Pub Date : 2017-12-01DOI: 10.1109/SGC.2017.8308862
M. Ataei, S. Malekshah, Mohsen Ghanbarnejad, A. J. Irani
Biomass distributed energy resources are also known as waste-to-energy plants. The heat from the combustion process is used to generate superheated steam in boilers. Municipal solid waste incineration is a greenhouse gas emitter; however, if greenhouse gas emitter reductions, achieved by accounting for waste-to-energy, exceed greenhouse gas emitter emissions, incineration can be considered as a net greenhouse gas emitter reducer. A metropolitan city like Tehran of Iran has the sufficient potential to construct biomass distributed energy resources. In this paper, the technical report of implementation, operation and economical assessment of waste incineration plant of Tehran as a practical case study is presented. The plant nominal capacity is 3MW that is located in the suburb of Tehran in Kahrizak region. The paper approaches are divided into three parts of economic, environmental and technical studies that the main factors of each section are studied. In this paper, the furnace technology of the plant is based on Pyrolysis incinerator that has the optimum combustion rather than other technologies. In addition, the installed filter is poly tetra flour ethylene that could observe 99.8% remaining dusts in the output gas that effect directly to improve the environmental standards.
{"title":"Implementation, operation and economical assessment of the first 3MW biomass distributed energy resource: A case study of Iran","authors":"M. Ataei, S. Malekshah, Mohsen Ghanbarnejad, A. J. Irani","doi":"10.1109/SGC.2017.8308862","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308862","url":null,"abstract":"Biomass distributed energy resources are also known as waste-to-energy plants. The heat from the combustion process is used to generate superheated steam in boilers. Municipal solid waste incineration is a greenhouse gas emitter; however, if greenhouse gas emitter reductions, achieved by accounting for waste-to-energy, exceed greenhouse gas emitter emissions, incineration can be considered as a net greenhouse gas emitter reducer. A metropolitan city like Tehran of Iran has the sufficient potential to construct biomass distributed energy resources. In this paper, the technical report of implementation, operation and economical assessment of waste incineration plant of Tehran as a practical case study is presented. The plant nominal capacity is 3MW that is located in the suburb of Tehran in Kahrizak region. The paper approaches are divided into three parts of economic, environmental and technical studies that the main factors of each section are studied. In this paper, the furnace technology of the plant is based on Pyrolysis incinerator that has the optimum combustion rather than other technologies. In addition, the installed filter is poly tetra flour ethylene that could observe 99.8% remaining dusts in the output gas that effect directly to improve the environmental standards.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"297 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122195805","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308854
Mohammd Ghaljehei, M. Golkar
High penetration of wind power increases the generation uncertainty in power systems. Large-scale energy storage systems, such as compressed air energy storage (CAES), can accommodate this uncertainty properly, if it is scheduled optimally. In this paper, a proposed stochastic AC-security constrained unit commitment (AC-SCUC) is performed considering CAES, wind power generation and thermal units, and a techno-economic assessment is conducted in the proposed stochastic methodology. A two-stage stochastic programming is employed to handle uncertainty of wind power generation. As the integration of CAES and wind power uncertainty affect voltage issue of power system, the techno-economic assessment is carried out in the proposed stochastic methodology to shed light on the effects of optimal generation scheduling on the static voltage stability. Due to its less computation cost, the wind power uncertainty is modeled using scenario-based approach. The AC-SCUC problem and CAES scheduling are considered as an optimization problem which is solved using mixed-integer non-linear programming (MINLP) approach. The proposed stochastic methodology is applied to a modified IEEE 30 bus test system.
{"title":"Effect of optimal generation scheduling of compressed air energy storage and wind power generation on economic and technical issues","authors":"Mohammd Ghaljehei, M. Golkar","doi":"10.1109/SGC.2017.8308854","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308854","url":null,"abstract":"High penetration of wind power increases the generation uncertainty in power systems. Large-scale energy storage systems, such as compressed air energy storage (CAES), can accommodate this uncertainty properly, if it is scheduled optimally. In this paper, a proposed stochastic AC-security constrained unit commitment (AC-SCUC) is performed considering CAES, wind power generation and thermal units, and a techno-economic assessment is conducted in the proposed stochastic methodology. A two-stage stochastic programming is employed to handle uncertainty of wind power generation. As the integration of CAES and wind power uncertainty affect voltage issue of power system, the techno-economic assessment is carried out in the proposed stochastic methodology to shed light on the effects of optimal generation scheduling on the static voltage stability. Due to its less computation cost, the wind power uncertainty is modeled using scenario-based approach. The AC-SCUC problem and CAES scheduling are considered as an optimization problem which is solved using mixed-integer non-linear programming (MINLP) approach. The proposed stochastic methodology is applied to a modified IEEE 30 bus test system.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115154882","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308877
Emad Nazerian, Sina Gharebaghi, A. Safdarian
Distribution network reconfiguration as a technique for reducing network losses and enhancing voltage profile has attracted attention of many researchers. In spite of impacts network reconfiguration can have on power quality indices, the potentials have not been studied enough. To fill the gap, this paper presents a method to determine optimum network configuration considering voltage profile, network losses, and total harmonic distortion (THD). The proposed method also vouches for radial structure of the network, supplying all loads, and maintaining voltages and currents within allowable bounds. Since network reconfiguration problem is a combinatorial optimization problem, a meta-heuristic method is applied here. The method is based on a modified version of selective particle swarm optimization (PSO). To investigate the effectiveness of the proposed method, it is applied to the IEEE 69-bus standard test system and the results are compared with those of genetic algorithm (GA) and ant colony optimization (ACO).
