Pub Date : 2019-09-01DOI: 10.1109/SEST.2019.8849050
S. Talari, D. Mende, David Sebastian Stock, M. Shafie‐khah, J. Catalão
In this paper, demand-side management (DSM) is performed through demand response aggregators (DRAs) in an uncertain environment within zonal price market framework. The proposed scheme aims to allow cross-border electricity trading and optimize interconnections usage as well as to obtain optimum DR volume from the perspective of the Market Coupling Operator (MCO). The market consists of several zonal price markets as Nominated Electricity Market Operators (NEMO) who run their day-ahead and balancing market internally and communicate the information to the MCO to provide the cooperation with other NEMOs. To this end, a stochastic two-stage model is formulated in which the total operation cost from MCO's viewpoint is minimized. Accordingly, the model aims to consider day-ahead decisions in the first stage and balancing decisions in the second stage. Furthermore, the intermittent nature of renewable sources generation is handled by scenario generation with Monte-Carlo Simulation (MCS) method. NEMOs are physically connected as radial network. Therefore, all relative network constraints are taken into account as a linear power flow for radial networks. The results of the implementation of the proposed model demonstrate the effectiveness of various DR biddings on hourly DR volume, hourly DR cost and power exchange between different NEMOS.
{"title":"Stochastic Demand Side Management in European Zonal Price Market","authors":"S. Talari, D. Mende, David Sebastian Stock, M. Shafie‐khah, J. Catalão","doi":"10.1109/SEST.2019.8849050","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849050","url":null,"abstract":"In this paper, demand-side management (DSM) is performed through demand response aggregators (DRAs) in an uncertain environment within zonal price market framework. The proposed scheme aims to allow cross-border electricity trading and optimize interconnections usage as well as to obtain optimum DR volume from the perspective of the Market Coupling Operator (MCO). The market consists of several zonal price markets as Nominated Electricity Market Operators (NEMO) who run their day-ahead and balancing market internally and communicate the information to the MCO to provide the cooperation with other NEMOs. To this end, a stochastic two-stage model is formulated in which the total operation cost from MCO's viewpoint is minimized. Accordingly, the model aims to consider day-ahead decisions in the first stage and balancing decisions in the second stage. Furthermore, the intermittent nature of renewable sources generation is handled by scenario generation with Monte-Carlo Simulation (MCS) method. NEMOs are physically connected as radial network. Therefore, all relative network constraints are taken into account as a linear power flow for radial networks. The results of the implementation of the proposed model demonstrate the effectiveness of various DR biddings on hourly DR volume, hourly DR cost and power exchange between different NEMOS.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131761172","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849120
Mohammadali Norouzi, J. Aghaei, S. Pirouzi
The high penetration of renewable energy sources (RESs) has imposed new challenges in the operation of smart distribution networks. Changing the distribution networks indices is one of the untoward significant changes. In this paper, to improve the operational performance of smart distribution network, the application of electric spring (ES) as a new device in the power electronic revolution is proposed. Furthermore, the novel static model of the ES is presented and described in detail. In the next step, the effect of the presence of ES on distribution network indices in various scenarios has been studied. Finally, the suggested solution has been tested on 32-bus IEEE test microgrid as a distribution network by the GAMS software to analyze the potential and effectiveness of the ES in improving the microgrid indices. The results of the simulations verify the suggested solution completely by modifying the mentioned indices, and enhancing the conditions for the operation of the microgrid.
