Pub Date : 2018-10-01DOI: 10.1109/EPEC.2018.8598442
A. Gagné, N. Ninad, John Adeyemo, D. Turcotte, Steven Wong
The irradiance at ground level mostly fluctuates due to cloud coverage. As clouds are moving toward a certain direction, the cardinal orientation of photovoitaic arrays affects the variability of the output power, and thus the impact on the electric power grid. This paper presents a new methodology with a circular layout for irradiance monitoring units to assess the solar variability in different directions of any site based on cloud speed-direction trend and directional variability reduction. The proposed methodology is used to assess the directional variability for a site at Varennes, QC, Canada using 1 year of measured data. The cloud speed direction is studied in order to observe any trend from a month-to-month and from an hour-to-hour. Overall the cloud direction has a trend of West to East direction, especially during the winter months. The variability reduction for each axis is estimated using the variability index (VI). The largest VI reduction is observed close to the cloud direction axis.
{"title":"Directional Solar Variability Analysis","authors":"A. Gagné, N. Ninad, John Adeyemo, D. Turcotte, Steven Wong","doi":"10.1109/EPEC.2018.8598442","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598442","url":null,"abstract":"The irradiance at ground level mostly fluctuates due to cloud coverage. As clouds are moving toward a certain direction, the cardinal orientation of photovoitaic arrays affects the variability of the output power, and thus the impact on the electric power grid. This paper presents a new methodology with a circular layout for irradiance monitoring units to assess the solar variability in different directions of any site based on cloud speed-direction trend and directional variability reduction. The proposed methodology is used to assess the directional variability for a site at Varennes, QC, Canada using 1 year of measured data. The cloud speed direction is studied in order to observe any trend from a month-to-month and from an hour-to-hour. Overall the cloud direction has a trend of West to East direction, especially during the winter months. The variability reduction for each axis is estimated using the variability index (VI). The largest VI reduction is observed close to the cloud direction axis.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129122439","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598294
Richard W Hamilton, Hayden Seager, K. P. Divakarla, A. Emadi, S. Razavi
Autonomous-capable Electrified Vehicles are becoming increasingly popular in the field of automotive research. They are being rapidly recognized as being a reliable alternative to completely human controlled vehicles for reducing the probability of incidents occurring due to driver distraction/ limitations. This review paper provides a general framework for modeling an autonomous-capable electrified vehicle highlighting some of the major building blocks associated with such a model. Some of the major relevant modeling tools are also discussed. Furthermore, the paper describes the simulations carried out using multiple test cases incorporating autonomous features of distinct levels.
{"title":"Modeling and Simulation of an Autonomous-capable Electrified Vehicle: A Review","authors":"Richard W Hamilton, Hayden Seager, K. P. Divakarla, A. Emadi, S. Razavi","doi":"10.1109/EPEC.2018.8598294","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598294","url":null,"abstract":"Autonomous-capable Electrified Vehicles are becoming increasingly popular in the field of automotive research. They are being rapidly recognized as being a reliable alternative to completely human controlled vehicles for reducing the probability of incidents occurring due to driver distraction/ limitations. This review paper provides a general framework for modeling an autonomous-capable electrified vehicle highlighting some of the major building blocks associated with such a model. Some of the major relevant modeling tools are also discussed. Furthermore, the paper describes the simulations carried out using multiple test cases incorporating autonomous features of distinct levels.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128109401","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598452
Abdullah M. Sawas, H. Farag
Recent research works have revealed that state estimators in power systems are susceptible to false data injection attacks (FDIA). Still, for an adversary, constructing a least effort attack vector is difficult and known to be L0-norm optimization problem. In this paper, two-fold intelligent approach is proposed to optimally construct the FDIA vector. First, the problem of selecting the vector components is formulated as a constrained nonlinear programming problem and is solved using Genetic Algorithm. Second, a Neural Network is trained to generate in real-time the vector amplitudes. The attack vector is optimally selected in terms of number of measurements to compromise, the set of measurements accessible be the adversary, and flexibility to successfully pass Bad Data Detection algorithm of the state estimator. The performance of the attack vectors is analyzed on the IEEE 14-bus system against AC state estimator for a range of various system loading conditions and considering two attack strategies.
