Pub Date : 2018-10-01DOI: 10.1109/ISGTEurope.2018.8571715
Nemer Amleh, M. Al-Muhaini, S. Djokic
This paper presents analysis of smart restoration techniques for improving system reliability through splitting a larger grid into a number of individual micro grids (MGs), which contain both wind and PV energy resources. The term “smart restoration” is used to denote adaptive control and management schemes, in which power system transfers from emergency operating conditions to a restorative state, where MGs are formed based on the available wind and PV energy resources. To preserve supply to all loads, or most of the loads in MGs, wind and PV energy resources are used for a fast transfer to MG operation and for efficient balancing of variable MG demands. The analysis uses Monte Carlo simulations to evaluate reliability indices for a number of considered MG scenarios.
{"title":"Smart Restoration for Improved Reliability of Microgrids with Renewable Energy Sources","authors":"Nemer Amleh, M. Al-Muhaini, S. Djokic","doi":"10.1109/ISGTEurope.2018.8571715","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571715","url":null,"abstract":"This paper presents analysis of smart restoration techniques for improving system reliability through splitting a larger grid into a number of individual micro grids (MGs), which contain both wind and PV energy resources. The term “smart restoration” is used to denote adaptive control and management schemes, in which power system transfers from emergency operating conditions to a restorative state, where MGs are formed based on the available wind and PV energy resources. To preserve supply to all loads, or most of the loads in MGs, wind and PV energy resources are used for a fast transfer to MG operation and for efficient balancing of variable MG demands. The analysis uses Monte Carlo simulations to evaluate reliability indices for a number of considered MG scenarios.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"37 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":"125812588","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/ISGTEurope.2018.8571898
Josue G. Deras-Campos, C. Angeles-Camacho, Lorena Cardenas-Guzman, Eloy Gomez-Lugo, Jose Valles-Canales
The underground distribution electric grid at UNAM is a success case in the implementation of smart grids in Mexico. The use of equipment for monitoring, protection, automation and control of the grid along with the parallel use of an optical fiber communication network has modernized the infrastructure installed on campus. Researchers, mainly from the Institute of Engineering and for purely academic purposes, are interested in using measurements of electrical parameters of the medium voltage grid in order to develop a monitoring and simulation platform that allows running state-of-the-art smart grid applications. Firstly, this paper focuses on the grid description; later, a proposal of how the data could be managed from the laboratory through the German software Power Factory DIgSILENT is presented. An example of an academic use is shown by performing a photovoltaic integration study using data from the SISIFO software, an open source Photovoltaic simulator.
{"title":"A Review of the New Medium Voltage Smart Grid at UNAM and its Academic Uses","authors":"Josue G. Deras-Campos, C. Angeles-Camacho, Lorena Cardenas-Guzman, Eloy Gomez-Lugo, Jose Valles-Canales","doi":"10.1109/ISGTEurope.2018.8571898","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571898","url":null,"abstract":"The underground distribution electric grid at UNAM is a success case in the implementation of smart grids in Mexico. The use of equipment for monitoring, protection, automation and control of the grid along with the parallel use of an optical fiber communication network has modernized the infrastructure installed on campus. Researchers, mainly from the Institute of Engineering and for purely academic purposes, are interested in using measurements of electrical parameters of the medium voltage grid in order to develop a monitoring and simulation platform that allows running state-of-the-art smart grid applications. Firstly, this paper focuses on the grid description; later, a proposal of how the data could be managed from the laboratory through the German software Power Factory DIgSILENT is presented. An example of an academic use is shown by performing a photovoltaic integration study using data from the SISIFO software, an open source Photovoltaic simulator.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"73 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":"126081539","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/ISGTEurope.2018.8571851
Jia-lin Bai, I. Erlich
This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.
