Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102742
Conner Ozatalar, R. Ahmad, Phillip Pambuh, Harshil Shah
As more behind the meter solar farms are installed onto the power grid, the true load on the power grid becomes more hidden to the utility because the meters only read the net difference between the native load and the solar generation. This becomes problematic for grid planning since the grid needs to be ready to handle the full native load in the case of a hot and cloudy summer day when load is very high and solar generation is low. This study breaks down solar irradiance into the diffuse components from the ground and sky, and the direct (beam) irradiance. These components are then combined using the Liu-Jordan model to estimate the solar irradiance on a tilted surface. This method was then applied to data from a weather station in an area in ComEd’s service territory to estimate the solar panel output of a local 2MW metered solar farm. When comparing the predicted generation and measured generation from this solar farm, it was determined that their existed inconsistencies within the data set. After reducing the size of the data set to remove potentially poor data, this method estimated solar production with an R2 value of 0.900 with an average absolute value error of 148kW. Based on these findings, this methodology had produced efficient results and can also be used to determine when a solar farm is not producing as expected.
{"title":"Estimating the Output of Behind the Meter Solar Farms by Breaking Irradiance Data into its Diffuse and Direct Components","authors":"Conner Ozatalar, R. Ahmad, Phillip Pambuh, Harshil Shah","doi":"10.1109/GridEdge54130.2023.10102742","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102742","url":null,"abstract":"As more behind the meter solar farms are installed onto the power grid, the true load on the power grid becomes more hidden to the utility because the meters only read the net difference between the native load and the solar generation. This becomes problematic for grid planning since the grid needs to be ready to handle the full native load in the case of a hot and cloudy summer day when load is very high and solar generation is low. This study breaks down solar irradiance into the diffuse components from the ground and sky, and the direct (beam) irradiance. These components are then combined using the Liu-Jordan model to estimate the solar irradiance on a tilted surface. This method was then applied to data from a weather station in an area in ComEd’s service territory to estimate the solar panel output of a local 2MW metered solar farm. When comparing the predicted generation and measured generation from this solar farm, it was determined that their existed inconsistencies within the data set. After reducing the size of the data set to remove potentially poor data, this method estimated solar production with an R2 value of 0.900 with an average absolute value error of 148kW. Based on these findings, this methodology had produced efficient results and can also be used to determine when a solar farm is not producing as expected.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"130 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115826999","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}
Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102711
Avik Ghosh, Cristian Cortes-Aguirre, Yi-An Chen, Adil Khurram, J. Kleissl
The recent increase in the intermittent variable renewable energy sources (VRES) results in mismatches between demand and supply that can cause grid instability. These issues can be mitigated with battery energy storage systems (BESS). However, BESS are generally dispatched conservatively to manage uncertainties in VRE forecast. Therefore, this paper proposes an online adaptive stochastic model predictive control (A-SMPC) based approach that minimizes electricity costs by expanding the BESS state of charge (SOC) limits beyond the nominal range of 20% – 80%. Allowing the SOC limits to expand, results in violation of the nominal SOC constraints. Chance constraints are implemented in the proposed A-SMPC method that guarantee that the probability of violating nominal SOC constraints remains below a desired value. Furthermore, the A-SMPC cost function includes time-of-use demand charges that have not been considered before in this type of model. Simulations based on historical load and PV generation data from the Port of San Diego for January 2019 shows that the proposed formulation outperforms the traditional MPC formulation, that does not include nominal SOC constraint violation, by reducing the monthly electricity costs by 7%. The proposed A-SMPC method results in 8% higher BESS utilization which translates to about 1 extra charging/discharging cycle during the analyzed month which is unlikely to have a significant impact on BESS lifetime.