{"title":"Two-fold Intelligent Approach for Successful FDI Attack on Power Systems State Estimation","authors":"Abdullah M. Sawas, H. Farag","doi":"10.1109/EPEC.2018.8598452","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598452","url":null,"abstract":"Recent research works have revealed that state estimators in power systems are susceptible to false data injection attacks (FDIA). Still, for an adversary, constructing a least effort attack vector is difficult and known to be L0-norm optimization problem. In this paper, two-fold intelligent approach is proposed to optimally construct the FDIA vector. First, the problem of selecting the vector components is formulated as a constrained nonlinear programming problem and is solved using Genetic Algorithm. Second, a Neural Network is trained to generate in real-time the vector amplitudes. The attack vector is optimally selected in terms of number of measurements to compromise, the set of measurements accessible be the adversary, and flexibility to successfully pass Bad Data Detection algorithm of the state estimator. The performance of the attack vectors is analyzed on the IEEE 14-bus system against AC state estimator for a range of various system loading conditions and considering two attack strategies.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133311780","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598457
Terumi Onishi, S. Obara, M. Okada, Yuji Ito
In order to expand the introduction amount of renewable energy, it is necessary to solve various problems such as suppression of output fluctuation, cost of power supply compensator for reducing output fluctuation, and lack of transmission capacity. On the other hand, it is known that output fluctuation of renewable energy is leveled by interconnecting renewable energy dispersedly arranged in a wide area [1]. Therefore, it is possible to reduce the cost of the system by optimally distributing and link the renewable energy to a wide area. Therefore, in this study, we developed computer algorithms to optimize the location and introduction amount of renewable energy that will conduct wide area interconnections based on actual transmission network equipment. The target of the analysis was the Hokkaido area in Japan with extensive land and abundant natural energy. Using the proposed algorithm, we evaluate the relationship between economical renewable energy location and capacity, renewable energy supply rate and grid capacity. As a result, it was possible to realize an economical power system with a high percentage power supply ratio of renewable energy.
{"title":"Layout planning of renewable energy in consideration of power transmission range based on transmission capacity","authors":"Terumi Onishi, S. Obara, M. Okada, Yuji Ito","doi":"10.1109/EPEC.2018.8598457","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598457","url":null,"abstract":"In order to expand the introduction amount of renewable energy, it is necessary to solve various problems such as suppression of output fluctuation, cost of power supply compensator for reducing output fluctuation, and lack of transmission capacity. On the other hand, it is known that output fluctuation of renewable energy is leveled by interconnecting renewable energy dispersedly arranged in a wide area [1]. Therefore, it is possible to reduce the cost of the system by optimally distributing and link the renewable energy to a wide area. Therefore, in this study, we developed computer algorithms to optimize the location and introduction amount of renewable energy that will conduct wide area interconnections based on actual transmission network equipment. The target of the analysis was the Hokkaido area in Japan with extensive land and abundant natural energy. Using the proposed algorithm, we evaluate the relationship between economical renewable energy location and capacity, renewable energy supply rate and grid capacity. As a result, it was possible to realize an economical power system with a high percentage power supply ratio of renewable energy.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123005429","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598349
A. Eajal, A. Yazdavar, E. El-Saadany, K. Ponnambalam
The future smart grid entails clusters with plug-and-play features known as microgrids. Each microgrid hosts a mix of distributed energy resources including synchronous-based. Nevertheless, synchronous-based generators, are characterised by their limited reactive power capabilities which could lead to voltage collapse problem during islanding. Microgrids also comprises controllable loads. The majority of modern loads are power-electronic-interfaced and demand voltage regulation at their ends, exhibiting constant power characteristics. Microgrids with high penetrations of constant-power loads are vulnerable to voltage collapse especially during contingencies such as weather-caused outages. To this end, this paper investigates the possibility voltage collapse phenomenon in islanded microgrids during contingencies. The voltage stability analysis was carried out on an islanded 6- bus microgrid. Several case studies were designed in order to reveal the likelihood of voltage collapse in microgrids under extreme events.