{"title":"Enhancing Distribution Network Indices Using Electric Spring under Renewable Generation Permission","authors":"Mohammadali Norouzi, J. Aghaei, S. Pirouzi","doi":"10.1109/SEST.2019.8849120","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849120","url":null,"abstract":"The high penetration of renewable energy sources (RESs) has imposed new challenges in the operation of smart distribution networks. Changing the distribution networks indices is one of the untoward significant changes. In this paper, to improve the operational performance of smart distribution network, the application of electric spring (ES) as a new device in the power electronic revolution is proposed. Furthermore, the novel static model of the ES is presented and described in detail. In the next step, the effect of the presence of ES on distribution network indices in various scenarios has been studied. Finally, the suggested solution has been tested on 32-bus IEEE test microgrid as a distribution network by the GAMS software to analyze the potential and effectiveness of the ES in improving the microgrid indices. The results of the simulations verify the suggested solution completely by modifying the mentioned indices, and enhancing the conditions for the operation of the microgrid.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131780782","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849063
Muhammad R. Abdussami, H. Gabbar
The Emergency Power Supply (EPS) is an inevitable part for the reliability of a Nuclear Power Plant (NPP). In case of failure of the power supply to electrical equipment in the NPP, the backup EPS plays a vital role. This paper proposes an innovative approach, with Flywheel-based Fast Charging Station (FFCS) along with Micro Energy Grid (MEG), to confirm the continuous power supply to the electrical system during the emergency in NPP. The paper focuses on the emergency diesel generator and battery system, which are connected to the Class III and Class I power of the NPP respectively for emergency purpose. The proposed model will eliminate the drawbacks of the battery system and the diesel generator. The MEG can operate in both mode; grid-connected mode (normal mode) and islanded mode (emergency mode). In normal mode, the electricity will be generated, stored in the main grid via an energy storage system or supplied to the consumer end. Under the emergency condition, the MEG will be disconnected from the main grid and will be connected to the FFCS depending on the requirements. The simulation results intend to show the novelty of the proposed model.
{"title":"Flywheel-based Micro Energy Grid for Reliable Emergency Back-up Power for Nuclear Power Plant","authors":"Muhammad R. Abdussami, H. Gabbar","doi":"10.1109/SEST.2019.8849063","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849063","url":null,"abstract":"The Emergency Power Supply (EPS) is an inevitable part for the reliability of a Nuclear Power Plant (NPP). In case of failure of the power supply to electrical equipment in the NPP, the backup EPS plays a vital role. This paper proposes an innovative approach, with Flywheel-based Fast Charging Station (FFCS) along with Micro Energy Grid (MEG), to confirm the continuous power supply to the electrical system during the emergency in NPP. The paper focuses on the emergency diesel generator and battery system, which are connected to the Class III and Class I power of the NPP respectively for emergency purpose. The proposed model will eliminate the drawbacks of the battery system and the diesel generator. The MEG can operate in both mode; grid-connected mode (normal mode) and islanded mode (emergency mode). In normal mode, the electricity will be generated, stored in the main grid via an energy storage system or supplied to the consumer end. Under the emergency condition, the MEG will be disconnected from the main grid and will be connected to the FFCS depending on the requirements. The simulation results intend to show the novelty of the proposed model.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130612138","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849141
Paul Gerdun, N. Ahmed, Vinaykumar Vernekar, Martin Töpfer, H. Weber
It is expected that in the near future, the electrical power supply networks will be significantly revolutionized. Today's conventional power plant structures will give way to a novel, inertia independent (free from rotating masses) power plant system. Such power stations, called storage power plants, will possess storages for different generation speed together with power electronic converters. They will be able to integrate and store energy from renewable sources. Since such a system will not possess any flywheels or rotating masses, thus frequency control as utilized in conventional power plants will be redundant. All the control principles necessary involving spinning reserve, primary and secondary control depending on frequency will be substituted by a comprehensive angle control of the nodal voltages in the transmission and distribution network. However, to be deemed truly feasible, these storage power plants must be able to function efficiently when they are integrated with conventional power plants and renewable energy sources. Thus, in this paper, these power plants are connected with conventional thermal and hydroelectric power stations as well as wind power plants, in a single network, and their dynamic behavior is studied under nodal voltage angle control as the ancillary service.
{"title":"Dynamic Operation of a Storage Power Plant (SPP) with Voltage Angle Control as Ancillary Service","authors":"Paul Gerdun, N. Ahmed, Vinaykumar Vernekar, Martin Töpfer, H. Weber","doi":"10.1109/SEST.2019.8849141","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849141","url":null,"abstract":"It is expected that in the near future, the electrical power supply networks will be significantly revolutionized. Today's conventional power plant structures will give way to a novel, inertia independent (free from rotating masses) power plant system. Such power stations, called storage power plants, will possess storages for different generation speed together with power electronic converters. They will be able to integrate and store energy from renewable sources. Since such a system will not possess any flywheels or rotating masses, thus frequency control as utilized in conventional power plants will be redundant. All the control principles necessary involving spinning reserve, primary and secondary control depending on frequency will be substituted by a comprehensive angle control of the nodal voltages in the transmission and distribution network. However, to be deemed truly feasible, these storage power plants must be able to function efficiently when they are integrated with conventional power plants and renewable energy sources. Thus, in this paper, these power plants are connected with conventional thermal and hydroelectric power stations as well as wind power plants, in a single network, and their dynamic behavior is studied under nodal voltage angle control as the ancillary service.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"290 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114952652","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849099
Mario Useche Arteaga, A. Ruiz, M. Rivera
This paper proposes to modify the classic control of voltage source converters for photovoltaic generation and battery energy storage systems, using model predictive control for the outer-loop and the conventional vector oriented control for the inner loop, in order to improve the voltage profiles in weak distribution networks. The proposed approach combines the advantages of the conventional vector oriented control and the model predictive control. Simulations in Matlab/Simulink over a realistic weak distribution system, based on a Colombian primary feeder with deficit of reactive power, demonstrate the advantages of the proposed control.
