Showing papers on "Economic dispatch published in 1998"
TL;DR: In this paper, a practical strategy based on quadratic programming (QP) techniques to solve the real-time economic dispatch problem is proposed. But the problem is formulated as a linear equality/inequality problem.
Abstract: The presence of multiple constraints due to network line flow limits and emission allowances in the economic dispatch of modern power systems makes the conventional Lambda-Delta iterative approach no longer effective. This paper proposes a practical strategy based on quadratic programming (QP) techniques to solve the real-time economic dispatch problem. It formulates the problem with a quadratic objective function based on the unit's cost curves in quadratic or piecewise-quadratic forms. The operation constraints are modeled as linear equality/inequality equations, resulting in a typical QP problem. Goal programming techniques are also incorporated in the formulation which guarantees the best available solution even under infeasible conditions. In addition, the proposed strategy formulates the problem in the second phase dispatch in real-time by including a set of emergency control variables to provide effective control strategies for properly relieving constraint violations if they exist. The effectiveness of the proposed strategy is demonstrated by an example power dispatch problem.
251 citations
TL;DR: In this paper, an efficient and reliable evolutionary-programming-based algorithm for solving the environmentally constrained economic dispatch (ECED) problem was developed, which can deal with load demand specifications in multiple intervals of the generation scheduling horizon.
Abstract: This paper develops an efficient and reliable evolutionary-programming-based algorithm for solving the environmentally constrained economic dispatch (ECED) problem. The algorithm can deal with load demand specifications in multiple intervals of the generation scheduling horizon. In the paper, the principal components of the evolutionary-programming-based ECED algorithm are presented. Solution acceleration techniques in the algorithm which enhance the speed and robustness of the algorithm are developed. The power and usefulness of the algorithm is demonstrated through its application to a test system.
238 citations
TL;DR: In this article, a new approach using Hopfield neural networks for solving the economic dispatch (ED) problem with transmission capacity constraints is presented, which is based on an improved hopfield neural network which was presented by Gee et al. (1994).
Abstract: This study presents a new approach using Hopfield neural networks for solving the economic dispatch (ED) problem with transmission capacity constraints. The proposed method is based on an improved Hopfield neural network which was presented by Gee et al. (1994). The authors discussed a new mapping technique for quadratic 0-1 programming problems with linear equality and inequality constraints. The special methodology improved the performance of Hopfield neural networks for solving combinatorial optimization problems. The authors have now modified Gee and Prager's (GP) method in order to solve ED with transmission capacity constraints. Constraints are handled using a combination of the GP model and the model of Abe et al. (1992). The proposed method (PHN) has achieved efficient and accurate solutions for two-area power systems with 3, 4, 40 and 120 units. The PHN results are very close to those obtained using the quadratic programming method.
231 citations
01 Nov 1998
TL;DR: Perturbation analysis shows that the solutions obtained by MOSST are truly pareto-optimal, i.e. no objective can be further improved without degrading the others, all in a single run.
Abstract: A new multi-objective stochastic search technique (MOSST) for the multi-objective economic dispatch problem in power systems is presented. It is a highly constrained problem with both equality and inequality constraints. The MOSST heuristic has been designed as a combination of real coded genetic algorithms (GA) and simulated annealing (SA). It incorporates a genetic crossover operator BLX-/spl alpha/ and a problem specific mutation operator with a local search heuristic to provide a better search capability. Extensive simulations are carried out on standard test systems, considering various aspects, and the results are compared with other methods. These results indicate that the new MOSST heuristic converges rapidly to improved solutions. MOSST is a truly multi-objective technique, as it provides the values of various parameters for optimising different objectives, as well as the best compromise between them, all in a single run. Perturbation analysis shows that the solutions obtained by MOSST are truly pareto-optimal, i.e. no objective can be further improved without degrading the others.
180 citations
TL;DR: In this article, an approach to the economic dispatch problem that combines both time-separated constraints and inter-temporal constraints (e.g., ramping) into a single optimization problem can be solved efficiently by interior point methods.
Abstract: The authors describe an approach to the economic dispatch problem that combines both time-separated constraints (e.g., demand and network flow) and inter-temporal constraints (e.g., ramping) into a single optimization problem that can be solved efficiently by interior point methods. By including generator ramping limits as well as network line flow constraints, both economic and security issues are treated simultaneously, avoiding ad hoc post processing. They present several test cases, including dispatching six generators on the IEEE 30-bus network over 168 hours with line flow and ramping constraints. Computational effort as measured by iteration counts or execution time (CPU sees) varies only modestly with problem size.
138 citations
TL;DR: In this paper, a new genetic approach for solving combined heat and power (CHP) economic dispatch problems is presented, where the complexity of CHP dispatch lies in the constraints imposed by the multi-demand and heat-power capacity mutual dependencies.