{"title":"On the Existence of Voltage Collapse in Islanded Microgrid","authors":"A. Eajal, A. Yazdavar, E. El-Saadany, K. Ponnambalam","doi":"10.1109/EPEC.2018.8598349","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598349","url":null,"abstract":"The future smart grid entails clusters with plug-and-play features known as microgrids. Each microgrid hosts a mix of distributed energy resources including synchronous-based. Nevertheless, synchronous-based generators, are characterised by their limited reactive power capabilities which could lead to voltage collapse problem during islanding. Microgrids also comprises controllable loads. The majority of modern loads are power-electronic-interfaced and demand voltage regulation at their ends, exhibiting constant power characteristics. Microgrids with high penetrations of constant-power loads are vulnerable to voltage collapse especially during contingencies such as weather-caused outages. To this end, this paper investigates the possibility voltage collapse phenomenon in islanded microgrids during contingencies. The voltage stability analysis was carried out on an islanded 6- bus microgrid. Several case studies were designed in order to reveal the likelihood of voltage collapse in microgrids under extreme events.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124903818","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598420
A. Papachristou, A. Awad, D. Turcotte, Steven Wong, A. Prieur
Distribution networks are three-phase systems supplying electricity to loads. While, ideally, the load at each point of the network would be equally distributed among the three phases, this is not the case in practice. The three-phase voltages and currents are thus unbalanced due to the different magnitudes of loads at each phase. The integration of single-phase distributed generation (DG), e.g., photovoltaic (PV) units installed at secondary networks, adds more challenges to the voltage unbalance in distribution networks. This paper investigates through simulations the impact of DG on the voltage unbalance in Canadian benchmark rural distribution networks. The maximum penetration levels of DG that can be integrated into distribution networks are determined taking into consideration the standard limits of voltage unbalance, operating voltage limits, and thermal ratings of the feeder. Different configurations of voltage regulators and DG are studied. Simulation results showed that the voltage unbalance factor (VUF) decreases with the integration of three-phase DG especially when high penetration levels of DG are located close to the end of the main feeder. Up to 24 MW of three-phase DG can be connected to the main feeder, which is 154% of the total peak load, without violating any of the limits. It was also found that the maximum size of a single-phase DG can be at least 3 times the peak load of a given node at any single-phase lateral.
{"title":"Impact of DG on Voltage Unbalance in Canadian Benchmark Rural Distribution Networks","authors":"A. Papachristou, A. Awad, D. Turcotte, Steven Wong, A. Prieur","doi":"10.1109/EPEC.2018.8598420","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598420","url":null,"abstract":"Distribution networks are three-phase systems supplying electricity to loads. While, ideally, the load at each point of the network would be equally distributed among the three phases, this is not the case in practice. The three-phase voltages and currents are thus unbalanced due to the different magnitudes of loads at each phase. The integration of single-phase distributed generation (DG), e.g., photovoltaic (PV) units installed at secondary networks, adds more challenges to the voltage unbalance in distribution networks. This paper investigates through simulations the impact of DG on the voltage unbalance in Canadian benchmark rural distribution networks. The maximum penetration levels of DG that can be integrated into distribution networks are determined taking into consideration the standard limits of voltage unbalance, operating voltage limits, and thermal ratings of the feeder. Different configurations of voltage regulators and DG are studied. Simulation results showed that the voltage unbalance factor (VUF) decreases with the integration of three-phase DG especially when high penetration levels of DG are located close to the end of the main feeder. Up to 24 MW of three-phase DG can be connected to the main feeder, which is 154% of the total peak load, without violating any of the limits. It was also found that the maximum size of a single-phase DG can be at least 3 times the peak load of a given node at any single-phase lateral.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438863","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598374
Ali R. Al-Roomi, M. El-Hawary
It is known that the energy trading strategy followed in existing smart grids is built based on transferring electricity between entities. Because there is a big portion of non-electric energy forms are also employed in daily uses, such as logs, solar, and biogas water heaters, so still there is a deficiency associated with these grids. There is an attempt to trade these non-electrical energy forms in the next generation smart grids. However, the option discussed in that study is not well established, and it is built based on only transferring hot waters through pipelines connected between entities. Actually, this approach has some limitations and it could be a non-optimal choice to trade nonelectrical energy forms in terms of minimum losses, maximum profit, less risks, more flexibility, environment friendly, aesthetics, etc. This study discusses multiple possible options to locally trade these non-electric energy forms in the next generation smart grids. Therefore, the best option can be selected based on a tradeoff or a single/multi-objective approach.
