{"title":"美国和欧洲的能源规划:基于投资组合的方法","authors":"Paul S. Lowengrub, Spencer Yang","doi":"10.2139/ssrn.1105032","DOIUrl":null,"url":null,"abstract":"Traditional energy planning in Europe and the United States focuses on finding the least-cost generating alternative. This approach worked sufficiently well in a technological era marked by relative cost certainty, low rates of technological progress, technologically homogenous generating alternatives, and stable energy prices. However, today's electricity planner faces a diverse range of resource options and a dynamic, complex, and uncertain future. Attempting to identify least-cost alternatives in this dynamic and uncertain environment is virtually impossible. As a result, more appropriate techniques are required to find strategies that remain economical under a variety of uncertain future outcomes.Given the uncertain environment, it makes sense to shift electricity planning from its current emphasis on identifying the least-cost technologies to the evaluation of alternative electricity generating portfolios and strategies. The techniques for doing this are rooted in modern finance theory - in particular mean-variance portfolio theory. The mean-variance portfolio analysis proposed in this report exemplifies how portfolio costs and risks can be examined and incorporated into policy decisions about future generating resources.This paper applies portfolio-theory optimization concepts from the field of finance to produce an expository evaluation of the multiple regions in the United States and Europe. Although the results are expository, they help show how today's energy planners can assess the potential changes to a portfolio's risks and costs that result from adding renewable resources (such as wind, hydro, and biomass) that have their own individual risk and cost profiles. The resulting risks and costs of alternative combinations of assets will be quantified, and this allows those portfolios that provide the best combinations of costs and risks to be identified as efficient frontier. Conversely, for any given level of cost, there is an associated minimum-risk portfolio. Portfolio analysis allows for the consideration of risk preferences when choosing among portfolios, as well as for the examination of the trade-offs among various risks and costs.","PeriodicalId":170505,"journal":{"name":"Macroeconomics eJournal","volume":"123 9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy Planning in the United States and Europe: A Portfolio-Based Approach\",\"authors\":\"Paul S. Lowengrub, Spencer Yang\",\"doi\":\"10.2139/ssrn.1105032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional energy planning in Europe and the United States focuses on finding the least-cost generating alternative. This approach worked sufficiently well in a technological era marked by relative cost certainty, low rates of technological progress, technologically homogenous generating alternatives, and stable energy prices. However, today's electricity planner faces a diverse range of resource options and a dynamic, complex, and uncertain future. Attempting to identify least-cost alternatives in this dynamic and uncertain environment is virtually impossible. As a result, more appropriate techniques are required to find strategies that remain economical under a variety of uncertain future outcomes.Given the uncertain environment, it makes sense to shift electricity planning from its current emphasis on identifying the least-cost technologies to the evaluation of alternative electricity generating portfolios and strategies. The techniques for doing this are rooted in modern finance theory - in particular mean-variance portfolio theory. The mean-variance portfolio analysis proposed in this report exemplifies how portfolio costs and risks can be examined and incorporated into policy decisions about future generating resources.This paper applies portfolio-theory optimization concepts from the field of finance to produce an expository evaluation of the multiple regions in the United States and Europe. Although the results are expository, they help show how today's energy planners can assess the potential changes to a portfolio's risks and costs that result from adding renewable resources (such as wind, hydro, and biomass) that have their own individual risk and cost profiles. The resulting risks and costs of alternative combinations of assets will be quantified, and this allows those portfolios that provide the best combinations of costs and risks to be identified as efficient frontier. Conversely, for any given level of cost, there is an associated minimum-risk portfolio. Portfolio analysis allows for the consideration of risk preferences when choosing among portfolios, as well as for the examination of the trade-offs among various risks and costs.\",\"PeriodicalId\":170505,\"journal\":{\"name\":\"Macroeconomics eJournal\",\"volume\":\"123 9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Macroeconomics eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.1105032\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Macroeconomics eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.1105032","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Energy Planning in the United States and Europe: A Portfolio-Based Approach
Traditional energy planning in Europe and the United States focuses on finding the least-cost generating alternative. This approach worked sufficiently well in a technological era marked by relative cost certainty, low rates of technological progress, technologically homogenous generating alternatives, and stable energy prices. However, today's electricity planner faces a diverse range of resource options and a dynamic, complex, and uncertain future. Attempting to identify least-cost alternatives in this dynamic and uncertain environment is virtually impossible. As a result, more appropriate techniques are required to find strategies that remain economical under a variety of uncertain future outcomes.Given the uncertain environment, it makes sense to shift electricity planning from its current emphasis on identifying the least-cost technologies to the evaluation of alternative electricity generating portfolios and strategies. The techniques for doing this are rooted in modern finance theory - in particular mean-variance portfolio theory. The mean-variance portfolio analysis proposed in this report exemplifies how portfolio costs and risks can be examined and incorporated into policy decisions about future generating resources.This paper applies portfolio-theory optimization concepts from the field of finance to produce an expository evaluation of the multiple regions in the United States and Europe. Although the results are expository, they help show how today's energy planners can assess the potential changes to a portfolio's risks and costs that result from adding renewable resources (such as wind, hydro, and biomass) that have their own individual risk and cost profiles. The resulting risks and costs of alternative combinations of assets will be quantified, and this allows those portfolios that provide the best combinations of costs and risks to be identified as efficient frontier. Conversely, for any given level of cost, there is an associated minimum-risk portfolio. Portfolio analysis allows for the consideration of risk preferences when choosing among portfolios, as well as for the examination of the trade-offs among various risks and costs.