{"title":"Coordinated Voltage Control for Transmission Grid Based on Multi-model Predictive Control Strategy","authors":"Jia-lin Bai, I. Erlich","doi":"10.1109/ISGTEurope.2018.8571851","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571851","url":null,"abstract":"This paper proposes a multi-model based predictive control (MMPC) strategy for the coordinated voltage control of the transmission grid that may operate under diverse anticipated conditions. Since both Kalman filtering and optimization process are based on mathematical model, a model database representing the critical operating conditions is required. For unrepresented conditions, MMPC is designed to be robust by setting the noise model of Kalman filter and by tuning the optimization window of MMPC. In each control cycle, MMPC searches for the optimal coordination of Automatic Voltage Regulators and Static Var Compensators. The case studies take into account two types of operation changes: load change over 24 hour and generator in/out of service. In different simulation tests, in comparison with single -model based control strategy, the superiority and robustness of MMPC following a load increase disturbance are demonstrated.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"65 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":"123413894","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/ISGTEurope.2018.8571802
A. R. Jordehi
Using distributed generation (DG) units is a viable strategy for improving the characteristics of electric distribution systems, in terms of power loss, voltage profile and power congestion. Finding optimal location and setting of DG's is referred to as DG allocation problem and is typically formulated as an optimisation problem which is solved by metaheuristic optimisation algorithms. In this paper, the performance of four metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), grey wolf optimisation (GWO), backtracking search algorithm (BSA) and whale optimisation algorithm (WOA) in solving DG allocation problem and also in solving simultaneous reconfiguration and DG allocation problem have been compared. The simulations have been done for six different scenarios. The results indicate the outperformance of GWO in most of the cases.
{"title":"DG allocation and reconfiguration in distribution systems by metaheuristic optimisation algorithms: a comparative analysis","authors":"A. R. Jordehi","doi":"10.1109/ISGTEurope.2018.8571802","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571802","url":null,"abstract":"Using distributed generation (DG) units is a viable strategy for improving the characteristics of electric distribution systems, in terms of power loss, voltage profile and power congestion. Finding optimal location and setting of DG's is referred to as DG allocation problem and is typically formulated as an optimisation problem which is solved by metaheuristic optimisation algorithms. In this paper, the performance of four metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), grey wolf optimisation (GWO), backtracking search algorithm (BSA) and whale optimisation algorithm (WOA) in solving DG allocation problem and also in solving simultaneous reconfiguration and DG allocation problem have been compared. The simulations have been done for six different scenarios. The results indicate the outperformance of GWO in most of the cases.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","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":"126757772","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/ISGTEurope.2018.8571465
A. Attya, N. Schofield, Mahmoud Dhimish
This paper proposes a compact approach to perform a preliminary techno-economic feasibility study to decide the technology and size of Battery Energy Storage System (BESS) that is suitable to particular application(s). A detailed mind matrix is proposed to provide a high-level vision of the incorporated techno-economic challenges and questions within the process, where 38 issues are expansively considered. Afterwards, a prioritization scheme is presented to evaluate the benefits and required capacity of BESS integration aiming to mitigate the complexity of such study. A simplified costing model is also discussed to highlight the main factors that judge the financial value of the BESS. This paper provides spotlight on the key knowledge gaps and research areas that could be of interest to industry and academic stakeholders.
{"title":"BESS Techno-economic Challenges to Support Wind Energy: Mind Mapping and Correlation Matrix","authors":"A. Attya, N. Schofield, Mahmoud Dhimish","doi":"10.1109/ISGTEurope.2018.8571465","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571465","url":null,"abstract":"This paper proposes a compact approach to perform a preliminary techno-economic feasibility study to decide the technology and size of Battery Energy Storage System (BESS) that is suitable to particular application(s). A detailed mind matrix is proposed to provide a high-level vision of the incorporated techno-economic challenges and questions within the process, where 38 issues are expansively considered. Afterwards, a prioritization scheme is presented to evaluate the benefits and required capacity of BESS integration aiming to mitigate the complexity of such study. A simplified costing model is also discussed to highlight the main factors that judge the financial value of the BESS. This paper provides spotlight on the key knowledge gaps and research areas that could be of interest to industry and academic stakeholders.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"201 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":"116160683","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/ISGTEurope.2018.8571721
Kunqi Jia, G. He, L. Yang, Ninghui Zhou
Although considerable of literature on residential demand response strategy takes user satisfaction into account, we argue that those researches cannot accurately reflect user satisfaction because they do not theoretically analyze the user's decision-making process from a cost-benefit perspective. In order to precisely characterize the user satisfaction of electricity consumption, this paper proposes a utility function (in an economic sense)-based approach for sophisticatedly formulating user satisfaction. Additionally, behavioral economics is introduced to describe user's decision-making process in demand response, and a washer dryer and a PEV are taken as examples. Since the proposed method can provide a theoretically practical analytical framework which indeed and elaborately takes human factors into consideration, user enthusiasm for demand response can be ensured and the effectiveness of the demand response strategy can be more easily realized.