{"title":"Possible Approaches to Trade Non-Electric Energy Sources in the Next Generation Smart Grids","authors":"Ali R. Al-Roomi, M. El-Hawary","doi":"10.1109/EPEC.2018.8598374","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598374","url":null,"abstract":"It is known that the energy trading strategy followed in existing smart grids is built based on transferring electricity between entities. Because there is a big portion of non-electric energy forms are also employed in daily uses, such as logs, solar, and biogas water heaters, so still there is a deficiency associated with these grids. There is an attempt to trade these non-electrical energy forms in the next generation smart grids. However, the option discussed in that study is not well established, and it is built based on only transferring hot waters through pipelines connected between entities. Actually, this approach has some limitations and it could be a non-optimal choice to trade nonelectrical energy forms in terms of minimum losses, maximum profit, less risks, more flexibility, environment friendly, aesthetics, etc. This study discusses multiple possible options to locally trade these non-electric energy forms in the next generation smart grids. Therefore, the best option can be selected based on a tradeoff or a single/multi-objective approach.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129638684","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598444
Jason Jaskolka
The modern energy sector depends on advanced metering infrastructure (AMI) systems responsible for gathering, measuring, and analyzing enormous amounts of energy consumption information to make important decisions related to energy services including billing, monitoring, distribution, load balancing, and more. However, the introduction and integration of these new technologies presents a wide range of complex challenges. Assuring the confidentially, integrity, availability, and accountability of sensitive consumer information, and the safe, resilient, and reliable delivery of critical services, is among the top priorities for governments and utility providers. In this paper, we describe our experience in developing assurance cases for arguing about the security and resilience of AMI systems, and the emerging regulatory and policy challenges and lessons learned in the development of advanced tools and methods for achieving cyber-assurance for the energy sector, and critical infrastructure in general.
{"title":"Challenges in Assuring Security and Resilience of Advanced Metering Infrastructure","authors":"Jason Jaskolka","doi":"10.1109/EPEC.2018.8598444","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598444","url":null,"abstract":"The modern energy sector depends on advanced metering infrastructure (AMI) systems responsible for gathering, measuring, and analyzing enormous amounts of energy consumption information to make important decisions related to energy services including billing, monitoring, distribution, load balancing, and more. However, the introduction and integration of these new technologies presents a wide range of complex challenges. Assuring the confidentially, integrity, availability, and accountability of sensitive consumer information, and the safe, resilient, and reliable delivery of critical services, is among the top priorities for governments and utility providers. In this paper, we describe our experience in developing assurance cases for arguing about the security and resilience of AMI systems, and the emerging regulatory and policy challenges and lessons learned in the development of advanced tools and methods for achieving cyber-assurance for the energy sector, and critical infrastructure in general.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127458303","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598329
Henning Wilms, M. Cupelli, A. Monti
In this paper we use publicly available time series data sets from the Global Energy Forecasting Competitions to evaluate the added value of exogenous, explanatory variables when forecasting wind, load and PV profiles. Two different auto-regressive models are built as well as one model that includes exogenous variables. All of models use recurrent neural networks (RNN) as their base architecture. The added value of exogenous variables is evaluated by comparing different accuracy metrics cross data set and cross model. The results show, that the autocorrelation of load and PV data sets produce reasonably good accuracies for auto-regressive predictions using RNNs, whereas wind production is far harder to forecast and the RNNs are not able to infer any suitable predictions using only a univariate time series.
