G.B. Sheble

Genetic algorithm solution of economic dispatch with valve point loading

A genetics-based algorithm is proposed to solve an economic dispatch problem for valve point discontinuities. The algorithm utilizes payoff information of candidate solutions to evaluate their optimality. Thus, the constraints of classical LaGrangian techniques on unit curves are circumvented. The formulations of an economic dispatch computer program using genetic algorithms are presented and the programs performances using two different encoding techniques are compared. The results are verified for a sample problem using a dynamic programming technique. >

Unit commitment literature synopsis

Several optimization techniques have been applied to the solution of the thermal unit commitment problem. They range from heuristics such as complete enumeration to the more sophisticated ones such as Augmented LaGrangian. The heuristics have even reappeared as expert systems. The problem to solve is the optimal scheduling of generating units over a short-term horizon, typically 168 hours. This paper is an overview of the literature in the unit commitment field over the past twenty five years. >

Evaluation of Dynamic Programming Based Methods and Multiple area Representation for Thermal Unit Commitments

This paper compares the performance of four unit commitment methods, three of which are based on the dynamic programming approach. The paper also presents the modeling of inter-area flow constraints by linear flow network, so that such multi-area representation recognizes any existing transmission limitations which are normally ignored in most unit commitment methods. To assure realistic results, data for two large systems (up to 96 units) were used: EPRI Scenario System C and a midwestern utility. Unit commitment results for these two systems are presented in the paper and they demonstrate the importance of multiple area representation of a system in unit commitment. Such representation affects the schedule costs and assures the determination of realizable schedules.

Refined genetic algorithm-economic dispatch example

A genetic-based algorithm is used to solve a power system economic dispatch (ED) problem. The algorithm utilizes payoff information of perspective solutions to evaluate optimality. Thus, the constraints of classical LaGrangian techniques on unit curves are eliminated. Using an economic dispatch problem as a basis for comparison, several different techniques which enhance program efficiency and accuracy, such as mutation prediction, elitism, interval approximation and penalty factors, are explored. Two unique genetic algorithms are also compared. The results are verified for a sample problem using a classical technique. >

Computational Auction Mechanisms for Restructured Power Industry Operation

From the Publisher: Computational Auction Mechanisms for Restructured Power Industry Operation outlines the application of auction methods for all aspects of power system operation, primarily for a competitive environment. A complete description of the industry structure as well as the various markets now being formed is given. A thorough introduction to auction basics is included to explain how auctions have grown in other industries. Auction methods are compared to classical techniques for power system analysis, operations, and planning. The material is useful for students performing research on the new business environment based on competition. Regulators will find information on initial methods to design and evaluate market systems, and power exchange and financial analysts will find information on the interdependence of markets and power system based techniques for risk management. This information compares the new business environment solutions with old business environment solutions. Computational Auction Mechanisms for Restructured Power Industry Operation provides a first introduction to how electricity will be traded as a commodity in the future.

Direct load control-A profit-based load management using linear programming

Conventional cost-based load management ignores the rate structure offered to customers. The resulting cost savings may cause revenue loss. In a deregulated power industry where utilities absorb the ultimate consequence of their decision making, reexamination of load management must be conducted. In this paper, profit-based load management is introduced to examine generic direct load control scheduling. Based upon the cost/market price function, the approach aims to increase the profit of utilities. Instead of determining the amount of energy to be deferred or to be paid back, the algorithm controls the number of groups power customer/load type to maximize the profit. In addition to the advantage of better physical feel on how the control devices should operate, the linear programming algorithm provides a relatively inexpensive and powerful approach to the scheduling problem.

A profit-based unit commitment GA for the competitive environment

As the electrical industry restructures, many of the traditional algorithms for controlling generating units need modification or replacement, previously utilized to schedule generation units in a manner that minimizes costs while meeting all demand, the unit commitment (UC) algorithm must be updated. A UC algorithm that maximizes profit will play an essential role in developing successful bidding strategies for the competitive generator. Simply bidding to win contracts is insufficient; bidding strategies must result in contracts that, on average, cover the total generation costs. No longer guaranteed to be the only electricity supplier, a generation companys share of the demand will be more difficult to predict than in the past. Removing the obligation to serve softens the demand constraint. In this paper the authors provide a price/profit-based UC formulation which considers the softer demand constraint and allocates fixed and transitional costs to the scheduled hours. The authors describe a genetic algorithm solution to this new UC problem and present results for an illustrative example.

Application of auctions as a pricing mechanism for the interchange of electric power

The expected move to a market-based electric power industry will significantly change electric utility operations. These changes will fundamentally alter the pricing of electric power. How this pricing will be accomplished is a key issue. Traditionally, embedded cost based methods have been used. Spot-pricing has received attention as a possible approach in a market-based electric power environment. Another market-based approach is the use of auctions. This paper presents the application of a sequential sealed-bid and sealed-offer auction to the pricing of electric power by using linear programming. >

Genetic-based unit commitment algorithm

This paper presents a new unit commitment scheduling algorithm. The proposed algorithm consist of using a genetic algorithm with domain specific mutation operators. The proposed algorithm can easily accommodate any constraint that can be true costed. Robustness of the proposed algorithm is demonstrated by comparison to a Lagrangian relaxation unit commitment algorithm on three different electric utilities. Results show the proposed algorithm finds good unit commitment schedules in a reasonable amount of computation time. Included in the appendix is an explanation of the true costing approach.

AGC simulator for price-based operation. I. A model

This paper deals with automatic generation control (AGC) in a deregulated electric industry. Through the passage of new public utility regulatory policies, the Federal Energy Regulatory Commission (FERC) encourages an open market system for price based operation. The FERC has issued a notice of proposed rulemaking seeking comments on various ancillary services. One of these ancillary services is load following. This paper suggests the modifications required in the conventional AGC software to prepare students to study load following in price-based market operation. The details of implementing an academic power system are used to highlight the differences between the AGC operation in a vertically integrated industry (conventional paradigm) and a horizontally integrated industry (new paradigm). The future business environment for electric utilities is incompletely defined as of this writing. Therefore, a framework for price-based operation is developed to assist students in understanding AGC implementation in the new market structure. The proposed market structure is kept generic enough to capture all possibilities in marketing load following capability.