{"title":"Adaptive Chance Constrained MPC under Load and PV Forecast Uncertainties","authors":"Avik Ghosh, Cristian Cortes-Aguirre, Yi-An Chen, Adil Khurram, J. Kleissl","doi":"10.1109/GridEdge54130.2023.10102711","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102711","url":null,"abstract":"The recent increase in the intermittent variable renewable energy sources (VRES) results in mismatches between demand and supply that can cause grid instability. These issues can be mitigated with battery energy storage systems (BESS). However, BESS are generally dispatched conservatively to manage uncertainties in VRE forecast. Therefore, this paper proposes an online adaptive stochastic model predictive control (A-SMPC) based approach that minimizes electricity costs by expanding the BESS state of charge (SOC) limits beyond the nominal range of 20% – 80%. Allowing the SOC limits to expand, results in violation of the nominal SOC constraints. Chance constraints are implemented in the proposed A-SMPC method that guarantee that the probability of violating nominal SOC constraints remains below a desired value. Furthermore, the A-SMPC cost function includes time-of-use demand charges that have not been considered before in this type of model. Simulations based on historical load and PV generation data from the Port of San Diego for January 2019 shows that the proposed formulation outperforms the traditional MPC formulation, that does not include nominal SOC constraint violation, by reducing the monthly electricity costs by 7%. The proposed A-SMPC method results in 8% higher BESS utilization which translates to about 1 extra charging/discharging cycle during the analyzed month which is unlikely to have a significant impact on BESS lifetime.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125184095","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}
Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102709
S. M. de Oca, P. Monzón, P. Belzarena
The electricity and transportation sectors are in a transformation process, in which both can benefit from working together. In particular, more than half of electric vehicle (EV) users have similar consumption behaviors and will use charging infrastructure at home, creating a great challenge for different stakeholders. Digital platforms allow automatic control of end devices, enabling users to be more active and committed to a sustainable system. Motivated by large-scale and online optimization approaches, we formulate a smart charging mechanism for coordinating a large population of residential EVs based on a price-responsive model. We used a stochastic subgradient method to deal with synchrony problems and communication overload. The Utility decides the energy price that maximizes its profit in a day-ahead flexibility market with available information, while the clients fulfill theirs consumption expectations.
{"title":"Incremental Subgradient Method for EVs Smart Charging Flexibility in Wholesale Energy Markets","authors":"S. M. de Oca, P. Monzón, P. Belzarena","doi":"10.1109/GridEdge54130.2023.10102709","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102709","url":null,"abstract":"The electricity and transportation sectors are in a transformation process, in which both can benefit from working together. In particular, more than half of electric vehicle (EV) users have similar consumption behaviors and will use charging infrastructure at home, creating a great challenge for different stakeholders. Digital platforms allow automatic control of end devices, enabling users to be more active and committed to a sustainable system. Motivated by large-scale and online optimization approaches, we formulate a smart charging mechanism for coordinating a large population of residential EVs based on a price-responsive model. We used a stochastic subgradient method to deal with synchrony problems and communication overload. The Utility decides the energy price that maximizes its profit in a day-ahead flexibility market with available information, while the clients fulfill theirs consumption expectations.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"392 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133189595","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}
Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102731
Alex Nassif
Non-wire alternatives are gaining acceptance in areas where traditional reliability improvement methods are of difficult adoption or not cost effective. Declining costs of energy storage systems favor the adoption of electrochemical batteries if supported by a sound value proposition. This paper presents a practical method to size battery storage systems based on minimizing the cost to the distribution system operator. The method is based on an exhaustive search and considers only practical aspects faced by electric utilities, leaving out parameters that are either not visible or impactful. The proposed approach was adopted in a real distribution network slated for reconfiguration just few years following the study, but poor reliability has favored the adoption of the storage system as an interim solution with minimum environmental impact and improved metrics.
