile Zheng, Long Cheng","doi":"10.1109/FES57669.2023.10183256","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10183256","url":null,"abstract":"The oligopoly nature of the power market leads to the existence of tacit collusion among power producers. The problem of collusion has seriously affected the fairness, competitiveness and effectiveness of the market. For this kind of problem, most predecessors have carried out theoretical research and put forward the causes of collusion and some prevention methods. However, tacit collusion is highly hidden and can be realized in many forms, which is difficult to judge and identify. Starting from the data, this paper finds out the power producers who may have collusion through mathematical methods, and then strictly “takes care of” such power producers. In the new energy power market, it is found that the collusion problem still exists in the new energy power market through modeling and analysis, and the collusion behavior of power producers in the power market is screened through the decision tree classification algorithm, The decision tree algorithm has a very obvious effect on the collusion analysis of power producers in the power market. Finally, some suggestions on the prevention of collusion are put forward.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121064042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analyzing the TVS Influenced by IOSS to Assess the Power Load Buses in Power Systems","authors":"Luu Huu Vinh Quang","doi":"10.1109/FES57669.2023.10182374","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182374","url":null,"abstract":"This paper proposes a new algorithm for analyzing the initial optimal steady-state (IOSS) with the optimal power flows (OPF) influencing the transient voltage stability (TVS) to assess the power load buses related to short circuit failure occurring in multi-machine power system operations. We propose a new formula as a new criterion to evaluate the TVS’ estimation of large power load buses involved in the severe disturbances occurring in multi-machine power systems. We compare the transient voltage stability estimation values according to the initial state with those according to the optimized state in daily power system operations for assessing and ranking the power load buses in multi-machine power systems. In this article, we simulate the transient voltage stability estimation’s value under the influence of the power network’s nonlinearity caused by the angular frequency changing in time under the actions of the automatic frequency regulation (AFR) and the automatic voltage regulation (AVR). The nonlinear programming method is applied with the Newton iteration technique to optimize the power output levels of the hydroelectric and thermoelectric generators for simulating the IOSS in daily power system operations. The typical numerical examples and results shown prove the advantages of the new proposed algorithm with new criteria evaluating the transient voltage stability.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121390984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Collective Citizen Energy Investment Models for Solar Power: Case Study Croatia","authors":"L. Herenčić, T. Capuder, M. Kıraç, Goran Cacic","doi":"10.1109/FES57669.2023.10182991","DOIUrl":"https://doi.org/10.1109/FES57669.2023.10182991","url":null,"abstract":"Cost-competitiveness of decentralized renewable energy sources (RESs) has opened opportunities for citizens’ ownership of RES and for the development of new business models. Citizen energy investment models based on cooperative principles have gained increased attention lately due to promises to support local economic welfare, boost local economy, increase social cohesion, help in grid optimization, and increase citizens’ support for new RES projects. In this paper, we provide an overview of collective citizen energy investment concepts and describe the six types of models being developed in Croatia. We provide an overview of the initiatives together with the challenges, threats, and opportunities found when concepts are faced with the real-life practice in Croatia. We show that even though citizens’ ownership of RES (mainly individual solar PV systems) is strongly increasing, the current developments of collective (group) citizen energy investment models are predominantly related to sporadic research projects and enthusiasts’ initiatives, meaning still no wider-scope investments in RES have been conducted this way. Following the findings, we provide recommendations for removing the barriers and speeding up the development of such projects in the future.","PeriodicalId":165790,"journal":{"name":"2023 International Conference on Future Energy Solutions (FES)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133082673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}