The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, othe...
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ISBN:
(纸本)9781457710018
The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and "green" operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a mixed integer non-linear programming (MINLP) approach.
In this paper, we introduce the planar expropriation problem with non-rigid rectangular facilities. The facilities considered in this study are two-dimensional facilities of rectangular shape. Moreover, we allow the f...
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In this paper, we introduce the planar expropriation problem with non-rigid rectangular facilities. The facilities considered in this study are two-dimensional facilities of rectangular shape. Moreover, we allow the facility dimensions to be decision variables and introduce the concept of non-rigid facilities. Based on the geometric properties of such facilities, we developed a new formulation for this continuous covering location model which does not require employing distance measures. This model is intended to determine the location and formation of facilities simultaneously. For solving this new model, we proposed a continuous branch-and-bound framework utilizing linear approximations for the tradeoff curve associated with the facility formation alternatives. Further, we developed new problem generation and bounding strategies suitable for our particular problem structure. Computational experience shows that the branch-and-bound procedure we developed performs better than conventional mixed-integernonlinearprogramming solvers BARON and SBB for solving this particular location model. (C) 2010 Published by Elsevier Ltd.
A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market ar...
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A model for designing the network of a new entrant supply chain under inelastic demand and in the presence of pre-existing competing chains is proposed. These supply chains provide an identical product for a market area. The model considers the location of distribution centres and retail outlets on a discrete set of potential locations. The assumptions of the model are: (1) static competition between the new and pre-existing chains and (2) a probabilistic customer behaviour based on an attraction function depending on both the location and the quality of the retailers. This model also incorporates the impact of the facilities' location decisions on the operational inventory and shipment decisions. The resulting model is formulated as a mixedintegernon-linear programme (MINLP). To solve the MINLP it is transformed to a linear one. We illustrate the model, discuss the results of a real-world case, and investigate the effectiveness of the proposed algorithm using randomly generated examples. Journal of the Operational Research Society (2011) 62, 1784-1795. doi:10.1057/jors.2010.146 Published online 17 November 2010
The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, othe...
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ISBN:
(纸本)9781457710001
The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and "green" operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a mixed integer non-linear programming (MINLP) approach.
The restructuring and deregulation has exposed the transmission planner to new objectives and uncertainties. As a result, new criteria and approaches are needed for transmission expansion planning (TEP) in deregulated...
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The restructuring and deregulation has exposed the transmission planner to new objectives and uncertainties. As a result, new criteria and approaches are needed for transmission expansion planning (TEP) in deregulated electricity markets. This paper proposes a new market-based approach for TEP. An improved differential evolution (IDE) model is proposed for the solution of this new market-based TEP problem. The modifications of IDE in comparison to the simple differential evolution method are: (1) the scaling factor F is varied randomly within some range, (2) an auxiliary set is employed to enhance the diversity of the population, (3) the newly generated trial vector is compared with the nearest parent, and (4) the simple feasibility rule is used to treat the constraints. Results from the application of the proposed method on the IEEE 30-bus test system demonstrate the feasibility and practicality of the proposed IDE for the solution of TEP problem. (C) 2009 Elsevier Ltd. All rights reserved.
In this paper, we present a framework that improves a designer's capability to determine near-optimal sizes of components for a given system architecture. Component sizing is a hard problem to solve because of com...
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ISBN:
(纸本)9780791844113
In this paper, we present a framework that improves a designer's capability to determine near-optimal sizes of components for a given system architecture. Component sizing is a hard problem to solve because of competing objectives, requirements from multiple disciplines, and the need for finding a solution quickly for the architecture being considered. In current approaches, designers rely on heuristics and iterate over the multiple objectives and requirements until a satisfactory solution is found. To improve on this state of practice, we introduce advances in the following two areas: a) Formulating a component sizing problem in a manner that is convenient to designers and b) Solving the problem efficiently so that all of the imposed requirements are satisfied simultaneously and the solution obtained is mathematically optimal. An acausal, algebraic, equation-based, declarative modeling approach using mathematical programming (GAMS) is taken to solve these problems more efficiently. In addition the Systems Modeling Language (OMG SysML (TM)) is used to formulate component sizing problems to facilitate problem formulation, model reuse and the automatic generation of low-level code that can be solved using GAMS and its solvers (BARON). This framework is demonstrated by applying it to an example of a hydraulic log splitter.
This paper proposes a new method for secure bilateral transactions determination ensuring economic power dispatch of the generators using new AC distribution factors for pool and bilateral coordinated markets. The new...
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This paper proposes a new method for secure bilateral transactions determination ensuring economic power dispatch of the generators using new AC distribution factors for pool and bilateral coordinated markets. The new optimization problem considers simultaneous minimization of deviations from scheduled transactions and fuel cost of the generators in the network. The fuel cost has been obtained for hybrid market model and impact of different percentage of bilateral demand on fuel cost, generation share, and pattern of transactions has also been determined. The impact of optimally located unified power flow controller (UPFC) on the bilateral transactions, fuel cost and generation pattern has also been studied. The results have also been obtained for pool market model. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS). (C) 2008 Elsevier Ltd. All rights reserved.
In this paper some transformation techniques, based on power transformations, are discussed. The techniques can be applied to solve optimization problems including signomial functions to global optimality. Signomial t...
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In this paper some transformation techniques, based on power transformations, are discussed. The techniques can be applied to solve optimization problems including signomial functions to global optimality. Signomial terms can always be convexified and underestimated using power transformations on the individual variables in the terms. However, often not all variables need to be transformed. A method for minimizing the number of original variables involved in the transformations is, therefore, presented. In order to illustrate how the given method can be integrated into the transformation framework, some mixedinteger optimization problems including signomial functions are finally solved to global optimality using the given techniques.
In this paper, a Constructive Heuristic Algorithm (CHA) is presented to solve the Transmission Network Expansion Planning Problem (TNEP), a complex non-convex mixed integer non-linear programming (MINLP) problem with ...
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In this paper, a Constructive Heuristic Algorithm (CHA) is presented to solve the Transmission Network Expansion Planning Problem (TNEP), a complex non-convex mixed integer non-linear programming (MINLP) problem with multiple local minima. In the proposed algorithm, the non-linearities are resolved through the following feature: when discrete decision variables are given, the model becomes linear in the continuous variables. A CHA is developed which improves the current solution by implementing multiple step simultaneous changes over a number of saturated transmission lines, in contrast to the approach traditionally followed. which implements one change at a time. Solutions to test problems are computed. (C) 2008 Elsevier B.V. All rights reserved.
The multiple allocation hub-and-spoke network design under hub congestion problem is addressed in this paper. A non-linearmixedintegerprogramming formulation is proposed, modeling the congestion as a convex cost fu...
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The multiple allocation hub-and-spoke network design under hub congestion problem is addressed in this paper. A non-linearmixedintegerprogramming formulation is proposed, modeling the congestion as a convex cost function. A generalized Benders decomposition algorithm has been deployed and has successfully solved standard data set instances up to 81 nodes. The proposed algorithm has also outperformed a commercial leading edge non-linearintegerprogramming package. The main contribution of this work is to establish a compromise between the transportation cost savings induced by the economies of scale exploitation and the costs associated with the congestion effects. (C) 2008 Elsevier Ltd. All rights reserved.
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