{"title":"Optimal distribution network reconfiguration considering power quality issues","authors":"Emad Nazerian, Sina Gharebaghi, A. Safdarian","doi":"10.1109/SGC.2017.8308877","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308877","url":null,"abstract":"Distribution network reconfiguration as a technique for reducing network losses and enhancing voltage profile has attracted attention of many researchers. In spite of impacts network reconfiguration can have on power quality indices, the potentials have not been studied enough. To fill the gap, this paper presents a method to determine optimum network configuration considering voltage profile, network losses, and total harmonic distortion (THD). The proposed method also vouches for radial structure of the network, supplying all loads, and maintaining voltages and currents within allowable bounds. Since network reconfiguration problem is a combinatorial optimization problem, a meta-heuristic method is applied here. The method is based on a modified version of selective particle swarm optimization (PSO). To investigate the effectiveness of the proposed method, it is applied to the IEEE 69-bus standard test system and the results are compared with those of genetic algorithm (GA) and ant colony optimization (ACO).","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116502999","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308833
M. Shafiekhani, A. Badri, Farshad Khavari
Today, with the reduced fossil fuel resources and increased environmental concerns, considering the increased use of renewable energy sources in power grids appears to be essential given the great benefits of these resources. The virtual power plant is an extensive energy management system to gather the capacity of interruptible loads, storage devices and distributed products to provide support services for the system and the energy marketing. The main objective of this paper is to provide a method for an optimal virtual power plant bidding strategy considering rivals in a joint day-ahead and balancing market. To this end, a bi-level mathematical optimization model with equilibrium constraints is provided. The first level of this model includes the maximization of the virtual power plant profits, while its second level involves maximizing the level of social welfare. The bi-level model is converted to a Mixed-Integer Linear Programming model using the theory of duality and Karush-Kuhn-Tucker (KKT) optimization conditions. The mentioned model is tested on the Standard IEEE 24-Bus network, which results indicated its effectiveness.
{"title":"A Bi-level model for strategic bidding of virtual power plant in day-ahead and balancing market","authors":"M. Shafiekhani, A. Badri, Farshad Khavari","doi":"10.1109/SGC.2017.8308833","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308833","url":null,"abstract":"Today, with the reduced fossil fuel resources and increased environmental concerns, considering the increased use of renewable energy sources in power grids appears to be essential given the great benefits of these resources. The virtual power plant is an extensive energy management system to gather the capacity of interruptible loads, storage devices and distributed products to provide support services for the system and the energy marketing. The main objective of this paper is to provide a method for an optimal virtual power plant bidding strategy considering rivals in a joint day-ahead and balancing market. To this end, a bi-level mathematical optimization model with equilibrium constraints is provided. The first level of this model includes the maximization of the virtual power plant profits, while its second level involves maximizing the level of social welfare. The bi-level model is converted to a Mixed-Integer Linear Programming model using the theory of duality and Karush-Kuhn-Tucker (KKT) optimization conditions. The mentioned model is tested on the Standard IEEE 24-Bus network, which results indicated its effectiveness.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126428076","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308879
Sina Gharebaghi, M. Izadi, A. Safdarian
Distribution networks are designed in loop structure, while they are operated as radial networks. In this regard, the location of normally open (NO) switches is usually determined by either minimizing real power losses or maximizing the reliability level. However, considering both losses and reliability in the decision making procedure may lead to a better solution. To do so, this paper proposes a mathematical model to find the optimal configuration of NO switches such that losses and reliability are optimized. The multi-objective model is scrutinized via weighted sum approach to achieve a single-objective model. The model is formulated in mixed integer quadratically constrained programming (MIQCP) format which can be easily solved in an effective run time. The effectiveness of the model is revealed through various scenarios and sensitivity analyses by simulating a real Finnish distribution network.