{"title":"Preference Analyses of Residential Appliances in Demand Response: A Novel Perspective Based on Behavioral Economics","authors":"Kunqi Jia, G. He, L. Yang, Ninghui Zhou","doi":"10.1109/ISGTEurope.2018.8571721","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571721","url":null,"abstract":"Although considerable of literature on residential demand response strategy takes user satisfaction into account, we argue that those researches cannot accurately reflect user satisfaction because they do not theoretically analyze the user's decision-making process from a cost-benefit perspective. In order to precisely characterize the user satisfaction of electricity consumption, this paper proposes a utility function (in an economic sense)-based approach for sophisticatedly formulating user satisfaction. Additionally, behavioral economics is introduced to describe user's decision-making process in demand response, and a washer dryer and a PEV are taken as examples. Since the proposed method can provide a theoretically practical analytical framework which indeed and elaborately takes human factors into consideration, user enthusiasm for demand response can be ensured and the effectiveness of the demand response strategy can be more easily realized.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"249 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":"114552394","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/ISGTEurope.2018.8571432
J. Khodaparast, O. Fosso, M. Molinas
Phasor estimation is crucial for monitoring and control of smart power systems. The classical signal processing method named Prony has been used for estimating the parameters of measured signals such as frequency, damping factor and phasor. To reduce the impact of noise on the parameters estimated by Prony, multi-channel Prony has been previously explored and presented in the literature. The basic approach for multi-channel Prony is a generalized solution, in which new rows are added to matrices for every channel. Since the generalized multi -channel Prony is time-consuming, a new method based on recursive solution is proposed in this paper to make it suitable for real-time application. Here, several channels of one Phasor Measurement Unit (PMU) are used to estimate the phasor of current/voltage in a recursive pattern, in which the phasor is computed recursively over time based on previously calculated estimates and new measurements. The proposed method is compared with three other solutions for multi-channel Prony: a) data fusion which is based on the Kalman filter concept, b) an alternating direction method of multipliers (ADMM), and c) a consensus update approach which is based on an iterative procedure. Simulation results demonstrate the ability of the proposed method for real-time phasor estimation, both in terms of maintaining the accuracy and reducing computation time.
{"title":"Real Time Phasor Estimation Based on Recursive Prony with Several Channels of One PMU","authors":"J. Khodaparast, O. Fosso, M. Molinas","doi":"10.1109/ISGTEurope.2018.8571432","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571432","url":null,"abstract":"Phasor estimation is crucial for monitoring and control of smart power systems. The classical signal processing method named Prony has been used for estimating the parameters of measured signals such as frequency, damping factor and phasor. To reduce the impact of noise on the parameters estimated by Prony, multi-channel Prony has been previously explored and presented in the literature. The basic approach for multi-channel Prony is a generalized solution, in which new rows are added to matrices for every channel. Since the generalized multi -channel Prony is time-consuming, a new method based on recursive solution is proposed in this paper to make it suitable for real-time application. Here, several channels of one Phasor Measurement Unit (PMU) are used to estimate the phasor of current/voltage in a recursive pattern, in which the phasor is computed recursively over time based on previously calculated estimates and new measurements. The proposed method is compared with three other solutions for multi-channel Prony: a) data fusion which is based on the Kalman filter concept, b) an alternating direction method of multipliers (ADMM), and c) a consensus update approach which is based on an iterative procedure. Simulation results demonstrate the ability of the proposed method for real-time phasor estimation, both in terms of maintaining the accuracy and reducing computation time.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"20 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":"116589618","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/ISGTEurope.2018.8571565
Oliver Selinger-Lutz, I. Katz, R. Hollinger, C. Wittwer
The future energy system needs to be reliable, affordable for all parties, and capable of integrating fluctuating renewable energy sources into the grid. In this work we present first field test results of a resilient Smart Grid concept using dynamic tariff rates for end customers. The tariff system is based on the course of the EPEX Day-Ahead electricity price. Ripple control was used as a robust and reliable communication system. This work focuses on three main aspects: the reliability of the communication system, the financial advantages for the end-customers, and the load shifting potential given by the external incentive signals. Results show that ripple control is an adequate communication system for sending tariff information signals to the end customers. A financial benefit for all field test participants was achieved by implementing the dynamic tariff system. We show that during the field test period, the Prosumers changed their energy consumption behavior when stimulated by the external incentives.
