...Available online at www.sciencedirect.com Solar Energy 98 (2013) 167–179 www.elsevier.com/locate/solener Ensuring long term investment for large scale solar power stations: Hedging instruments for green power A. Radchik a,⇑, I. Skryabin b, J. Maisano c, A. Novikov d, T. Gazarian e Mathematics & Statistics, Faculty of Science, UTS and Director GTS Pty. Ltd., Suite 2, 16 Figtree Avenue, Randwick, NSW 2031, Australia b Centre for Sustainable Energy Systems, Australian National University, Canberra 2000, Australia c Energy Markets, TTA Pty. Ltd., Suite 12, L6, 321 Pitt St., Sydney, NSW 2000, Australia d School of Mathematics & Statistics, Faculty of Science, University of Technology Sydney (UTS), P.O. Box 123, Broadway, NSW 2007, Australia e School of Mathematics & Statistics, Faculty of Science, UTS, 1 Stella Vista Pl, Greenwich, NSW 2065, Australia Available online 29 March 2013 Communicated by: Associate Editor Frank Vignola a Abstract There is a general consensus that solar power is one of the cleanest energy technologies available. Nevertheless, investment in largescale Solar Power Generators (SPGs) is largely impeded by the intermittent nature of solar power. Since the electricity market has a critical responsibility to maintain the reliability of energy supply, the SPG can be registered only as the market semi-scheduled generator (AEMC, 2011). This option excludes the advantages of providing baseload supply, which in turn impedes efficient market contracting for SPGs...
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... A Skeptic's Guide to Computer Models by John D. Sterman This article was written by Dr. John D. Sterman, Director of the MIT System Dynamics Group and Professor of Management Science at the Sloan School of Management, Massachusetts Institute of Technology, 50 Memorial Drive, Cambridge, MA 02139, USA; email: jsterman@mit.edu. Copyright © John D. Sterman, 1988, 1991. All rights reserved. This paper is reprinted from Sterman, J. D. (1991). A Skeptic's Guide to Computer Models. In Barney, G. O. et al. (eds.), Managing a Nation: The Microcomputer Software Catalog. Boulder, CO: Westview Press, 209-229. An earlier version of this paper also appeared in Foresight and National Decisions: The Horseman and the Bureaucrat (Grant 1988). A S KEPTIC'S GUIDE TO COMPUTER MODELS 2 The Inevitability of Using Models........................................................................3 Mental and Computer Models..............................................................................2 The Importance of Purpose..................................................................................3 Two Kinds of Models: Optimization Versus Simulation and Econometrics.......4 Optimization.............................................................................................4 Limitations of Optimization..........................................................5 When To Use Optimization....................
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... Power Resources Power or energy comes from different sources: solar, wind, hydroelectricity, nuclear energy, fossil fuel and so on. A society or civilization cannot survive for a moment without power or energy. So, sufficient energy is the basic foundation for the development of a nation. Daily needs, industries, transportation and communication and so on are governed by energy sufficiency. What is energy? The stored ability to perform work or produce heat comes in many forms-electric, mechanical, or nuclear, among others. This is called energy. Sources of energy: a) Renewable resources: It includes wood, water, and solar. This kind of resources can be produced further. b) Non-renewable resources: It encompasses fossil fuel, natural gas, coal, oil and so on. Questions for the students: Bangladesh is an energy deficit country. Why? Meeting energy demand is the key to...
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...HBR Article: Diamonds in the Data Mine March 31, 2010 By Gary Loveman This is a pretty nice and short yet highly effective article that outlines the importance of providing an exceptional customer service in today’s service industry, especially in the gaming industry as it is the case of Harrah’s Entertainment casino. Actually, from its inception, Harrah’s former CEO Phil Satre had instituted this policy of “changing Harrah’s from an operations-driven company that viewed each casino as a stand-alone business into a marketing-driven company that built customer loyalty to all Harrah’s properties”. In doing so, Satre asked Gary Loveman to head a strategy to affect this change in all Harrah’s organizations, and so Loveman did follow through on this task. He effectively focused on delivering customer service and on understanding and marketing effectively to the customer. This is the secret to Harrah’s success, which allows him and Harrah’s to maintain loyalty from its customers based on the database they had collected over the years, as they were able to identify their customers’ needs and wants as well as to have good reward and incentive programs in place to recognize their clientele according to the time and money they spend gambling over their facilities. Yet, for their workforce, Harrah’s instituted a bonus system tied to job satisfaction. “Rewards hinge on everyone’s performance at a casino- and on customer satisfaction, not a property’s financial performance”. Also...