{"title":"Control of Energy Storage and Photovoltaic Systems using Model Predictive Control","authors":"Mario Useche Arteaga, A. Ruiz, M. Rivera","doi":"10.1109/SEST.2019.8849099","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849099","url":null,"abstract":"This paper proposes to modify the classic control of voltage source converters for photovoltaic generation and battery energy storage systems, using model predictive control for the outer-loop and the conventional vector oriented control for the inner loop, in order to improve the voltage profiles in weak distribution networks. The proposed approach combines the advantages of the conventional vector oriented control and the model predictive control. Simulations in Matlab/Simulink over a realistic weak distribution system, based on a Colombian primary feeder with deficit of reactive power, demonstrate the advantages of the proposed control.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114975257","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849150
Per Aaslid, M. Belsnes, O. Fosso
Intermittent energy sources demand temporal storages to balance generation and load, and batteries stand out as an alternative. However, the lifetime is limited, and cycling depth affects the battery degradation rate. Current stochastic multi-stage methods lack proper representation of battery degradation. This paper proposes a stochastic multi-stage model for optimizing battery operation in a microgrid considering battery degradation with a piece-wise linear cost function with uncertain wind power production and load. The model is solved using Stochastic Dual Dynamic Programming (SDDP) and is demonstrated on a 4-bus test case with limited import and export capacity to illustrate the battery degradation cost's impacts on the battery cycling strategy. The results show that the importance of a stochastic method is more pronounced when battery degradation is modelled.
{"title":"Optimal microgrid operation considering battery degradation using stochastic dual dynamic programming","authors":"Per Aaslid, M. Belsnes, O. Fosso","doi":"10.1109/SEST.2019.8849150","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849150","url":null,"abstract":"Intermittent energy sources demand temporal storages to balance generation and load, and batteries stand out as an alternative. However, the lifetime is limited, and cycling depth affects the battery degradation rate. Current stochastic multi-stage methods lack proper representation of battery degradation. This paper proposes a stochastic multi-stage model for optimizing battery operation in a microgrid considering battery degradation with a piece-wise linear cost function with uncertain wind power production and load. The model is solved using Stochastic Dual Dynamic Programming (SDDP) and is demonstrated on a 4-bus test case with limited import and export capacity to illustrate the battery degradation cost's impacts on the battery cycling strategy. The results show that the importance of a stochastic method is more pronounced when battery degradation is modelled.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129576597","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849143
Frederik vom Scheidt, P. Staudt, Christof Weinhardt
As residential customers become a more integral part of the electricity system the importance of electricity tariffs increases. The widespread adoption of new, economically efficient tariffs for residential customers can yield substantial system benefits. However, in liberalized electricity markets tariffs are selected by each individual household. System-beneficial tariffs do not necessarily bring private benefits for each household. Therefore, it is important to enable households to make well-informed decisions about which tariff to select. Assistance for such decisions can come from adequate Decision Support Tools which have been called for from the European Commission. To this end we design a set of six tariffs, based on empirical data: four different time-of-use (TOU) tariffs, one real-time pricing (RTP) tariff, and a benchmark tariff with a flat, invariant price (Flat). Applying the tariffs to a consumption data set of more than 100,000 customers we find that for a small share of customers electricity bills vary substantially under different tariffs. We present and evaluate a naive approach which recommends an annual tariff to each household, based on information from one month. We find that the performance of this naive classifier differs strongly between tariffs. Finally, we assess the economic consequences of false tariff selection and find that overall economic risks are highest for the RTP tariff.
