The Experts below are selected from a list of 138399 Experts worldwide ranked by ideXlab platform
J L Zhen - One of the best experts on this subject based on the ideXlab platform.
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energy water nexus planning of regional electric Power System within an inexact optimization model in tangshan city china
Journal of Cleaner Production, 2020Co-Authors: J L Zhen, G H Huang, Xueli Liu, Zhengping LiuAbstract:Abstract Under the increasingly serious energy and water resources crisis, the correlation between two resources has become more and more close. Promoting the sustainable development of energy and water resources has been an inevitable choice for regional energy System planning. In this study, a hybrid interval two-stage fuzzy credibility constrained programming (ITFCP) model is developed for supporting energy-water nexus System Management. ITFCP can explicitly address System uncertainties presented as probability distributions, fuzzy sets, and intervals, as well as dual dynamics through the concept of solutions with interval membership function. The method could provide effective linkages between predefined policies and economic penalties as well as System economy and risk. Then, ITFCP is applied to electric Power System Management under considering energy-water nexus in Tangshan City, which is a typical resource-based, high pollution, and water-deficient region in China. Multiple scenarios of different credibility levels about water availability are designed. Results disclosed that coal-fired Power and imported electricity would play primary role in meeting tremendous electricity demand under the current situation. Results also revealed that the total water consumption control would be an effective way to accelerate electric Power structural adjustment, protect energy and water resources as well as improve atmospheric environment. These findings are valuable for decision makers to gain in-depth analysis for more reasonable and applicable development patterns within a complex energy-water System.
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electric Power System planning with renewable energy accommodation for supporting the sustainable development of tangshan city china
Journal of Cleaner Production, 2016Co-Authors: J L Zhen, G H Huang, Suhua WangAbstract:Abstract In this study, considering break the original energy structure dominated by coal and make the most use of renewable energy in the future, an inexact stochastic robust mixed-integer programming (ITSRMP) method was developed for supporting regional electric Power System Management in Tangshan City, China. The developed method incorporated interval-parameter programming (IPP), stochastic robust optimization (SRO), two-stage stochastic programming (TSP), and mixed integer programming (MIP) within a general optimization framework to reflect uncertainties expressed as interval values and probability distributions in the regional electric Power System. Three scenarios corresponding to different subsidy price levels and three cases associated with different pollutants emission reduction levels were designed. The electricity generation schemes, facility-expansion, pollutant emission, and System cost considering the subsidy policy and air pollution mitigation control had been obtained. The results indicated that subsidy policy would exert an important influence on the development of Tangshan's electric Power System, which can reduce the cost advantage of conventional Power generation and enhance the development enthusiasm of renewable Power generation to Power enterprises. In detail, the electricity generation amount of renewable energy would increase with the improvement of subsidy price level. Moreover, decision makers could identify the possible policy implementations and enforcements under considering the trade-off among System economy, security and environmental objectives. The modeling results were valuable for promoting new energy accommodation and supporting the sustainable development of social economy.
Eric Wai Ming Lee - One of the best experts on this subject based on the ideXlab platform.
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Short-term prediction of photovoltaic energy generation by intelligent approach
Energy and Buildings, 2012Co-Authors: Stanley K.h. Chow, Eric Wai Ming LeeAbstract:Abstract Population growth and quickly depleting fossil fuel reserves are creating demand for the development and use of renewable energy resources such as solar energy. The evaluation and forecasting of energy demands have become concerns for facility managers, and predicting energy generation plays a critical role in Power-System Management, scheduling, and dispatch operations. A reliable energy supply forecast helps to prevent unexpected loads and provides vital information for decisions made on energy generation and purchase. However, study of energy generation prediction by the photovoltaic (PV) System has been limited over the years, especially concerning short-term predictions. This study will adopt the artificial neural network (ANN) to mimic the nonlinear correlation between the metrological parameters and energy generated by the PV System. It aims to find that short-term prediction performance is comparable with real-time prediction performance when ahead solar angles are applied to the predictions.
G H Huang - One of the best experts on this subject based on the ideXlab platform.
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energy water nexus planning of regional electric Power System within an inexact optimization model in tangshan city china
Journal of Cleaner Production, 2020Co-Authors: J L Zhen, G H Huang, Xueli Liu, Zhengping LiuAbstract:Abstract Under the increasingly serious energy and water resources crisis, the correlation between two resources has become more and more close. Promoting the sustainable development of energy and water resources has been an inevitable choice for regional energy System planning. In this study, a hybrid interval two-stage fuzzy credibility constrained programming (ITFCP) model is developed for supporting energy-water nexus System Management. ITFCP can explicitly address System uncertainties presented as probability distributions, fuzzy sets, and intervals, as well as dual dynamics through the concept of solutions with interval membership function. The method could provide effective linkages between predefined policies and economic penalties as well as System economy and risk. Then, ITFCP is applied to electric Power System Management under considering energy-water nexus in Tangshan City, which is a typical resource-based, high pollution, and water-deficient region in China. Multiple scenarios of different credibility levels about water availability are designed. Results disclosed that coal-fired Power and imported electricity would play primary role in meeting tremendous electricity demand under the current situation. Results also revealed that the total water consumption control would be an effective way to accelerate electric Power structural adjustment, protect energy and water resources as well as improve atmospheric environment. These findings are valuable for decision makers to gain in-depth analysis for more reasonable and applicable development patterns within a complex energy-water System.