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...By Dr. Robert E. Brooks, RBAC, Inc. and C.P. Neill, Logistic Solutions, Inc. Abstract Gridnet is an embedded-network-based LP system for simultaneously optimizing very large natural gas sourcing and transportation acquisition operations. Using the PS/2-based Wizard i860 co-processor, Gridnet solves generalized network problems with over 18,000 nodes and 200,000 arcs in under five minutes. The paper discusses the need and requirements for this system as well as the technical approach, implementation, and effects of installation at five user sites. The Setting Since the mid-1970's, we have been developing computer-based decision support systems involving the natural gas industry. In 1975 in his Ph.D. dissertation, Robert Brooks developed the first math programming model explicitly to represent all of the interstate natural gas pipelines in a comprehensive nationwide model of the supply, demand, and transportation of natural gas [1]. This served as the basis for forecasting models used by the U.S. Department of Energy and Federal Energy Regulatory Commission during the 1970's [2, 3, 4, 5]. In the first such model, gas supply was divided up into about thirty production regions and demand was specified by state. Each pipeline was represented by a network of nodes and arcs, one node for each state served by the pipeline, one arc connecting each pair of states whose border was crossed by the pipeline in each allowable direction. All pipeline interconnects between each pair of pipelines...
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...Business Analysis III - Anadarko Petroleum Corporation Leonard VanBerkel MGT/521 October 15, 2012 Kirk Davis Business Analysis III - Anadarko Petroleum Corporation Anadarko Petroleum Corporation (Anadarko); head office in The Woodlands, Texas, employees 4,800 people and is a Fortune 500 company with recorded revenues of $13.967 billion for fiscal year ending 2011. This represented an increase of 28% over 2010. Anadarko posted record sales volume in 2011. Contrasted against Anadarko is Exxon, which had reported revenues over the same period of $452.926 billion and was ranked number one for most profitable companies, realizing profits of $41.060 billion (CNNMoney, 2012). Anadarko is ranked 192nd whereas Exxon is ranked 1st. The most glaring difference financially between the two companies is not just the large revenue gap, but the difference in profitability. Despite achieving record sales numbers and double digit growth, Anadarko recorded a net loss of $2.649 billion for fiscal year ending 2011 (CNNMoney, 2012). There are a large number of companies in the petroleum industry that realized large profits on varying degrees of revenues in 2011, yet Anadarko showed large losses. The question that arises is why did Anadarko lose money, while so many other companies in the same industry were profitable? A SWOT (strengths, weaknesses, opportunities, threats) analysis has been performed on Anadarko to determine if it is worth investing in this company, or consider it another casualty...
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...Con Block AT-Climate Change hurts the economy Sub Point A: Climate change is not caused by human activities. Created: May 31, 2011, 2:43 PM Last Updated: September 01, 2015, 4:16 PM Written by Joseph Bast and James M. Taylor https://www.heartland.org/ideas/global-warming-not-crisis Heartland Institute, which has been studying global warming since 1994. There is plenty of evidence that there is no scientific consensus that climate change is man-made and dangerous (Bast and Spencer, 2014). The multi-volume Climate Change Reconsidered series cites thousands of articles appearing in peer-reviewed journals that challenge the basic underlying assumptions of AGW (Climate Change Reconsidered 2008, 2009, 2011, 2013, 2014). More than 30,000 scientists have signed a petition saying there is no threat that man-made global warming will pose a threat to humanity or nature (Petition Project). Alarmists often cite an essay by Naomi Oreskes claiming to show that virtually all articles about global warming in peer-reviewed journals support the so-called consensus. But a no-less-rigorous study by Benny Peiser that attempted to replicate her results searched the abstracts of 1,117 scientific journal articles on “global climate change” and found only 13 (1 percent) explicitly endorse the “consensus view” while 34 reject or cast doubt on the view that human activity has been the main driver of warming over the past 50 years. A more recent search by Klaus-Martin Schulte of 928 scientific...