{"title":"Optimal network configuration considering network losses and service reliability","authors":"Sina Gharebaghi, M. Izadi, A. Safdarian","doi":"10.1109/SGC.2017.8308879","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308879","url":null,"abstract":"Distribution networks are designed in loop structure, while they are operated as radial networks. In this regard, the location of normally open (NO) switches is usually determined by either minimizing real power losses or maximizing the reliability level. However, considering both losses and reliability in the decision making procedure may lead to a better solution. To do so, this paper proposes a mathematical model to find the optimal configuration of NO switches such that losses and reliability are optimized. The multi-objective model is scrutinized via weighted sum approach to achieve a single-objective model. The model is formulated in mixed integer quadratically constrained programming (MIQCP) format which can be easily solved in an effective run time. The effectiveness of the model is revealed through various scenarios and sensitivity analyses by simulating a real Finnish distribution network.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124909005","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308876
M. Mousavi, A. Ranjbar, A. Safdarian
Electric distribution system is one of the most important parts of power systems owing to delivering electricity to consumers. The major amount of losses in a power system is in distribution level. Optimal distributed generation (DG) placement and sizing have a significant effect on power loss reduction in distribution systems. In this paper, a mixed integer conic programming (MICP) approach is presented to solve the problem of DG placement, sizing, and hourly generation with the aim of reducing power loss and costs in radial distribution systems. The costs include both investment and operational costs of DGs. Hourly load variations are considered in the model. To verify the effectiveness of the proposed solution approach, studies are carried out on the IEEE 33-bus distribution test system.
{"title":"Optimal DG placement and sizing based on MICP in radial distribution networks","authors":"M. Mousavi, A. Ranjbar, A. Safdarian","doi":"10.1109/SGC.2017.8308876","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308876","url":null,"abstract":"Electric distribution system is one of the most important parts of power systems owing to delivering electricity to consumers. The major amount of losses in a power system is in distribution level. Optimal distributed generation (DG) placement and sizing have a significant effect on power loss reduction in distribution systems. In this paper, a mixed integer conic programming (MICP) approach is presented to solve the problem of DG placement, sizing, and hourly generation with the aim of reducing power loss and costs in radial distribution systems. The costs include both investment and operational costs of DGs. Hourly load variations are considered in the model. To verify the effectiveness of the proposed solution approach, studies are carried out on the IEEE 33-bus distribution test system.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132051135","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 : 2017-12-01DOI: 10.1109/sgc.2017.8308849
H. Zeynal, Sima Ahmadpour
The edge of technology has yet to come at a very sophisticated level where hardware and software are integrated to form a sturdy system. High efficiently, self-reliance and self-healing are of main concerns when age of smart grids appeared. Smart grids play a crucial role in delivering seamless power supply efficiently with higher resiliency. However, the mellifluous operation of this grid, as a physical system, is subjugated by a cyborg network which contains data communication devices and it associated protocols. The resultant system which is a two coexistent incongruous network introduces a plethora of operational hurdles by far the interdependency that is a thorny issue. This work attempts simulating the codependent operation of both network elements when executing as a smart grid. To facilitate the modeling and analysis, a GUI tool is developed to make the simulation user-friendly and make the initial promises that every proposition towards optimizing smart grid has to take into account co-optimization of both networks elements.
{"title":"Cyber-physical interdependency in smart grid","authors":"H. Zeynal, Sima Ahmadpour","doi":"10.1109/sgc.2017.8308849","DOIUrl":"https://doi.org/10.1109/sgc.2017.8308849","url":null,"abstract":"The edge of technology has yet to come at a very sophisticated level where hardware and software are integrated to form a sturdy system. High efficiently, self-reliance and self-healing are of main concerns when age of smart grids appeared. Smart grids play a crucial role in delivering seamless power supply efficiently with higher resiliency. However, the mellifluous operation of this grid, as a physical system, is subjugated by a cyborg network which contains data communication devices and it associated protocols. The resultant system which is a two coexistent incongruous network introduces a plethora of operational hurdles by far the interdependency that is a thorny issue. This work attempts simulating the codependent operation of both network elements when executing as a smart grid. To facilitate the modeling and analysis, a GUI tool is developed to make the simulation user-friendly and make the initial promises that every proposition towards optimizing smart grid has to take into account co-optimization of both networks elements.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126898128","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308866
Sajad A. Ansari, S. Hosseinian, J. Moghani
Under voltage rise/drop conditions, grid-connected distributed generation systems have to be disconnected from the grid. However, due to the increasing number of grid-connected PV systems, the future photovoltaic (PV) systems should become more active and support low-voltage ride-through (LVRT) capability. The aim of this paper is to show a new advantage of the flyback inverter under boundary conduction mode (BCM) for supporting LVRT capability without using any auxiliary control system and any limitation in designing of the parameters. The detailed operation of the flyback inverter under increasing and decreasing conditions of the grid voltage for BCM operation are presented. Finally, simulation results based on the flyback inverter under grid faults are demonstrated. The results elucidate that the flyback inverter under BCM operation can support LVRT capability for Ac module application in distributed generation systems, without any limitation in parameters design and any additional control system.