{"title":"On the Necessity of Exogenous Variables for Load, PV and Wind Day-Ahead Forecasts using Recurrent Neural Networks","authors":"Henning Wilms, M. Cupelli, A. Monti","doi":"10.1109/EPEC.2018.8598329","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598329","url":null,"abstract":"In this paper we use publicly available time series data sets from the Global Energy Forecasting Competitions to evaluate the added value of exogenous, explanatory variables when forecasting wind, load and PV profiles. Two different auto-regressive models are built as well as one model that includes exogenous variables. All of models use recurrent neural networks (RNN) as their base architecture. The added value of exogenous variables is evaluated by comparing different accuracy metrics cross data set and cross model. The results show, that the autocorrelation of load and PV data sets produce reasonably good accuracies for auto-regressive predictions using RNNs, whereas wind production is far harder to forecast and the RNNs are not able to infer any suitable predictions using only a univariate time series.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126330657","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 : 2018-10-01DOI: 10.1109/EPEC.2018.8598379
Irene Wanady, A. Viswanath, K. Mahata
This paper aims to build a solar forecasting model for the power system operator to allow them to make informed decisions on the electricity market dispatch. Detailed literature review on meteorological and atmospheric sciences is performed to understand the various factors which affect the solar irradiance level. These parameters are classified into four types. The first type is the meteorological parameters which vary with the date and time and the second type is the parameters which depend on the location. Using known equations and existing empirical models, the parameters classified in these two types is determined. The third classification is the parameters which are affected by the weather and this includes temperature and relative humidity. In this paper, statistical prediction method will be used to forecast these two parameters. Temperature and humidity are related to each other and therefore, vector time series is used in the prediction method. Stationary time series data will be used in the ARMA model fitting. The innovation series was found before maximum likelihood and instrumental variable method are used to determine the suitable parameter for the ARMA model. The last classification for this paper is the parameter for the cloud cover. Image processing of satellite images will be used to determine this cloudiness parameter. Solar irradiance is then calculated using the combination of all these parameters. This method is illustrated by using Singapore weather data.
{"title":"Solar Forecasting for Power System Operator","authors":"Irene Wanady, A. Viswanath, K. Mahata","doi":"10.1109/EPEC.2018.8598379","DOIUrl":"https://doi.org/10.1109/EPEC.2018.8598379","url":null,"abstract":"This paper aims to build a solar forecasting model for the power system operator to allow them to make informed decisions on the electricity market dispatch. Detailed literature review on meteorological and atmospheric sciences is performed to understand the various factors which affect the solar irradiance level. These parameters are classified into four types. The first type is the meteorological parameters which vary with the date and time and the second type is the parameters which depend on the location. Using known equations and existing empirical models, the parameters classified in these two types is determined. The third classification is the parameters which are affected by the weather and this includes temperature and relative humidity. In this paper, statistical prediction method will be used to forecast these two parameters. Temperature and humidity are related to each other and therefore, vector time series is used in the prediction method. Stationary time series data will be used in the ARMA model fitting. The innovation series was found before maximum likelihood and instrumental variable method are used to determine the suitable parameter for the ARMA model. The last classification for this paper is the parameter for the cloud cover. Image processing of satellite images will be used to determine this cloudiness parameter. Solar irradiance is then calculated using the combination of all these parameters. This method is illustrated by using Singapore weather data.","PeriodicalId":265297,"journal":{"name":"2018 IEEE Electrical Power and Energy Conference (EPEC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125918622","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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