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...ASSIGNMENT 1 Introduction : Recent years ,Malaysia is keeping on priming of economy,their aim is to determine the Malaysia into a high-income developed nation.so they has been proposed the economic transformation programme ,the programme is a comprehensive effort that will transform Malaysia into a high-income nation ,and change the country's main productivity from the agricultural to the Industrialization by 2020. The Economy transformation programme is follow a quite different way from the past to develop the economy . This programme planning to focus on the core development area : the 12 national key economic areas(NKEAs) ,including oil gas and energy ,palm oil and rubber, financial services,tourism,business service,electrical and electronic,wholesale and retail ,education,healthcare , Communications Content and Infrastructure; Agriculture; and Greater Kuala Lumpur/Klang Valley.which are choose from the Malaysia' s advantage industry and the future potential industry.those key economic areas will bring a huge amount of profit contribute to Malaysia 's economy ,and those areas will be acquired the public investment and government support in prior。Besides,those Key economic area will be get policy reforms such as the remove the economic competition barriers and market liberalization .This program will involve the deliberate choices and trade-offs. Prioritize investment in key economic sectors means less investment in other areas. To bring about meaningful change for...
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...such as upstream which includes oil exploration, extraction, shipping and wholesale operations, downstream which includes marketing, refining, and retail operations and chemical division. In 2012, with rapid growth, ExxonMobil becomes number 1 in Forbes Global 2000 list. * Mission Exxon Mobil Corporation is committed to being the world's premier petroleum and petrochemical company (ExxonMobil, 2006). To accomplish this mission, not only the financial and operating objectives must be achieved, the company should also follow specific ethical standards to build a perfect relationship between the company and stockholders, including shareholders, customers, employees and communities. * Objectives and strategies For such a large oil and gas company, each business of ExxonMobil is indispensable, no matter the upstream, downstream or the chemical division. And each business...
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...to meet the future needs. Planning is a process for accomplishing purposes. It is a blue print of growth and a road map of development. It helps in deciding objectives both in quantitative and qualitative terms. It is setting of goals on the basis of objectives and keeping in the resources. A plan can play a vital role in helping to avoid mistakes or recognize hidden opportunities. Planning helps in forecasting the future, makes the future visible to some extent. It bridges between where we are and where we want to go. Planning is looking ahead. Forecasting is the process of making statements about events whose actual outcomes (typically) have not yet been observed. A commonplace example might be estimation for some variable of interest at some specified future date. Prediction is a similar, but more general term. Both might refer to formal statistical methods employing time series, cross-sectional or longitudinal data, or alternatively to less formal judgemental methods. In any case, the data must be up to date in order for the forecast to be as accurate as possible. Forecasting can be...
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... * For students without basic knowledge of computer **For students with basic knowledge of computer & mandatory for students with Major in subjects offered from the SECS Numeracy MAT 100* MAT 210* Basic University Mathematics 1 Basic University Mathematics 2 6 3 3 3 *MAT 100 and MAT 210 mandatory for SLAS majors(English, Media & Communication, Anthropology) other than Sociology MAT 101* MAT 211* MAT 102* MAT 212* Intermediate University Mathematics II Probability and Statistics Introduction to Linear Algebra & Calculus Probability & Statistics for Sc. & Engr. 3 3 3 3 **MAT 101and MAT 211 mandatory for Business/SESM/Sociology majors $MAT 102 and $MAT 212 is mandatory for students with major in Engineering and Computer Science Natural 7-8 Sciences CHE 101* Chemistry 3 CHE 101L* PHY 101** PHY 101L** PHY 102** PHY 102** BIO 102 BIO 102T CHE 102 CHE102T ENV 101 ENV 102 ENV 102T PSY 201 Chemistry Lab University Physics-I University Physics-I Lab University Physics-II University Physics-II Lab...
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...Decision Support Systems The material has been prepared by considering the prescribed textbook, internet and assignments given by the students (BBM 2011-2014 Batch). The material can be further improved by adding more insightful examples and explanation. The material may not be exhaustive and should be taken as a guide to help in better learning of the subject. ALL THE BEST Unit – I: 1. What is DSS? Explain the Characteristics, Benefits and Limitations of DSS. Definition: A decision support systems is a system under the control of one or more decision makers that assist in the activity of decision making by providing set of tools intended to impose structure to the decision making situation and improve the effectiveness of the decision outcome. Characteristics of DSS: * Employed in semistructured or unstructured decision contexts * Intended to support decision makers rather than replace them * Supports all phases of the decision-making process * Focuses on effectiveness of the process rather than efficiency * Is under control of the DSS user * Uses underlying data and models * Facilitates learning on the part of the decision maker * Is interactive and user-friendly * Is generally developed using an evolutionary, iterative process * Can support multiple independent or interdependent decisions * Supports individual, group or team-based decision-making Situation of Certainty Structured Unstructured Situation...