{"title":"A Resilience-Driven Battery Energy Storage System Sizing Strategy for Grid Edge Radial Supplies","authors":"Alex Nassif","doi":"10.1109/GridEdge54130.2023.10102731","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102731","url":null,"abstract":"Non-wire alternatives are gaining acceptance in areas where traditional reliability improvement methods are of difficult adoption or not cost effective. Declining costs of energy storage systems favor the adoption of electrochemical batteries if supported by a sound value proposition. This paper presents a practical method to size battery storage systems based on minimizing the cost to the distribution system operator. The method is based on an exhaustive search and considers only practical aspects faced by electric utilities, leaving out parameters that are either not visible or impactful. The proposed approach was adopted in a real distribution network slated for reconfiguration just few years following the study, but poor reliability has favored the adoption of the storage system as an interim solution with minimum environmental impact and improved metrics.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121817093","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}
Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102721
Yushan Hou, Jing Zhu, Michael Z. Liu, W. J. Nacmanson, L. Ochoa
The widespread adoption of residential electric vehicles (EVs) will result in larger voltage drops due to the extra demand. Since most residential EV chargers are single-phase, they might also contribute to voltage unbalance which, in turn, can make voltage drop issues on certain phases worse. This paper investigates the extent to which voltage unbalance affects the EV hosting capacity of distribution networks using a Monte Carlo-based time-series analysis to capture the uncertainties of EV location, charger size, and charging behavior. Using a realistically modeled Australian MV-LV network with 1,300+ customers, results show that with increasing EV penetrations, the voltage unbalance keeps increasing too, even for 100% EV penetration. Moreover, it is demonstrated that large voltage unbalance significantly limits EV hosting capacity, suggesting the need for considering balancing strategies when possible.
{"title":"EV Hosting Capacity and Voltage Unbalance: An Australian Case Study","authors":"Yushan Hou, Jing Zhu, Michael Z. Liu, W. J. Nacmanson, L. Ochoa","doi":"10.1109/GridEdge54130.2023.10102721","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102721","url":null,"abstract":"The widespread adoption of residential electric vehicles (EVs) will result in larger voltage drops due to the extra demand. Since most residential EV chargers are single-phase, they might also contribute to voltage unbalance which, in turn, can make voltage drop issues on certain phases worse. This paper investigates the extent to which voltage unbalance affects the EV hosting capacity of distribution networks using a Monte Carlo-based time-series analysis to capture the uncertainties of EV location, charger size, and charging behavior. Using a realistically modeled Australian MV-LV network with 1,300+ customers, results show that with increasing EV penetrations, the voltage unbalance keeps increasing too, even for 100% EV penetration. Moreover, it is demonstrated that large voltage unbalance significantly limits EV hosting capacity, suggesting the need for considering balancing strategies when possible.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"112 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129424136","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}
Pub Date : 2023-04-10DOI: 10.1109/GridEdge54130.2023.10102734
Bashar Mousa Melhem, Steven Liu
Based on the provisions of grid support published in the latest network codes (NC), wind turbines (WTs), among other renewable energy units, must regulate their output power to actively participate in supporting the grid frequency. However, the most frequently utilized wind turbines with doubly fed induction generators (DFIG) have limitations regarding rotor speed and converter power in addition to issues related to their power output resulting from wind speed fluctuation and model-plant mismatch. In this paper, rotor side converter of WT operated in de-loading mode is controlled adaptively. The objective is to provide transmission system operator (TSO) with an accurate available power and mitigate the influence of wind disturbances while following TSO variable power set-point. The limitations of both rotor speed and rotor side converter are considered in the proposed control approach.
