The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-pha...The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-phase flow. The buildup type curves or buildup behavior could be obtained through the solution by using su-perposition. But a new outer boundary condition for variable pressure boundary must be introduced to obtain the correct pressure buildup solutions by superposition. A technique is shown to determine the deviation time from the infinite-acting semilog radial flow stabilization in the derivatives of pressure, which is calculated with respect to and plotted vs. shut-in time. Field examples are given to illustrate the use of the proposed method for analyzing transient pressure data from a well located in a multi-well water-injection reservoir. An adaptive genetic algorithm-based method is used to match the pressure and pressure derivative data to estimate reservoir parameters. The validity and applicability of the proposed method are also demonstrated through the examples.展开更多
The main objective of this paper is to show an overview analysis of market power issues.Market power reflects the scarcity of power supply.It is the ability of a particular seller or group of sellers to maintain price...The main objective of this paper is to show an overview analysis of market power issues.Market power reflects the scarcity of power supply.It is the ability of a particular seller or group of sellers to maintain prices profitably above competitive levels for a significant period of time.Because the electric power system has its own characteristics that are different to other economic systems,both physical factors and economic factors of power system are key elements on this definition.We study some cases here,including different line limit levels,load levels and bid strategy through a market model based on OPF (optimal power flow) with a decommitment algorithm.展开更多
This paper studied a supervisory control system for a hybrid off-highway electric vehicle under the chargesustaining(CS)condition.A new predictive double Q-learning with backup models(PDQL)scheme is proposed to optimi...This paper studied a supervisory control system for a hybrid off-highway electric vehicle under the chargesustaining(CS)condition.A new predictive double Q-learning with backup models(PDQL)scheme is proposed to optimize the engine fuel in real-world driving and improve energy efficiency with a faster and more robust learning process.Unlike the existing“model-free”methods,which solely follow on-policy and off-policy to update knowledge bases(Q-tables),the PDQL is developed with the capability to merge both on-policy and off-policy learning by introducing a backup model(Q-table).Experimental evaluations are conducted based on software-in-the-loop(SiL)and hardware-in-the-loop(HiL)test platforms based on real-time modelling of the studied vehicle.Compared to the standard double Q-learning(SDQL),the PDQL only needs half of the learning iterations to achieve better energy efficiency than the SDQL at the end learning process.In the SiL under 35 rounds of learning,the results show that the PDQL can improve the vehicle energy efficiency by 1.75%higher than SDQL.By implementing the PDQL in HiL under four predefined real-world conditions,the PDQL can robustly save more than 5.03%energy than the SDQL scheme.展开更多
Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternati...Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.展开更多
文摘The development and application of a new solution is demonstrated for the type-curve analysis and in-terpretation of well test data from a multiwell reservoir system of both production and injection wells with two-phase flow. The buildup type curves or buildup behavior could be obtained through the solution by using su-perposition. But a new outer boundary condition for variable pressure boundary must be introduced to obtain the correct pressure buildup solutions by superposition. A technique is shown to determine the deviation time from the infinite-acting semilog radial flow stabilization in the derivatives of pressure, which is calculated with respect to and plotted vs. shut-in time. Field examples are given to illustrate the use of the proposed method for analyzing transient pressure data from a well located in a multi-well water-injection reservoir. An adaptive genetic algorithm-based method is used to match the pressure and pressure derivative data to estimate reservoir parameters. The validity and applicability of the proposed method are also demonstrated through the examples.
基金This paper supported by National Natural Science Foundation of China (50079006).
文摘The main objective of this paper is to show an overview analysis of market power issues.Market power reflects the scarcity of power supply.It is the ability of a particular seller or group of sellers to maintain prices profitably above competitive levels for a significant period of time.Because the electric power system has its own characteristics that are different to other economic systems,both physical factors and economic factors of power system are key elements on this definition.We study some cases here,including different line limit levels,load levels and bid strategy through a market model based on OPF (optimal power flow) with a decommitment algorithm.
基金Project(KF2029)supported by the State Key Laboratory of Automotive Safety and Energy(Tsinghua University),ChinaProject(102253)supported partially by the Innovate UK。
文摘This paper studied a supervisory control system for a hybrid off-highway electric vehicle under the chargesustaining(CS)condition.A new predictive double Q-learning with backup models(PDQL)scheme is proposed to optimize the engine fuel in real-world driving and improve energy efficiency with a faster and more robust learning process.Unlike the existing“model-free”methods,which solely follow on-policy and off-policy to update knowledge bases(Q-tables),the PDQL is developed with the capability to merge both on-policy and off-policy learning by introducing a backup model(Q-table).Experimental evaluations are conducted based on software-in-the-loop(SiL)and hardware-in-the-loop(HiL)test platforms based on real-time modelling of the studied vehicle.Compared to the standard double Q-learning(SDQL),the PDQL only needs half of the learning iterations to achieve better energy efficiency than the SDQL at the end learning process.In the SiL under 35 rounds of learning,the results show that the PDQL can improve the vehicle energy efficiency by 1.75%higher than SDQL.By implementing the PDQL in HiL under four predefined real-world conditions,the PDQL can robustly save more than 5.03%energy than the SDQL scheme.
文摘Wind energy is considered a hope in future as a clean and sustainable energy, as can be seen by the growing number of wind farms installed all over the world. With the huge proliferation of wind farms, as an alternative to the traditional fossil power generation, the economic issues dictate the necessity of monitoring systems to optimize the availability and profits. The relatively high cost of operation and maintenance associated to wind power is a major issue. Wind turbines are most of the time located in remote areas or offshore and these factors increase the referred operation and maintenance costs. Good maintenance strategies are needed to increase the health management of wind turbines. The objective of this paper is to show the application of neural networks to analyze all the wind turbine information to identify possible future failures, based on previous information of the turbine.
