Applied Operations Research And Financial Modelling In Energy
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Applied Operations Research and Financial Modelling in Energy
This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector. This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University’s Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).
Applied Operations Research and Financial Modelling in Energy
This book on Applied Operations Research and Financial Modelling in Energy (AORFME) presents several applications of operations research (OR) and financial modelling. The contributions by a group of OR and Finance researchers focus on a variety of energy decisions, presenting a quantitative perspective, and providing policy implications of the proposed or applied methodologies. The content is divided into three main parts: Applied OR I: Optimization Approaches, Applied OR II: Forecasting Approaches and Financial Modelling: Impacts of Energy Policies and Developments in Energy Markets. The book appeals to scholars in economics, finance and operations research, and to practitioners working in the energy sector. This is the eighth volume in a series of books on energy organized by the Centre for Energy and Value Issues (CEVI). For this volume, CEVI collaborated with Hacettepe University's Energy Markets Research and Application Center. The previous volumes in the series are: Financial Aspects in Energy (2011), Energy Economics and Financial Markets (2012), Perspectives on Energy Risk (2014), Energy Technology and Valuation Issues (2015), Energy and Finance (2016), Energy Economy, Finance and Geostrategy (2018), and Financial Implications of Regulations in the Energy Industry (2020).
Complementarity Modeling in Energy Markets
Author: Steven A. Gabriel
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-07-20
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. on-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. conomic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria) d. roblems 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? s 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.