{"title":"Assessing the Economics of Residential Electricity Tariff Selection","authors":"Frederik vom Scheidt, P. Staudt, Christof Weinhardt","doi":"10.1109/SEST.2019.8849143","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849143","url":null,"abstract":"As residential customers become a more integral part of the electricity system the importance of electricity tariffs increases. The widespread adoption of new, economically efficient tariffs for residential customers can yield substantial system benefits. However, in liberalized electricity markets tariffs are selected by each individual household. System-beneficial tariffs do not necessarily bring private benefits for each household. Therefore, it is important to enable households to make well-informed decisions about which tariff to select. Assistance for such decisions can come from adequate Decision Support Tools which have been called for from the European Commission. To this end we design a set of six tariffs, based on empirical data: four different time-of-use (TOU) tariffs, one real-time pricing (RTP) tariff, and a benchmark tariff with a flat, invariant price (Flat). Applying the tariffs to a consumption data set of more than 100,000 customers we find that for a small share of customers electricity bills vary substantially under different tariffs. We present and evaluate a naive approach which recommends an annual tariff to each household, based on information from one month. We find that the performance of this naive classifier differs strongly between tariffs. Finally, we assess the economic consequences of false tariff selection and find that overall economic risks are highest for the RTP tariff.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131224173","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849025
Luis F. Ugarte, Fransk A. Puma, M. D. de Almeida
The interdependence of future distribution grids and communication networks creates the need to use tools capable of analyzing and solving problems of operation, control and monitoring of the electrical system. Therefore, it is very important to create co-simulation infrastructures to enable various types of analysis in electric power systems. Open Distribution System Simulator (OpenDSS) is an interesting alternative with potential benefits as COM automation, compiled dynamic link library, text scripting that provide the conditions for the development of a Distribution Management System (DMS) and its system applications. This document analyzes how OpenDSS plus a Driver Software, such as Matlab or Python, can become an adequate co-simulation infrastructure for education and research on power system analysis, such as State Estimation. The studies were conducted through the IEEE 13-bus test feeder under several operating conditions highlighting the benefits of a robust architecture.
{"title":"Co-Simulation Architecture: A Tool to Enable the State Estimator Application in Smart Grid Environment","authors":"Luis F. Ugarte, Fransk A. Puma, M. D. de Almeida","doi":"10.1109/SEST.2019.8849025","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849025","url":null,"abstract":"The interdependence of future distribution grids and communication networks creates the need to use tools capable of analyzing and solving problems of operation, control and monitoring of the electrical system. Therefore, it is very important to create co-simulation infrastructures to enable various types of analysis in electric power systems. Open Distribution System Simulator (OpenDSS) is an interesting alternative with potential benefits as COM automation, compiled dynamic link library, text scripting that provide the conditions for the development of a Distribution Management System (DMS) and its system applications. This document analyzes how OpenDSS plus a Driver Software, such as Matlab or Python, can become an adequate co-simulation infrastructure for education and research on power system analysis, such as State Estimation. The studies were conducted through the IEEE 13-bus test feeder under several operating conditions highlighting the benefits of a robust architecture.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"292 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132315933","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849083
Sasan Rafii-Tabrizi, J. Hadji-Minaglou, F. Scholzen, F. Capitanescu
This paper proposes a deterministic mixed integer linear programming model for the optimal operation of an energy system providing thermal and electrical energy for a residential and commercial nearly zero energy building. The space heating and space cooling demand of the buildings is simulated using a resistive-capacitive model within a quadratic program respectively. Thermal energy for space heating, space cooling and domestic hot water is buffered in thermal energy storage systems. A dual source heat pump provides thermal energy for space heating and domestic hot water, whereas space cooling is covered by an underground ice storage. The environmental energy sources of the heat pump are ice storage or wind infrared sensitive collectors. The collectors are further used to regenerate the ice storage. Further space heating demands are covered by a combined heat and power unit, which also produces electricity. Photovoltaic panels produce electrical energy which can be stored in a battery storage system. The electrical energy system is capable of selling and buying electricity from the public power grid. A mixed integer linear programming model is developed to minimise the operation cost of the combined commercial and residential nearly zero energy building over a scheduling horizon of 24h. The developed model is tested on two typical days, which are representative for the summer and winter season. Furthermore, it is investigated how external incentives such as varying electricity prices impact the optimal scheduling of the energy system.
