The Experts below are selected from a list of 135885 Experts worldwide ranked by ideXlab platform
Zhoushu Jiang - One of the best experts on this subject based on the ideXlab platform.
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Operational Cost optimization of a full-scale SWRO system under multi-parameter variable conditions ☆
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
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Operational Cost optimization of a full scale swro system under multi parameter variable conditions
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
Ole-morten Midtgard - One of the best experts on this subject based on the ideXlab platform.
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Optimization of Operational Cost for a grid-supporting PV system with battery storage
Renewable Energy, 2016Co-Authors: Iromi Ranaweera, Ole-morten MidtgardAbstract:Coupling an energy storage to a photovoltaic (PV) system not only increases the self-consumption but also solves the over-voltage issues if the cycling of the storage is properly controlled. Whatever the application the storage is used for, the primary concern of the system owner is to maximize the profits. Therefore, this paper addresses an energy management system for a PV system coupled with battery energy storage, which maximizes the daily economic benefits while curtailing the power injection to the grid in such a way that helps to mitigate over-voltage problems caused by reverse power flow. A time dependent grid feed-in limit is proposed achieve this objective. The daily Operational Cost that includes the energy Cost and the battery degradation Cost is considered as the objective function. The non-linear constrained optimization problem is solved using dynamic programming. The analyses are made to investigate the economic benefits of charging the battery from the grid. It is found that there is a possibility for these systems for participating in load-levelling if batteries are charged from the PV system. In order for that to be feasible, the peak-hour sell-back price for the energy from storage should be higher than the off-peak utility electricity price.
Aipeng Jiang - One of the best experts on this subject based on the ideXlab platform.
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Operational Cost optimization of a full-scale SWRO system under multi-parameter variable conditions ☆
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
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Operational Cost optimization of a full scale swro system under multi parameter variable conditions
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
Matthias Gatzen - One of the best experts on this subject based on the ideXlab platform.
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decreasing Operational Cost of high performance oilfield services by lifecycle driven trade offs in development
Cirp Annals-manufacturing Technology, 2014Co-Authors: Christian Marten, Matthias GatzenAbstract:Abstract Oilfield service providers are faced with increasing service reliability, reducing Operational Cost, and the need for rapidly delivering innovative technology. These factors are predominantly influenced in the conceptual design stage. To enable better trade-off decisions a holistic, bottom-up, lifecycle Cost model has been developed. The novelty is the early involvement of all stakeholders, i.e., developers, producers and customers, with heavy focus on the Operational Cost, ultimately meeting the needs of an integrated service provider's customers. Existing business, product, and Operational data, as well as expert knowledge, are fed into the model to forecast lifecycle Cost throughout development. In addition to the model description, a case study is presented.
Jian Wang - One of the best experts on this subject based on the ideXlab platform.
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Operational Cost optimization of a full-scale SWRO system under multi-parameter variable conditions ☆
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
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Operational Cost optimization of a full scale swro system under multi parameter variable conditions
Desalination, 2015Co-Authors: Aipeng Jiang, Jian Wang, Lorenz T. Biegler, Wen Cheng, Changxin Xing, Zhoushu JiangAbstract:Abstract In this work, an Operational optimization designed to reduce the Operational Cost of a full-scale seawater reverse osmosis (SWRO) system was studied under variable operating conditions. To increase Operational flexibility and Cost savings potential, the storage tank was used as the buffer between freshwater production and supply. With a well-developed mathematical model, which included reverse osmosis (RO) process equations, the storage tank equations and Operational Cost equations, the optimal problem was formulated in the form of nonlinear DAOPs (differential algebraic optimization problems). To solve the problem effectively, a simultaneous approach was introduced in which the differential and algebraic variables were fully discretized. Then nonlinear solver of IPOPT was used to solve the discretized large-scale nonlinear programming (NLP) problem. Computational results show that the Operational optimization has significant potential of more than 26% Cost saving over conventional method. Based on the successful solution, the impacts of variable parameters, such as feed temperature, seawater salinity, electricity price and freshwater demand were analyzed in detail. The effect of these parameters on Operational Cost savings and corresponding key performance indicators was determined, which enhances the understanding of the SWRO process and its optimal control.
