Carbon dioxide (CO_2) emission reduction targeting is an important move in atmospheric CO_2 concentration control. Idea of applying HEN retrofit and fuel switching in existing plant has been proposed to be applied sim...
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ISBN:
(纸本)9781457700033
Carbon dioxide (CO_2) emission reduction targeting is an important move in atmospheric CO_2 concentration control. Idea of applying HEN retrofit and fuel switching in existing plant has been proposed to be applied simultaneously in achieving CO_2 emissions reduction. Graphical approach combining the mentioned idea has been proposed, but involves potentially time consuming manual procedures. Besides, quality of solution produced greatly depends on designer's experience and judgment, and graphical approach hardly account for the cost factor during the design phase, thus potentially generate complex design. This paper introduces a MINLP model for simultaneous CO_2 emissions reduction targeting via fuel switching and HEN retrofit for existing plant. A model execution strategy was proposed along with proposed model. Application of proposed model onto case study proven workability of the model to generates solution for targeted CO_2 emissions reduction in minimum payback period manner.
In a hydro energy and water resource system it is desirable to optimize hydropower production with considerations of flood control, residential, agricultural and industrial water supply, navigation, environmental and ...
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ISBN:
(纸本)9781457710001
In a hydro energy and water resource system it is desirable to optimize hydropower production with considerations of flood control, residential, agricultural and industrial water supply, navigation, environmental and ecological requirements, etc.. Incorporating complicated constraints of cascaded reservoirs and government regulation on water resource usage allocation, this paper presents a long-term scheduling problem of hydro energy and water resource system based on chance-constrained programming with uncertainties of natural water inflows and water demands of different regions. The water usage regulation with uncertain natural inflow is modeled as probabilistic chance constraints. The nonlinear and noconvex hydro plant production function is converted into mixedinteger formulation and a general mixed integer linear programming (MILP) method is applied to solve this complicated scheduling problem. Preliminary numerical testing results for a river basin with cascaded reservoirs show that based on the problem formulation presented in the paper, the long-term scheduling is solved efficiently and accurately. Numerical testing for a more complex hydro system is being conducted.
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 mixedinteger Non-linearprogramming (MINLP) approach.
Order allocation among member enterprises of a horizontal conglomerate is the key problem when the conglomerate headquarters is responsible for obtaining all market orders. Considering stochastic characteristic of com...
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Order allocation among member enterprises of a horizontal conglomerate is the key problem when the conglomerate headquarters is responsible for obtaining all market orders. Considering stochastic characteristic of component defects in assemble-to-order, a mixed integer linear programming model for order allocation with multi-order, multi-product, multi-period, and multi-manufacture was proposed. The constraint conditions of the model are capacity limitations, material balance equations, and order quantities limitations. The objective function of the model consists of assembling costs, transportation costs and shortage penalty costs. The model is tested by a simulation of an example.
Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. In this paper, we propose a thermal-driven 3D floor-planner. Our contributions include: (1) a n...
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Heat removal and power density distribution delivery have become two major reliability concerns in 3D stacked technology. In this paper, we propose a thermal-driven 3D floor-planner. Our contributions include: (1) a novel multi-objective formulation to consider the thermal and performance constraints in the optimization approach; (2) an efficient mixed integer linear programming (MILP) representation of the floorplanning model; and (3) a smooth integration of the MILP model with an accurate thermal modelling of the architecture. The experimental work is conducted for two realistic many-core single-chip architectures: an homogeneous system resembling Intel's SCC, and an improved heterogeneous setup. The results show promising improvements of the mean, peak temperature and the thermal gradient, with a reduced overhead in the wire length of the system.
In this study,a developed inexact community-scale energy model has been developed for planning renewable energy management systems under *** allows uncertainties presented as both probability distributions and interva...