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electric Power System planning with renewable energy accommodation for supporting the sustainable development of tangshan city china
Journal of Cleaner Production, 2016Co-Authors: J L Zhen, G H Huang, Suhua WangAbstract:Abstract In this study, considering break the original energy structure dominated by coal and make the most use of renewable energy in the future, an inexact stochastic robust mixed-integer programming (ITSRMP) method was developed for supporting regional electric Power System Management in Tangshan City, China. The developed method incorporated interval-parameter programming (IPP), stochastic robust optimization (SRO), two-stage stochastic programming (TSP), and mixed integer programming (MIP) within a general optimization framework to reflect uncertainties expressed as interval values and probability distributions in the regional electric Power System. Three scenarios corresponding to different subsidy price levels and three cases associated with different pollutants emission reduction levels were designed. The electricity generation schemes, facility-expansion, pollutant emission, and System cost considering the subsidy policy and air pollution mitigation control had been obtained. The results indicated that subsidy policy would exert an important influence on the development of Tangshan's electric Power System, which can reduce the cost advantage of conventional Power generation and enhance the development enthusiasm of renewable Power generation to Power enterprises. In detail, the electricity generation amount of renewable energy would increase with the improvement of subsidy price level. Moreover, decision makers could identify the possible policy implementations and enforcements under considering the trade-off among System economy, security and environmental objectives. The modeling results were valuable for promoting new energy accommodation and supporting the sustainable development of social economy.
Suhua Wang - One of the best experts on this subject based on the ideXlab platform.
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electric Power System planning with renewable energy accommodation for supporting the sustainable development of tangshan city china
Journal of Cleaner Production, 2016Co-Authors: J L Zhen, G H Huang, Suhua WangAbstract:Abstract In this study, considering break the original energy structure dominated by coal and make the most use of renewable energy in the future, an inexact stochastic robust mixed-integer programming (ITSRMP) method was developed for supporting regional electric Power System Management in Tangshan City, China. The developed method incorporated interval-parameter programming (IPP), stochastic robust optimization (SRO), two-stage stochastic programming (TSP), and mixed integer programming (MIP) within a general optimization framework to reflect uncertainties expressed as interval values and probability distributions in the regional electric Power System. Three scenarios corresponding to different subsidy price levels and three cases associated with different pollutants emission reduction levels were designed. The electricity generation schemes, facility-expansion, pollutant emission, and System cost considering the subsidy policy and air pollution mitigation control had been obtained. The results indicated that subsidy policy would exert an important influence on the development of Tangshan's electric Power System, which can reduce the cost advantage of conventional Power generation and enhance the development enthusiasm of renewable Power generation to Power enterprises. In detail, the electricity generation amount of renewable energy would increase with the improvement of subsidy price level. Moreover, decision makers could identify the possible policy implementations and enforcements under considering the trade-off among System economy, security and environmental objectives. The modeling results were valuable for promoting new energy accommodation and supporting the sustainable development of social economy.
Haijiang Li - One of the best experts on this subject based on the ideXlab platform.
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Towards the next generation of smart grids: Semantic and holonic multi-agent Management of distributed energy resources
Renewable and Sustainable Energy Reviews, 2017Co-Authors: Shaun Howell, Jean-laurent Hippolyte, Yacine Rezgui, Bejay Jayan, Haijiang LiAbstract:The energy landscape is experiencing accelerating change; centralized energy Systems are being decarbonized, and transitioning towards distributed energy Systems, facilitated by advances in Power System Management and information and communication technologies. This paper elaborates on these generations of energy Systems by critically reviewing relevant authoritative literature. This includes a discussion of modern concepts such as ‘smart grid’, ‘microgrid’, ‘virtual Power plant’ and ‘multi-energy System’, and the relationships between them, as well as the trends towards distributed intelligence and interoperability. Each of these emerging urban energy concepts holds merit when applied within a centralized grid paradigm, but very little research applies these approaches within the emerging energy landscape typified by a high penetration of distributed energy resources, prosumers (consumers and producers), interoperability, and big data. Given the ongoing boom in these fields, this will lead to new challenges and opportunities as the status-quo of energy Systems changes dramatically. We argue that a new generation of holonic energy Systems is required to orchestrate the interplay between these dense, diverse and distributed energy components. The paper therefore contributes a description of holonic energy Systems and the implicit research required towards sustainability and resilience in the imminent energy landscape. This promotes the Systemic features of autonomy, belonging, connectivity, diversity and emergence, and balances global and local System objectives, through adaptive control topologies and demand responsive energy Management. Future research avenues are identified to support this transition regarding interoperability, secure distributed control and a System of Systems approach.