Abstract: This paper presents a new genetic approach for solving combined heat and power (CHP) economic dispatch problems The complication of CHP dispatch lies in the constraints imposed by the multi-demand and heat-power capacity mutual dependencies The paper proposes improved penalty function formulation for Genetic Algorithms (GAs) to effectively handle constraints The method has been tested and compared to demonstrate its effectiveness
100 citations
TL;DR: In this paper, Pool, bilateral and multilateral dispatch co-ordination are explored and mathematical models developed for each case, and the practical case when all three modes coexist is discussed with respect to both forward and real time dispatch.
Abstract: Managing dispatch in an open access environment is a new challenge facing independent transmission system operators who are mandated to provide a level playing field for all transmission users Two issues are especially important viz; use-of-transmission-system charges and congestion management This paper examines aspects of these issues with emphasis on the latter Pool, bilateral and multilateral dispatch co-ordination are explored and mathematical models developed for each case The practical case when all three modes coexist is discussed with respect to both forward and real time dispatch
91 citations
TL;DR: In this article, a new formulation of the extended security constrained economic dispatch which allocates both power and reserve generation resources is presented, where the dispatch of the resources is constrained by limitations of system transmission capacities.
Abstract: The Poolco model is emerging as one of the most acceptable options for organizing the spot market of electricity. Although the model represents a reasonable and safe transition from present industry practices to what is required in a competitive electricity market, many important issues remain to be resolved. In particular, issues regarding reliability related services are of a special concern to the industry. This paper is devoted to the issue of reserve service delivery and pricing. The Poolco model is extended in this paper to include spot pricing of reserve generation and transmission capacities, as well as demand side bidding. In the authors' extended model, suppliers submit bids for power as well as for reserve capacities. A new formulation of the extended security constrained economic dispatch which allocates both power and reserve generation resources is presented in this paper. The dispatch of the resources is constrained by limitations of system transmission capacities. The proposed formulation is considered to be relevant not only in the Poolco, but in a more general setup. An illustrative example is used to introduce concepts and present results. Finally, some general issues' regarding formats of proposals, balance of payments and uniqueness of the prices that apply equally to both the original and extended Poolco models are discussed.
54 citations
TL;DR: In this article, the authors explored a new simulation-based dispatch rule and a queue prediction dispatch rule, and compared several other dispatch rules commonly used in semiconductor manufacturing with their proposed dispatch rules.
Abstract: Semiconductor wafer fabrication involves very complex process routing, and reducing flow times is very important. This study reports a search for better dispatch rules for achieving the goal of reducing flow times, while maintaining high machine utilization. We explored a new simulation-based dispatch rule and a queue prediction dispatch rule. Using simulation experiments and an industrial data set, we also compared several other dispatch rules commonly used in semiconductor manufacturing with our proposed dispatch rules. Among these rules, in addition to the simulation-based dispatching rule, the shortest-remaining-processing-time, earliest-due-date and leastslack rules also performed well in terms of reducing flow times. The reasons behind these good rules are discussed in this paper. Based on the previous works and this study, accurately predicting and effectively utilizing future flow times can improve the quality of production management decisions.
38 citations
03 Mar 1998
TL;DR: In this article, a model for topping, combined cycle facilities has been depicted based on a Lagrangian and Kuhn-Tucker approach for optimization with constraints, and the theoretical aspects of applying such an approach are also discussed.
Abstract: Economic dispatch models for combined cycle cogeneration plants are evaluated. A model for topping, combined cycle facilities has been depicted based on a Lagrangian and Kuhn-Tucker approach for optimization with constraints. The model has been expanded to include typical power plant environmental constraints. The theoretical aspects of applying such an approach are also discussed.
30 citations
TL;DR: A novel algorithm is proposed to calculate the optimising problem of economic and security dispatch in which DC power flow and limitation on power transmission line capacity are taken into consideration and is more effective in calculating speed, robustness, property of convergence and requirement of computer memory without introducing any multiplier.
Abstract: This paper proposes a novel algorithm to calculate the optimising problem of economic and security dispatch in which DC power flow and limitation on power transmission line capacity are taken into consideration. Compared to the conventional Lagrangian Relaxation approach, the algorithm proposed is more effective in calculating speed, robustness, property of convergence and requirement of computer memory without introducing any multiplier. A new and efficient way is proposed to deal with more complex constraints in economic dispatch. The theoretical proof of the algorithm is also given in this paper and the advantage is demonstrated by calculating the IEEE 24-node system and compared with the results obtained by MATLAB.
