The Experts below are selected from a list of 126 Experts worldwide ranked by ideXlab platform
Nnamdi I Nwulu - One of the best experts on this subject based on the ideXlab platform.
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multi objective dynamic economic emission dispatch of electric power generation integrated with game theory based Demand response programs
Energy Conversion and Management, 2015Co-Authors: Nnamdi I NwuluAbstract:The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to Constraints such as load Demand Constraint, ramp rate Constraint, amongst other Constraints. In this work, we integrate a game theory based Demand response program into the DEED problem. The game theory based Demand response program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic Demand response model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model.
Claudio A Canizares - One of the best experts on this subject based on the ideXlab platform.
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smart distribution system operations with price responsive and controllable loads
IEEE Transactions on Smart Grid, 2015Co-Authors: Isha Sharma, Kankar Bhattacharya, Claudio A CanizaresAbstract:This paper presents a new modeling framework for analysis of impact and scheduling of price-responsive as well as controllable loads in a three-phase unbalanced distribution system. The price-responsive loads are assumed to be linearly or exponentially dependent on price, i.e., Demand reduces as price increases and vice versa. The effect of such uncontrolled price-responsive loads on the distribution feeder is studied as customers seek to reduce their energy cost. Secondly, a novel constant energy load model, which is controllable by the local distribution company (LDC), is proposed in this paper. A controllable load is one that can be scheduled by the LDC through remote signals, Demand response programs, or customer-end home energy management systems. Minimization of cost of energy drawn by LDC, feeder losses, and customers cost pertaining to the controllable component of the load are considered as objectives from the LDCs and customers' perspective. The effect of a peak Demand Constraint on the controllability of the load is further examined. The proposed models are tested on two feeders: 1) the IEEE 13-node test feeder; and 2) a practical LDC feeder system. Detailed studies examine the operational aspects of price-responsive and controllable loads on the overall system. It is observed that the LDC controlled load model results in a more uniform system load profile, and that with a reduction in the peak Demand cap, the energy drawn decreases, consequently reducing feeder losses and LDC's and customers' costs.
Dmitry Ivanov - One of the best experts on this subject based on the ideXlab platform.
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optimal distribution re planning in a centralized multi stage supply network under conditions of the ripple effect and structure dynamics
European Journal of Operational Research, 2014Co-Authors: Dmitry Ivanov, Alexander N Pavlov, Boris V SokolovAbstract:In this paper, an original approach to formulate and solve a multi-period and multi-commodity distribution (re)planning problem for a multi-stage centralized upstream network with structure dynamics considerations is proposed. First original idea of this study is description of the supply chain as a non-stationary dynamic system along with a linear programming (LP) model. This allows distribute design and control variables between dynamic and static models. Second original idea is to transit from the classical LP model to maximal flow problem by excluding Demand Constraint from the LP model. The first contribution of this study is multi-objective problem formulation that opens additional perspectives for decision-making beyond cost-oriented optimization. Second, the maximal flow LP model allows the finding of a feasible solution even for unbalanced supply and Demand cases without relaxing hard capacity Constraints. Third, this allows improve service level at the strategic inventory holding point. Fourth, structure dynamics and ripple effect can be taken into account. Structure dynamics allows considering different execution scenarios and developing suggestions on replanning in the case of disturbances. The graph of structural reliability allows identify the optimistic and pessimistic scenarios. These scenarios are used for computational experiments with the developed model and the industrial models. With the developed model, the practical issues of scenario-based risk identification strategy and operational distribution planning can be interlinked.
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dual problem formulation and its application to optimal redesign of an integrated production distribution network with structure dynamics and ripple effect considerations
International Journal of Production Research, 2013Co-Authors: Dmitry Ivanov, Boris Sokolov, Alexander A PavlovAbstract:In this paper, a dual problem formulation is developed in order to solve a multi-objective, multi-period and multi-commodity production–distribution (re)planning problem for a multi-stage centralised upstream network with structure dynamics considerations. The original idea of this study is to use the real logic of decision-making in companies and exclude Demand Constraint from the linear programming (LP) model. This allows transit from the classical transportation problem, formulated as an LP model in order to improve service level at the strategic inventory holding point. The formulation as an LP model makes it possible to formulate the dual problem. The performed structural analysis revealed some interesting managerial insights into building robust distribution plans and interconnecting decisions on distribution network design, planning, and sourcing.
Boris V Sokolov - One of the best experts on this subject based on the ideXlab platform.
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optimal distribution re planning in a centralized multi stage supply network under conditions of the ripple effect and structure dynamics
European Journal of Operational Research, 2014Co-Authors: Dmitry Ivanov, Alexander N Pavlov, Boris V SokolovAbstract:In this paper, an original approach to formulate and solve a multi-period and multi-commodity distribution (re)planning problem for a multi-stage centralized upstream network with structure dynamics considerations is proposed. First original idea of this study is description of the supply chain as a non-stationary dynamic system along with a linear programming (LP) model. This allows distribute design and control variables between dynamic and static models. Second original idea is to transit from the classical LP model to maximal flow problem by excluding Demand Constraint from the LP model. The first contribution of this study is multi-objective problem formulation that opens additional perspectives for decision-making beyond cost-oriented optimization. Second, the maximal flow LP model allows the finding of a feasible solution even for unbalanced supply and Demand cases without relaxing hard capacity Constraints. Third, this allows improve service level at the strategic inventory holding point. Fourth, structure dynamics and ripple effect can be taken into account. Structure dynamics allows considering different execution scenarios and developing suggestions on replanning in the case of disturbances. The graph of structural reliability allows identify the optimistic and pessimistic scenarios. These scenarios are used for computational experiments with the developed model and the industrial models. With the developed model, the practical issues of scenario-based risk identification strategy and operational distribution planning can be interlinked.
Isha Sharma - One of the best experts on this subject based on the ideXlab platform.
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smart distribution system operations with price responsive and controllable loads
IEEE Transactions on Smart Grid, 2015Co-Authors: Isha Sharma, Kankar Bhattacharya, Claudio A CanizaresAbstract:This paper presents a new modeling framework for analysis of impact and scheduling of price-responsive as well as controllable loads in a three-phase unbalanced distribution system. The price-responsive loads are assumed to be linearly or exponentially dependent on price, i.e., Demand reduces as price increases and vice versa. The effect of such uncontrolled price-responsive loads on the distribution feeder is studied as customers seek to reduce their energy cost. Secondly, a novel constant energy load model, which is controllable by the local distribution company (LDC), is proposed in this paper. A controllable load is one that can be scheduled by the LDC through remote signals, Demand response programs, or customer-end home energy management systems. Minimization of cost of energy drawn by LDC, feeder losses, and customers cost pertaining to the controllable component of the load are considered as objectives from the LDCs and customers' perspective. The effect of a peak Demand Constraint on the controllability of the load is further examined. The proposed models are tested on two feeders: 1) the IEEE 13-node test feeder; and 2) a practical LDC feeder system. Detailed studies examine the operational aspects of price-responsive and controllable loads on the overall system. It is observed that the LDC controlled load model results in a more uniform system load profile, and that with a reduction in the peak Demand cap, the energy drawn decreases, consequently reducing feeder losses and LDC's and customers' costs.