This paper discusses the evolution and implementation of smart dispatch tools to support the real-time operation of the PJM competitive wholesale electricity market. These innovations include the implementation of mul...
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ISBN:
(纸本)9781457710001
This paper discusses the evolution and implementation of smart dispatch tools to support the real-time operation of the PJM competitive wholesale electricity market. These innovations include the implementation of multi-stage real-time dispatch software, adaptive generation modeling, enhanced visualization tools and comprehensive evaluation and feedback mechanisms through the perfect dispatch concept. The paper discusses the operational situations and challenges that have driven the need for continued evolution of dispatch tools. The paper explores efficiency gains that the market experienced when these innovations were successfully incorporated into the market clearing and dispatch processes at PJM.
The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor in...
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The problem of distribution centers location with multiple practical constraints, such as soft service time window, rigid work time window, vehicle being reused and so on, is shown firstly. Secondly, a multi-factor integrated optimization model is given, which not only optimizes distribution centers location and vehicle routes, but also meets all the multiple practical constraints. A bi-level nested genetic algorithm is proposed thirdly, where the design of the lower algorithm meets various constraints of optimization. Finally, the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
The problem of distribution centers location with multiple practical constraints,such as soft service time window,rigid work time window,vehicle being reused and so on,is shown ***,a multi-factor integrated optimizati...
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The problem of distribution centers location with multiple practical constraints,such as soft service time window,rigid work time window,vehicle being reused and so on,is shown ***,a multi-factor integrated optimization model is given,which not only optimizes distribution centers location and vehicle routes,but also meets all the multiple practical constraints.A bi-level nested genetic algorithm is proposed thirdly,where the design of the lower algorithm meets various constraints of ***,the feasibility of the model and the efficiency of the algorithm are tested by a numerical example.
Wind power bidding is critical for wind power producers operations in an electricity market. Due to the uncertainly and variability of wind power output, some markets impose a penalty on the deviation between the wind...
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ISBN:
(纸本)9781457710001
Wind power bidding is critical for wind power producers operations in an electricity market. Due to the uncertainly and variability of wind power output, some markets impose a penalty on the deviation between the wind power bids in the day-ahead market and the real wind power output in the real-time market. The objective of a wind power producers bidding problem is to maximize the producers profit while minimizing the penalty and ensuring the output from its wind farms can be utilized to the largest extent. In this paper, we present a wind power bidding strategy based on chance-constrained optimization. The chance constraint is used to define the probability that certain amount of wind power bid into the market can be accepted. We formulate the problem as a chance-constrained two-stage (CCTS) stochastic optimization program. The second stage represents the many possible realizations of wind power output by scenarios. We also consider pumped-storage hydro power plants as storage to accommodate the fluctuation of wind power. Sample Average Approximation (SAA) is used to solve the problem. Numerical examples are also provided.
Fast web service selection approach is crucial for seamless and dynamic integration of e-business applications. However, since existing service selection approaches take up a lot of time, this make service selection o...
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Fast web service selection approach is crucial for seamless and dynamic integration of e-business applications. However, since existing service selection approaches take up a lot of time, this make service selection out of time control. In this paper, we propose a fast web service selection(FWSS) approach for service composition system in e-business. In FWSS, only those services that fit to the context of users are valid candidates for the composition, and then mixed integer programming is used to find the most suitable service from above services. Experimental results show that our approach can fast perform service selection for web service composition.
This paper discusses a model predictive control approach to hybrid systems with continuous and discrete *** algorithm,which takes into account a model of a hybrid system,described as Hybrid ***,to avoid computational ...
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This paper discusses a model predictive control approach to hybrid systems with continuous and discrete *** algorithm,which takes into account a model of a hybrid system,described as Hybrid ***,to avoid computational complexity and computation time,the nonlinear optimization problem is solved by evolutionary algorithms(EA)such as Genetic Algorithms(GA)and Particle Swarm Optimization(PSO).We have applied both GA and PSO algorithms for nonlinear optimization in Hybrid Predictive Control(HPC)for the start-up of a Continuous Stirred-Tank Reactor(CSTR).The simulation results show the good performance of approaches and their capability to use in online application.
This paper proposes a multi-agent approach to decentralized power system restoration for distribution system *** proposed method consists of several Distributing Substation Agents(DSAGs) and Load Agents(LAGs).LAG corr...
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This paper proposes a multi-agent approach to decentralized power system restoration for distribution system *** proposed method consists of several Distributing Substation Agents(DSAGs) and Load Agents(LAGs).LAG corresponds to the customer load,while a DSAG corresponds to the distribution *** restores self-load,while a DSAG supplies the electricity to *** the simulation results,it can be seen the proposed multi-agent system could reach the right solution by making use of only the local *** addition,the proposed method is able to get the restorative plan which is better than the solution of the mixedinteger ***,the interaction of several simple agents leads to a dynamic restoration system,allowing approximation solution *** means that the proposed multi-agent restoration system is a promising approach to more large-scale distribution networks.
This paper presents a mixed-integerprogramming formulation to find optimal solutions for the block layout problem with unequal departmental areas arranged in flexible bays. The nonlinear department area constraints a...
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This paper presents a mixed-integerprogramming formulation to find optimal solutions for the block layout problem with unequal departmental areas arranged in flexible bays. The nonlinear department area constraints are modeled in a continuous plane without using any surrogate constraints. The formulation is extensively tested on problems from the literature. (c) 2005 Elsevier B.V. All rights reserved.
作者：
Hua, ZSHuang, FHUSTC
Sch Management Dept Informat Management & Decis Sci Anhua 230026 Peoples R China
To effectively reduce the search space of GAs on large-scale M I P problems, this paper proposed a new variable grouping method based on Structure properties of a problem. Taking the capacity expansion and technology ...
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To effectively reduce the search space of GAs on large-scale M I P problems, this paper proposed a new variable grouping method based on Structure properties of a problem. Taking the capacity expansion and technology selection problem as a typical example, this method groups problem's decision variables over time period and machine line. Based on this new variable grouping method, we developed a variable-grouping based genetic algorithm according to problem's structure properties (VGGA-S). We tested the performance of VGGA-S by applying it on the capacity expansion and technology selection problem. Numerical experiments suggested that, VGGA-S Outperforms the standard GA and variable-grouping based GAs without considering problem's structure properties, both on computation time and solution quality. Although VGGA-S is proposed based on structure properties of a specific MIP problem, it is a general optimization algorithm and theoretically applicable to other large scale MIP problems. (c) 2005 Elsevier Inc. All rights reserved.
Particle Swarm Optimization (PSO) for mixed integer programming problems is proposed. PSO is mainly a method to find a global or quasi-minimum for a nonlinear and nonconvex optimization problem, and there have been fe...
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Particle Swarm Optimization (PSO) for mixed integer programming problems is proposed. PSO is mainly a method to find a global or quasi-minimum for a nonlinear and nonconvex optimization problem, and there have been few studies into optimization problems with discrete decision variables. In this paper, we present the treatment of discrete variables. To treat discrete decision variables as a penalty function, it is possible to treat all decision variables as a continuous decision variable. As a result, the penalty parameter for the penalty function is needed. In this paper, we also present how to determine the penalty parameter for the penalty function. Through mathematical and structural optimization problems, we examine the validity of PSO for the mixed decision variables. (c) 2006 Wiley Periodicals, Inc.
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