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...Overview of Applications by Discipline ECONOMICS Estimating sensitivity of demand to price 352–356 Pricing problems 352–366, 422–427 Estimating cost of power 363–366 47–56, Assessing a utility function 554–556 Estimating demand for products 632–638, 649–650, 764–771, 965 Subway token hoarding 792 FINANCE AND ACCOUNTING Collecting on delinquent credit accounts 14–16 Cost projections 29–33 Finding a breakeven point 33–41 Calculating NPV 57–62 Calculating NPV for production capacity decision 58–62 Portfolio management 173–178, 345–346, 387–394, 442–444, 689–691 Pension fund management 178–182 Financial planning 210–214, 676–681, 734–735 Arbitrage opportunities in oil pricing 215–219 Currency trading 220 Capital budgeting 290–295 Estimating stock betas 396–401 Hedging risk with put options 407–408 Stock hedging 407–408 Asset management 409–410 New product development 503–504, 574, 673–676, 715–722 Bidding for a government contract 513–518, 523–533, 653–657 Investing with risk aversion 557–560 Land purchasing decision 575 Risk analysis 582–583 Liquidity risk management 651–653 Estimating warranty costs 657–661 Retirement planning 681–685 Modeling stock prices 685–686 Pricing options 686–689, 691–693 Investing for college 732 Bond investment 733 HUMAN RESOURCES AND HEALTH CARE Fighting HIV/AIDS 23–24 DEA in the hospital industry 184–189 Salesforce allocation problems 454–456 Assigning MBA students to teams 462 Selecting...
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...Tomorrow’s World By Marvin J. Cetron and Owen Davies Forces in the Natural and Institutional Environments Introduction For nearly half a century, Forecasting International has been tracking the forces that shape our future. Some 20 years ago, we codified our observations into a list of trends that forms the basis for much of our work. For each of our projects, we compare the specific circumstances of an industry or organization with these general trends and project their interactions. This often allows us to form a remarkably detailed picture of what lies ahead. This is Part Two of FI’s periodic trend report. It covers trends in energy, the environment, technology, management and institutions, and terrorism. (Part One, published in the May-June 2010 issue of THE FUTURIST, tracked economic, population, societal, family, and work trends.) Because this forecast project is ongoing, the authors — and the World Future Society — welcome your feedback. 38 THE FUTURIST July-August 2010 © 2010 World Future Society • 7910 Woodmont Avenue, Suite 450, Bethesda, MD 20814, U.S.A. • All rights reserved. JULIEN GRONDIN / ISTOCKPHOTO Energy Trends 40% in 1999 to about 37% in 2020. n Despite efforts to develop alternative sources of energy, oil consumption is still rising rapidly. • The world used only 57 million barrels of oil per day in 1973, when the first major price shock hit. By 2008, it was using 86 million barrels daily, according to...
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...Journal of Computational Science 2 (2011) 1–8 Contents lists available at ScienceDirect Journal of Computational Science journal homepage: www.elsevier.com/locate/jocs Twitter mood predicts the stock market Johan Bollen a,∗,1 , Huina Mao a,1 , Xiaojun Zeng b a b School of Informatics and Computing, Indiana University, 919 E. 10th Street, Bloomington, IN 47408, United States School of Computer Science, University of Manchester, Kilburn Building, Oxford Road, Manchester M13 9PL, United Kingdom a r t i c l e i n f o Article history: Received 15 October 2010 Received in revised form 2 December 2010 Accepted 5 December 2010 Available online 2 February 2011 Keywords: Social networks Sentiment tracking Stock market Collective mood a b s t r a c t Behavioral economics tells us that emotions can profoundly affect individual behavior and decisionmaking. Does this also apply to societies at large, i.e. can societies experience mood states that affect their collective decision making? By extension is the public mood correlated or even predictive of economic indicators? Here we investigate whether measurements of collective mood states derived from largescale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time. We analyze the text content of daily Twitter feeds by two mood tracking tools, namely OpinionFinder that measures positive vs. negative mood and Google-Profile of Mood States (GPOMS) that measures mood ...
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