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Over the years, the electric power industry has been using optimization methods to help them solve the unit commitment problem. The result has been savings of tens and perhaps hundreds of millions of dollars in fuel costs. Things are changing, however. Optimization technology is improving, and the industry is undergoing radical restructuring. Consequently, the role of commitment models is changing, and the value of the improved solutions that better algorithms might yield is increasing. The dual purpose of this book is to explore the technology and needs of the next generation of computer models for aiding unit commitment decisions. Because of the unit commitment problem's size and complexity and because of the large economic benefits that could result from its improved solution, considerable attention has been devoted to algorithm development in the book. More systematic procedures based on a variety of widely researched algorithms have been proposed and tested. These techniques have included dynamic programming, branch-and-bound mixed integer programming (MIP), linear and network programming approaches, and Benders decomposition methods, among others. Recently, metaheuristic methods have been tested, such as genetic programming and simulated annealing, along with expert systems and neural networks. Because electric markets are changing rapidly, how UC models are solved and what purposes they serve need reconsideration. Hence, the book brings together people who understand the problem and people who know what improvements in algorithms are really possible. The two-fold result in The Next Generation of Electric Power Unit Commitment Models is an assessment of industry needs and new formulations and computational approaches that promise to make unit commitment models more responsive to those needs.

Electric power consumption --- Electric power production --- Electric power --- Forecasting --- Mathematical models --- Decision making --- Purchasing --- EPUB-LIV-FT SPRINGER-B --- Economics. --- Environmental management. --- Environmental economics. --- Environmental protection. --- Operations research. --- Economics, general. --- Environmental Management. --- Energy Policy, Economics and Management. --- Environmental Economics. --- Atmospheric Protection/Air Quality Control/Air Pollution. --- Operations Research/Decision Theory. --- Mathematical models. --- Management science. --- Energy policy. --- Energy and state. --- Air pollution. --- Decision making. --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Choice (Psychology) --- Problem solving --- Operational analysis --- Operational research --- Industrial engineering --- Management science --- Research --- System theory --- Air --- Air contaminants --- Air pollutants --- Air pollution --- Air pollution control --- Air toxics --- Airborne pollutants --- Atmosphere --- Contaminants, Air --- Control of air pollution --- Pollutants, Air --- Toxics, Air --- Pollution --- Air quality --- Atmospheric deposition --- Economics --- Environmental quality --- Energy and state --- Power resources --- State and energy --- Industrial policy --- Energy conservation --- Environmental stewardship --- Stewardship, Environmental --- Environmental sciences --- Quantitative business analysis --- Operations research --- Statistical decision --- Economic theory --- Political economy --- Social sciences --- Economic man --- Control --- Environmental aspects --- Economic aspects --- Government policy --- Consumption of electric power --- Electricity --- Electric utilities --- Energy consumption --- Demand-side management (Electric utilities) --- Electric power generation --- Electricity generation --- Power production, Electric --- Electric power systems --- Electrification --- Electric power supply --- Power supply, Electric --- Consumption --- Electric power consumption - Forecasting - Mathematical models - Congresses --- Electric power production - Decision making - Mathematical models - Congresses --- Electric power - Purchasing - Decision making - Mathematical models - Congresses

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This addition to the ISOR series  introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques.   In a nutshell, complementarity models generalize: a. optimization problems via their Karush-Kuhn-Tucker conditions b. non-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions) c. economic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria) d. problems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES). As such, complementarity models are a very general and flexible modeling format. A natural question is why concentrate on energy markets for this complementarity approach?  As it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems.  The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold.  Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning.  Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers.

Economics --- Methodology of economics --- Finance --- Operational research. Game theory --- Mathematical statistics --- Business economics --- Planning (firm) --- Business management --- financieel management --- bedrijfseconomie --- economie --- mathematische modellen --- econometrie --- operationeel onderzoek