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In this study,a developed inexact community-scale energy model has been developed for planning renewable energy management systems under *** allows uncertainties presented as both probability distributions and interval values to be incorporated with in a general optimization *** method is based on an integration of the existing possibility degree method for interval numbers,the satisfaction degree method for stochastic variables and mixed integer linear programming *** can also facilitate capacityexpansion planning for energy-production facilities within a multi-period and multi-option *** in energy management systems can be systematically reflected,thus applicability of the modeling process can be highly *** model has then been applied to a case of long-term renewable energy management planning for three *** solutions for the planning of energy management systems have been generated.
This problem includes fuzzy parameters, choosing suppliers according to their quality raw materials and supplier contracts. There is a trade-off between raw material quality, its purchasing and reprocessing costs. If ...
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This problem includes fuzzy parameters, choosing suppliers according to their quality raw materials and supplier contracts. There is a trade-off between raw material quality, its purchasing and reprocessing costs. If decision maker (DM) wishes to work with a supplier which supplies a low quality raw material, this raw material can be in need of reprocessing. To avoid the reprocessing costs, a supplier which serves a high quality raw material can be chosen but at this time the DM has to face a high purchasing cost. An integrated fuzzy supply chain network system is considered to accomplish problems aforementioned trade-offs above.
mixed integer linear programming (MILP) models have in the last decade gained considerable interest in simulation of deregulated electricity markets [1, 2]. They are based on an in-depth knowledge of all relavant tech...
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mixed integer linear programming (MILP) models have in the last decade gained considerable interest in simulation of deregulated electricity markets [1, 2]. They are based on an in-depth knowledge of all relavant technical characteristics (for example a cascade of hydro power plants), of the current state (for example the regulating basins states), and the forecast of external parameters (for example the 24 hours inflows forecast) of the system under study, and the hour-by-hour forecast of the electricity marginal price for the following day [8]. Similar as in the linearprogramming (LP) models, in MILPs, too, all technical operation limitations are expressed as a set of linear equations and inequations. The optimization function in MILPs remains linear and is usually expressed as the maximum of the expected revenue from the electricity market. It is very important to note that some variables in MILPs can be of the integer type which allows far better modelling of system technical characteristics then in LPs. When applying MILPs, one does not ussually do the math since it suffices to use the available computer solvers. This paper presents the theory of the new MILP Flores model that has been developed at the Milan Vidmar Electric Power Research Institute. It is based on the Institute's PRAK model that calculates the hydro cascades production [17]. The know-how follows the general LP energy flow MESSAGE model of the International Atomic Energy Agency [18]. Two examples are added: the cascade of three existing run-of-river plants on the Soea river including the new pumping hydro plant Avee [14] and the weekly-cycle cascade of the two rehabilitated plants Moste II+III on the upper Sava river [15].
A linear time-varying aggregate traffic flow model can be used to develop traffic flow management strategies using optimization algorithms. However, there are few methods available in the literature to translate these...
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A linear time-varying aggregate traffic flow model can be used to develop traffic flow management strategies using optimization algorithms. However, there are few methods available in the literature to translate these aggregate solutions into practical control actions involving individual aircraft. In this paper, a computationally efficient disaggregation algorithm is proposed by employing a series of linear program and mixedintegerlinear program methods, which converts an aggregate (flow-based) solution to a flight-specific control action. Numerical results generated by the optimization method and the disaggregation algorithm are presented and illustrated by applying them to generate traffic flow management schedules for a typical day in the U.S. National Airspace System.
In this paper, a variant of the Traveling Salesman Problem with Time Windows is considered, which consists in minimizing the sum of travel durations between a depot and several customer locations. Two mixedinteger li...
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In this paper, a variant of the Traveling Salesman Problem with Time Windows is considered, which consists in minimizing the sum of travel durations between a depot and several customer locations. Two mixed integer linear programming formulations are presented for this problem: a classical arc flow model and a sequential assignment model. Several polyhedral results are provided for the second formulation, in the special case arising when there is a closed time window only at the depot, while open time windows are considered at all other locations. Exact and heuristic algorithms are also proposed for the problem. Computational results show that medium size instances can be solved exactly with both models, while the heuristic provides good quality solutions for medium to large size instances. (C) 2010 Elsevier B.V. All rights reserved.
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