TL;DR: In this paper, a Lagrangian relaxation solution method is applied to the problem of joint energy and reserve dispatch in a pool-oriented electricity market, where the problem is formulated as a joint optimization problem.
Abstract: A Lagrangian relaxation solution method is applied by the authors to the problem of joint energy and reserve dispatch in a pool-oriented electricity market.
TL;DR: In this paper, the robustness of a search technique based on genetic algorithms (GAs) against a number of conventional techniques over a spectrum of power dispatch problems was evaluated, and it was shown that the more complex the problem is, the more benefit one can obtain from a GA.
Abstract: The mathematical formulation for a power economic dispatch problem can be variously defined according to utilities' central focus. Conventionally, it is common practice to approach different dispatch problems via different techniques. The time and design effort, thus induced in partly altering or entirely replacing the existing technique, is not desirable. This paper demonstrates the robustness of a search technique based on genetic algorithms (GAs) against a number of conventional techniques over a spectrum of power dispatch problems. The problems investigated are in increasing order of complexity. Initially, GAs cannot do better than conventional techniques when the simple problem formulation is encountered, e.g. in the case of static classic Economic Dispatch. However, when problems become progressively more complicated, GAs gradually overtake conventional techniques which are limited mainly by solution accuracy. The outcome of the study clearly shows the robustness and suitability of GAs on the power dispatch problems, and verifies the fact that the more complex the problem is, the more benefit one can obtain from a GA.
06 Jan 1998
TL;DR: In this article, a transmission-constrained unit commitment method using a Lagrangian relaxation approach is presented, where the transmission constraints are modeled as linear constraints based on a DC power flow model and the demand and spinning reserve constraints are relaxed by attaching Lagrange multipliers.
Abstract: The paper presents a transmission-constrained unit commitment method using a Lagrangian relaxation approach. The transmission constraints are modeled as linear constraints based on a DC power flow model. The transmission constraints, as well as the demand and spinning reserve constraints, are relaxed by attaching Lagrange multipliers. The authors take a new approach in the algorithmic scheme. A three-phase algorithm is devised including dual optimization, a feasibility phase and unit decommitment. A test problem involving more than 2500 transmission lines and 2200 buses is tested along with other test problems.
01 Jan 1998
TL;DR: Using priority rules, a project was conducted to implement a dispatching system in a high-volume semiconductor frontend production as mentioned in this paper, where the specific goals were to apply dispatch rules to reduce cycle time and balance the WIP in the line.
Abstract: Using priority rules, a project was conducted to implement a dispatching system in a high-volume semiconductor frontend production. The specific goals of this project were to apply dispatch rules to reduce cycle time and balance the WIP in the line . This paper will present the project methodology, implemented dispatch policies and measurable results in different production areas.
TL;DR: In this paper, a new nonlinear convex network flow programming (NLCNFP) model and algorithm for solving the on-line economic power dispatch and automatic generation control (AGC) with security and economy is presented.
TL;DR: In this paper, the authors show that economic models are unable to predict whether imperfect competition in generation increases or reduces transmission congestion payments, despite early speculation to the contrary, and they also show that imperfect competition can increase or decrease transmission congestion.
24 May 1998
TL;DR: An evaluation of technical concerns that may arise from the deregulation of electric power systems, particularly including wheeling transactions, are presented, conducted by multiple perspectives such as: transmission loss, voltage profiles, and network congestion.
Abstract: In this paper the authors present an evaluation of technical concerns that may arise from the deregulation of electric power systems, particularly including wheeling transactions. In the deregulation of the power industry, many independent power producers (IPPs) are seeking chances to be connected to the existing transmission systems under an open access environment. Some IPPs will sell power to existing utilities at a market price and others may participate in wheeling transactions with a third party, using the existing transmission system. This paper reports research about the impact of wheeling introduced in an existing electric power system. The evaluation of the impact on the existing utility power system is conducted by multiple perspectives such as: transmission loss, voltage profiles, and network congestion. Numerical analyses have been done on a standard IEEE power system. The optimal power flow was solved by varying the possible combinations of an IPP supplier and a customer load in wheeling transactions. The power output of the IPPs was assumed to be determined by an economic objective and therefore not controllable by the existing utility. The various numerical aspects were assessed based on the economic dispatch and AC load flow data.
03 Mar 1998
TL;DR: In this paper, the authors formulated the CME constrained economic dispatch problem and presented an optimisation technique based on duality theory to solve the problem, where the concept of subsidised incremental cost was introduced.
Abstract: With the participation of nonutility generation in a fast-growing energy market, a contracted minimum energy (CME) constrained economic dispatch problem has emerged and became a common concern between the host utility, independent power producer and regulatory body. This paper formulates the CME constrained dispatch problem and presents an optimisation technique based on duality theory. By introducing the concept of subsidised incremental cost, we have interpreted the essence of CME constraints and set up a modified equal incremental criterion under new operation environment and open energy market.