{"title":"Optimal Operation of Nearly Zero Energy Buildings using Mixed Integer Linear Programming","authors":"Sasan Rafii-Tabrizi, J. Hadji-Minaglou, F. Scholzen, F. Capitanescu","doi":"10.1109/SEST.2019.8849083","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849083","url":null,"abstract":"This paper proposes a deterministic mixed integer linear programming model for the optimal operation of an energy system providing thermal and electrical energy for a residential and commercial nearly zero energy building. The space heating and space cooling demand of the buildings is simulated using a resistive-capacitive model within a quadratic program respectively. Thermal energy for space heating, space cooling and domestic hot water is buffered in thermal energy storage systems. A dual source heat pump provides thermal energy for space heating and domestic hot water, whereas space cooling is covered by an underground ice storage. The environmental energy sources of the heat pump are ice storage or wind infrared sensitive collectors. The collectors are further used to regenerate the ice storage. Further space heating demands are covered by a combined heat and power unit, which also produces electricity. Photovoltaic panels produce electrical energy which can be stored in a battery storage system. The electrical energy system is capable of selling and buying electricity from the public power grid. A mixed integer linear programming model is developed to minimise the operation cost of the combined commercial and residential nearly zero energy building over a scheduling horizon of 24h. The developed model is tested on two typical days, which are representative for the summer and winter season. Furthermore, it is investigated how external incentives such as varying electricity prices impact the optimal scheduling of the energy system.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130274049","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 : 2019-09-01DOI: 10.1109/SEST.2019.8849131
M. Daneshvar, B. Mohammadi-ivatloo, S. Asadi, K. Zare, A. Anvari‐Moghaddam
In recent decades, the rising penetration of various types of distributed energy resources has made interactions between all types of energy inevitable. In this respect, energy hubs are created with the aim of considering the interactions between multi-carrier energy systems throughout the smart grids. In this research, optimal scheduling of the multi-energy hubs is considered in the day-ahead market with the aim of minimizing the energy hub's cost. Because of the high usage of the clean energy production potential by employing the wind turbines and PV panels at each energy hub, the proposed model will mitigate the greenhouse gas emissions through reducing the operation of the gas-fired systems over the scheduling horizon. The combined cooling/heating and power system is also used as a backup unit for the stochastic producers to ensure energy supply with minimum load shedding. Moreover, electrical and thermal energy storage devices are also employed for storing energy during time intervals when there is a large amount of clean and free energy production. The Monte-Carlo simulation approach is used for modeling the uncertain behaviors of the stochastic producers and fast forward selection method is also used for the scenario reduction process. The flexibility of the energy demand is also investigated using demand response programs. In order to validate the effectiveness of the proposed model, IEEE 10-bus standard test system integrated with distributed energy resources is used. Simulation results demonstrate the applicability and usefulness of the proposed model in the energy management of multi energy hubs.
{"title":"Optimal Day-Ahead Scheduling of the Renewable Based Energy Hubs Considering Demand Side Energy Management","authors":"M. Daneshvar, B. Mohammadi-ivatloo, S. Asadi, K. Zare, A. Anvari‐Moghaddam","doi":"10.1109/SEST.2019.8849131","DOIUrl":"https://doi.org/10.1109/SEST.2019.8849131","url":null,"abstract":"In recent decades, the rising penetration of various types of distributed energy resources has made interactions between all types of energy inevitable. In this respect, energy hubs are created with the aim of considering the interactions between multi-carrier energy systems throughout the smart grids. In this research, optimal scheduling of the multi-energy hubs is considered in the day-ahead market with the aim of minimizing the energy hub's cost. Because of the high usage of the clean energy production potential by employing the wind turbines and PV panels at each energy hub, the proposed model will mitigate the greenhouse gas emissions through reducing the operation of the gas-fired systems over the scheduling horizon. The combined cooling/heating and power system is also used as a backup unit for the stochastic producers to ensure energy supply with minimum load shedding. Moreover, electrical and thermal energy storage devices are also employed for storing energy during time intervals when there is a large amount of clean and free energy production. The Monte-Carlo simulation approach is used for modeling the uncertain behaviors of the stochastic producers and fast forward selection method is also used for the scenario reduction process. The flexibility of the energy demand is also investigated using demand response programs. In order to validate the effectiveness of the proposed model, IEEE 10-bus standard test system integrated with distributed energy resources is used. Simulation results demonstrate the applicability and usefulness of the proposed model in the energy management of multi energy hubs.","PeriodicalId":158839,"journal":{"name":"2019 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131345215","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：