This paper presents a web-based system to predict the electricity prices.The proposed system captures the geographical location,weather forecast,and oil price for one week ahead.The captured parameters are fed to a fu...This paper presents a web-based system to predict the electricity prices.The proposed system captures the geographical location,weather forecast,and oil price for one week ahead.The captured parameters are fed to a fuzzy-logic-based algorithm to calculate electric energy prices.Based on predicted electricity prices,consumers can turn ON/OFF or reschedule operations of their home appliances to reduce their electricity bill.The proposed algorithm was developed and hosted in a utility server(U-server).On the consumer side,a home gateway(H-gateway),and a monitoring and control system was designed,built,and tested by using a single chip microcontroller.展开更多
Inverter-dominated isolated/islanded microgrids(IDIMGs)lack infinite buses and have low inertia,resulting in higher sensitivity to disturbances and reduced stability compared to grid-tied systems.Enhanc-ing the resili...Inverter-dominated isolated/islanded microgrids(IDIMGs)lack infinite buses and have low inertia,resulting in higher sensitivity to disturbances and reduced stability compared to grid-tied systems.Enhanc-ing the resilience of IDIMGs can be achieved by maxim-izing the system loadability and/or mitigating the expected disturbances such as line switching operations.This paper proposes a two-stage framework based on the deployment of mobile energy storage(MES)to enhance the resilience of IDIMGs.In the first stage,the network configuration and deployment of MES are optimized to maximize the system loadability.The proposed formulation for this stage is a stochastic multi-period mixed-integer nonlinear program(MINLP)that maximizes a weighted sum of minimax loadabilities.In the second stage,transitional locations of MES,line-exchange execution sequence,and droop control of dispatchable sources are jointly optimized to mitigate line-switching disturbances that occur when transitioning to the new network configuration obtained in the first stage.The second stage model is a multi-objective MINLP.The proposed models are solved within the gen-eral algebraic modeling system(GAMS),utilizing a mod-ified IEEE 33-bus system.Simulations are conducted to assess the significance of each proposed model,and the results reveal remarkable improvements in system loadability with the utilization of the first-stage model and significant reductions in the total switched power with the adoption of the second-stage model.展开更多
Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can...Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.展开更多
基金supported by the American University of Sharjah under Master Project COE-699-F15S16
文摘This paper presents a web-based system to predict the electricity prices.The proposed system captures the geographical location,weather forecast,and oil price for one week ahead.The captured parameters are fed to a fuzzy-logic-based algorithm to calculate electric energy prices.Based on predicted electricity prices,consumers can turn ON/OFF or reschedule operations of their home appliances to reduce their electricity bill.The proposed algorithm was developed and hosted in a utility server(U-server).On the consumer side,a home gateway(H-gateway),and a monitoring and control system was designed,built,and tested by using a single chip microcontroller.
文摘Inverter-dominated isolated/islanded microgrids(IDIMGs)lack infinite buses and have low inertia,resulting in higher sensitivity to disturbances and reduced stability compared to grid-tied systems.Enhanc-ing the resilience of IDIMGs can be achieved by maxim-izing the system loadability and/or mitigating the expected disturbances such as line switching operations.This paper proposes a two-stage framework based on the deployment of mobile energy storage(MES)to enhance the resilience of IDIMGs.In the first stage,the network configuration and deployment of MES are optimized to maximize the system loadability.The proposed formulation for this stage is a stochastic multi-period mixed-integer nonlinear program(MINLP)that maximizes a weighted sum of minimax loadabilities.In the second stage,transitional locations of MES,line-exchange execution sequence,and droop control of dispatchable sources are jointly optimized to mitigate line-switching disturbances that occur when transitioning to the new network configuration obtained in the first stage.The second stage model is a multi-objective MINLP.The proposed models are solved within the gen-eral algebraic modeling system(GAMS),utilizing a mod-ified IEEE 33-bus system.Simulations are conducted to assess the significance of each proposed model,and the results reveal remarkable improvements in system loadability with the utilization of the first-stage model and significant reductions in the total switched power with the adoption of the second-stage model.
基金This work was made possible through funding from the Digital Agriculture Knowledge and Information System(DAKIS)Project(ID:FKZ 031B0729A)financed by the German Federal Ministry of Education and Research(BMBF).Sincere thanks to Amir Armaghan for his amazing sketches on the DAKIS GUI,enabling us to approach the work from the user's perspective.We acknowledge the valuable contributions of Stefan Zachaeus,Sebastian Möller and Nils Niemann on the design of the DAKIS back end.We thank the many other members of the DAKIS crew that one way or another contribute expertise and input to the development of the DAKIS.
文摘Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity,biodiversity,and the provision of ecosystem services.The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems.We present the Digital Agricultural Knowledge and Information System(DAKIS)to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture.To develop the DAKIS,we specified,together with stakeholders,requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools.The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity,the capacity to foster communication and cooperation between farmers and other actors,and the ability to link multiple spatiotemporal scales and sustainability levels.To overcome these challenges,the DAKIS provides a digital platform to support farmers'decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources.The approach integrates remote and in situ sensors,artificial intelligence,modelling,stakeholder-stated demand for biodiversity and ecosystem services,and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design,including natural and agronomic factors,economic and policy considerations,and socio-cultural preferences and settings.Ultimately,the DAKIS embeds the consideration of ecosystem services,biodiversity,and sustainability into farmers'decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers'objectives and societal demands.