03 Mar 1998
TL;DR: In this paper, a general formulation of the optimum economic load dispatch problem in a system with thermal plants taking into account the constraints on emission of sulfur dioxide and oxides of nitrogen is presented.
Abstract: This paper presents a general formulation of the optimum economic load dispatch problem in a system with thermal plants taking into account the constraints on emission of sulfur dioxide and oxides of nitrogen. The proposed algorithm is useful to determine the optimum mix-ratio of high sulfur content and low sulfur content fuels, to limit the sulfur dioxide (SO/sub 2/) emission per hour. The emission of oxides of nitrogen (NO/sub x/) is minimised by reducing the output of the generating units with the high ratio of incremental NO/sub x/ emission to incremental fuel cost. The method proposed for considering the pollution constraints is simple, and can easily be incorporated in an existing economic dispatch program. The algorithm is tested on a plant with four generating units, and the results are presented.
01 Jan 1998
TL;DR: In this paper, the authors presented an optimisation technique based on duality theory aid for the CME constrained dispatch problem and interpreted the essence of CME constraints and set up a modified equal-time critcion under new operation environment and open energy m;uket.
Abstract: With the participation of non-utility generetion in a fast-growing energy market, a contracted minimuin energy constrained economic disp;itcli problem has einergcd and became a common concern between the host utility, independent power producer iind regularory hxly. 'I'his paper forinulates the CME constrained dispatch problem and presents an optimisation technique based on duality theory aid. By introducing the concept of nrbsidised increnuntuf cosl, we have interpreted the essence of CME constraints and set up a modified equal incremcnl;il critcrion under new operation environment and open energy m;uket
01 Jan 1998
TL;DR: In this paper, a series of examples of pricing in a competitive electricity market model illustrates the determination of prices under economic dispatch in a network and relates transmission constraints to congestion rentals that lead to different prices.
Abstract: Examples of pricing in networks illustrate the issues that accompany transmission congestion in a competitive electricity market.2 In theory, pricing in a competitive electricity market with price-taking participants is at marginal cost. The competitive model is equivalent to a market with a central coordinator operating a pool. The many potential suppliers compete to meet demand, bidding energy supplies into the pool. The dispatcher chooses the welfare-maximizing combination of generation and demand to balance the system. 3 This optimal dispatch determines the market clearing prices. Consumers pay this price into the pool for energy taken from the spot market and generators in turn are paid this price for the energy supplied. Inherently, energy pricing and transmission congestion pricing are intimately connected. A series of examples of pricing in the competitive electricity market model illustrates the determination of prices under economic dispatch in a network and relates transmission constraints to congestion rentals that lead to different prices
Journal Article•
TL;DR: This paper proposes anew neural network (NN)-based algorithm to solve economic dispatch (ED) problems with some units having prohibited operating zones and shows that the new algorithm has the advantages of both the SA technique and the Hopfield model.
Abstract: This paper proposes anew neural network (NN)-based algorithm to solve economic dispatch (ED) problems with some units having prohibited operating zones. The prohibited operating zones of units result in the ED problem becoming a nonconvex optimization problem; therefore, there are many local minima embedded in the problem. The new NN model is formed by incorporating a simulated anneal ing (SA) technique into a Hopfield model. In the model, an effective strategy is explored in accordance with the equal-incremental-cost criterion to deal with the difficult problem of operating in one of the prohibited zones. An energy function is defined, and the system state changes until a minimum energy is reached. A Gaussian distribution disturbance is added to the variation of the neuron's input to provide the new candidate solution with an ability to escape from the local minima. Conceptually, the model solution normally moves in the direction of decreasing energy, but sometimes we intentionally allow it to accept uphill movements following a probabilistic acceptance criterion, such that it will finally search out the global optimum solution for the nonconvex ED problem. Application of the proposed algorithm is illustrated using a 15-unit system with four units having prohibited operating zones. Computational results of the sample system show that the new algorithm has the advantages of both the SA technique and the Hopfield model.
01 Jan 1998
TL;DR: In this article, a model for topping, combined cycle facilities has been depicted based on Lagrangian and Kuhn-Tucker approach for optimization with constraints, and the theoretical aspects of applying such an approach are discussed.
Abstract: Economic dispatch models for combined cycle cogeneration plants are evaluated. A model for topping, combined cycle facilities has been depicted based on Lagrangian and Kuhn - Tucker approach for optimization with constraints. The model has been expanded to include typical plant environmental constraints. The theoretical aspects of applying such an approach are discussed.