{"title":"Lessons Learned From Field Test Data of a Robust Smart Grid Concept","authors":"Oliver Selinger-Lutz, I. Katz, R. Hollinger, C. Wittwer","doi":"10.1109/ISGTEurope.2018.8571565","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571565","url":null,"abstract":"The future energy system needs to be reliable, affordable for all parties, and capable of integrating fluctuating renewable energy sources into the grid. In this work we present first field test results of a resilient Smart Grid concept using dynamic tariff rates for end customers. The tariff system is based on the course of the EPEX Day-Ahead electricity price. Ripple control was used as a robust and reliable communication system. This work focuses on three main aspects: the reliability of the communication system, the financial advantages for the end-customers, and the load shifting potential given by the external incentive signals. Results show that ripple control is an adequate communication system for sending tariff information signals to the end customers. A financial benefit for all field test participants was achieved by implementing the dynamic tariff system. We show that during the field test period, the Prosumers changed their energy consumption behavior when stimulated by the external incentives.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"18 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":"116848032","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/ISGTEurope.2018.8571447
James Wylie, P. Judge, T. Green
Modular Multi-level Converters (MMC) for medium voltage applications need to be compact and low-loss but also must have good waveform quality. This makes the choice of Sub-Module (SM) voltage rating and quantity a challenging compromise. An extra degree of design freedom is possible if modules in each arm are a mixture of nominal voltage ratings. A design is investigated here with several high voltage SMs for bulk power processing and two low voltage SMs for waveform following control. Power loss, efficiency and total harmonic distortion are compared against two designs of conventional MMC of equivalent power rating and waveform distortion level, but different SM voltage choices. A new low-level controller for SM rotation is devised which deploys different SM types for the different purposes, but also ensures charge balancing. Simulation results show reduced power loss for an MMC with mixed voltage-rated SMs within the same arm, when compared against the conventional MMCs.
{"title":"Modular Multi-level Converter for Medium Voltage Applications with Mixed Sub-module Voltages within Each Arm","authors":"James Wylie, P. Judge, T. Green","doi":"10.1109/ISGTEurope.2018.8571447","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571447","url":null,"abstract":"Modular Multi-level Converters (MMC) for medium voltage applications need to be compact and low-loss but also must have good waveform quality. This makes the choice of Sub-Module (SM) voltage rating and quantity a challenging compromise. An extra degree of design freedom is possible if modules in each arm are a mixture of nominal voltage ratings. A design is investigated here with several high voltage SMs for bulk power processing and two low voltage SMs for waveform following control. Power loss, efficiency and total harmonic distortion are compared against two designs of conventional MMC of equivalent power rating and waveform distortion level, but different SM voltage choices. A new low-level controller for SM rotation is devised which deploys different SM types for the different purposes, but also ensures charge balancing. Simulation results show reduced power loss for an MMC with mixed voltage-rated SMs within the same arm, when compared against the conventional MMCs.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","volume":"123 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":"129600038","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/ISGTEurope.2018.8571845
M. Grabner, A. Souvent, B. Blazic, A. Košir
The paper presents a brief summary of the study which was carried out as part of the demand response (DR) project in the scope of Slovenian-Japanese NEDO project. The purpose of this study was to examine the possible annual substation (SBS) peak load decrease before actual DR activation in order to assess the possible benefit of the future program. SBS load time series data were thoroughly examined with various types of statistical diagrams. The daily load profiles were analyzed with the unsupervised machine learning. With 50 hours of DR activation available per year, the annual peak could be decreased for around 5%. Since the load is highly dependent on temperature, normalized daily peak load was calculated with supervised machine learning. It can be seen throughout the paper that advanced statistical diagrams and machine learning techniques allow better assessment of future the DR program.
{"title":"Statistical Load Time Series Analysis for the Demand Side Management","authors":"M. Grabner, A. Souvent, B. Blazic, A. Košir","doi":"10.1109/ISGTEurope.2018.8571845","DOIUrl":"https://doi.org/10.1109/ISGTEurope.2018.8571845","url":null,"abstract":"The paper presents a brief summary of the study which was carried out as part of the demand response (DR) project in the scope of Slovenian-Japanese NEDO project. The purpose of this study was to examine the possible annual substation (SBS) peak load decrease before actual DR activation in order to assess the possible benefit of the future program. SBS load time series data were thoroughly examined with various types of statistical diagrams. The daily load profiles were analyzed with the unsupervised machine learning. With 50 hours of DR activation available per year, the annual peak could be decreased for around 5%. Since the load is highly dependent on temperature, normalized daily peak load was calculated with supervised machine learning. It can be seen throughout the paper that advanced statistical diagrams and machine learning techniques allow better assessment of future the DR program.","PeriodicalId":302863,"journal":{"name":"2018 IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT-Europe)","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":"128511221","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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