{"title":"Adaptive approach for primary frequency support by wind turbines based on grid code requirements and turbines limitations","authors":"Bashar Mousa Melhem, Steven Liu","doi":"10.1109/GridEdge54130.2023.10102734","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102734","url":null,"abstract":"Based on the provisions of grid support published in the latest network codes (NC), wind turbines (WTs), among other renewable energy units, must regulate their output power to actively participate in supporting the grid frequency. However, the most frequently utilized wind turbines with doubly fed induction generators (DFIG) have limitations regarding rotor speed and converter power in addition to issues related to their power output resulting from wind speed fluctuation and model-plant mismatch. In this paper, rotor side converter of WT operated in de-loading mode is controlled adaptively. The objective is to provide transmission system operator (TSO) with an accurate available power and mitigate the influence of wind disturbances while following TSO variable power set-point. The limitations of both rotor speed and rotor side converter are considered in the proposed control approach.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"226 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113994664","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}
Pub Date : 2023-02-02DOI: 10.1109/GridEdge54130.2023.10102714
Victor Paduani, Rahul Kadavil, H. Hooshyar, A. Haddadi, A. Jakaria, A. Huque
This paper presents the development of a real-time T&D co-simulation testbed for simulating large grids under high DER penetration. By integrating bulk power system, distribution feeders, and distributed energy resources (DER) models into one simulation environment, the testbed enables the performance analysis and validation of DER management systems (DERMS) algorithms. This work proposes a co-simulation timestep sequence for the cross-platform data exchange and time synchronization, with a communication framework based on MQTT communication protocol. The proposed strategy is tested with a 5,000 buses model of part of the North American bulk power system (BPS) and a 9,500 nodes distribution feeder model obtained from a local utility. Simulations are carried out to demonstrate the capability of the proposed framework to propagate events between the transmission and distribution models. Results are used to quantify how the co-simulation timestep size can affect the propagation of dynamics between the models.
{"title":"Real-Time T&D Co-Simulation for Testing Grid Impact of High DER Participation","authors":"Victor Paduani, Rahul Kadavil, H. Hooshyar, A. Haddadi, A. Jakaria, A. Huque","doi":"10.1109/GridEdge54130.2023.10102714","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102714","url":null,"abstract":"This paper presents the development of a real-time T&D co-simulation testbed for simulating large grids under high DER penetration. By integrating bulk power system, distribution feeders, and distributed energy resources (DER) models into one simulation environment, the testbed enables the performance analysis and validation of DER management systems (DERMS) algorithms. This work proposes a co-simulation timestep sequence for the cross-platform data exchange and time synchronization, with a communication framework based on MQTT communication protocol. The proposed strategy is tested with a 5,000 buses model of part of the North American bulk power system (BPS) and a 9,500 nodes distribution feeder model obtained from a local utility. Simulations are carried out to demonstrate the capability of the proposed framework to propagate events between the transmission and distribution models. Results are used to quantify how the co-simulation timestep size can affect the propagation of dynamics between the models.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130338592","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}
Pub Date : 2022-10-05DOI: 10.1109/GridEdge54130.2023.10102720
Lisa Laurent, Jean-Sébastien Brouillon, G. Ferrari-Trecate
This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart Meters). First, we present a model of the grid, as well as the existing MLE based on voltage and current phasor measurements. Then, this problem formulation is adjusted for phase-less measurements using common assumptions. The effect of these assumptions is compared to the initial problem in various scenarios. Finally, numerical experiments on a popular IEEE benchmark network indicate promising results. Missing data can greatly disrupt estimation methods. Not measuring the voltage phase only adds 30% of error to the admittance matrix estimate in realistic conditions. Moreover, the sensitivity to measurement noise is similar with and without the phase.
{"title":"Maximum likelihood estimation of distribution grid topology and parameters from Smart Meter data","authors":"Lisa Laurent, Jean-Sébastien Brouillon, G. Ferrari-Trecate","doi":"10.1109/GridEdge54130.2023.10102720","DOIUrl":"https://doi.org/10.1109/GridEdge54130.2023.10102720","url":null,"abstract":"This paper defines a Maximum Likelihood Estimator (MLE) for the admittance matrix estimation of distribution grids, utilising voltage magnitude and power measurements collected only from common, unsychronised measuring devices (Smart Meters). First, we present a model of the grid, as well as the existing MLE based on voltage and current phasor measurements. Then, this problem formulation is adjusted for phase-less measurements using common assumptions. The effect of these assumptions is compared to the initial problem in various scenarios. Finally, numerical experiments on a popular IEEE benchmark network indicate promising results. Missing data can greatly disrupt estimation methods. Not measuring the voltage phase only adds 30% of error to the admittance matrix estimate in realistic conditions. Moreover, the sensitivity to measurement noise is similar with and without the phase.","PeriodicalId":377998,"journal":{"name":"2023 IEEE PES Grid Edge Technologies Conference & Exposition (Grid Edge)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115888471","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}
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