{"title":"Low-voltage ride-through capability of flyback inverter under BCM operation for AC module applications","authors":"Sajad A. Ansari, S. Hosseinian, J. Moghani","doi":"10.1109/SGC.2017.8308866","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308866","url":null,"abstract":"Under voltage rise/drop conditions, grid-connected distributed generation systems have to be disconnected from the grid. However, due to the increasing number of grid-connected PV systems, the future photovoltaic (PV) systems should become more active and support low-voltage ride-through (LVRT) capability. The aim of this paper is to show a new advantage of the flyback inverter under boundary conduction mode (BCM) for supporting LVRT capability without using any auxiliary control system and any limitation in designing of the parameters. The detailed operation of the flyback inverter under increasing and decreasing conditions of the grid voltage for BCM operation are presented. Finally, simulation results based on the flyback inverter under grid faults are demonstrated. The results elucidate that the flyback inverter under BCM operation can support LVRT capability for Ac module application in distributed generation systems, without any limitation in parameters design and any additional control system.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"430 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115956177","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308873
Sahand Liasi, S. Bathaee
The classical modus operandi of electric energy systems try to keep demand and supply balanced at all times, but this cause high generation prices at peak hours and needs huge power capacity to comply peak demand, while in other hours this capacity remains useless. To avoid these issues, many researchers focus on peak shaving and demand response activities to improve system efficiency and reliability. In this paper, a game theory based method has been developed and simulated to show proficiency of managing ventilation system and simultaneously connecting electric vehicles to microgrid (V2G) to provide various demand response services and peak shaving with focus on optimizing generation cost and emission together.
{"title":"Optimizing microgrid using demand response and electric vehicles connection to microgrid","authors":"Sahand Liasi, S. Bathaee","doi":"10.1109/SGC.2017.8308873","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308873","url":null,"abstract":"The classical modus operandi of electric energy systems try to keep demand and supply balanced at all times, but this cause high generation prices at peak hours and needs huge power capacity to comply peak demand, while in other hours this capacity remains useless. To avoid these issues, many researchers focus on peak shaving and demand response activities to improve system efficiency and reliability. In this paper, a game theory based method has been developed and simulated to show proficiency of managing ventilation system and simultaneously connecting electric vehicles to microgrid (V2G) to provide various demand response services and peak shaving with focus on optimizing generation cost and emission together.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"99 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114134475","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 : 2017-12-01DOI: 10.1109/SGC.2017.8308837
Farshad Khavari, A. Badri, Ali Zangeneh, M. Shafiekhani
Various models are proposed to manage multi-microgrid energy systems. Centralized and decentralized are two basic models, to this end. This paper compares these two energy-management models of multi-microgrid systems for day-ahead scheduling. This comparison is done for the time of calculation, the benefit of microgrids and the state of the Distributed Energy Resources(DER) in microgrids when happen predetermined islanding mode. Simulation and unit commitment is coded and solved by mixed integer programming (MIP) solver CPLEX in GAMS.
{"title":"A comparison of centralized and decentralized energy-management models of multi-microgrid systems","authors":"Farshad Khavari, A. Badri, Ali Zangeneh, M. Shafiekhani","doi":"10.1109/SGC.2017.8308837","DOIUrl":"https://doi.org/10.1109/SGC.2017.8308837","url":null,"abstract":"Various models are proposed to manage multi-microgrid energy systems. Centralized and decentralized are two basic models, to this end. This paper compares these two energy-management models of multi-microgrid systems for day-ahead scheduling. This comparison is done for the time of calculation, the benefit of microgrids and the state of the Distributed Energy Resources(DER) in microgrids when happen predetermined islanding mode. Simulation and unit commitment is coded and solved by mixed integer programming (MIP) solver CPLEX in GAMS.","PeriodicalId":346749,"journal":{"name":"2017 Smart Grid Conference (SGC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130698782","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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