可再生能源发电项目投资决策的实物期权方法

由于传统DCF分析方法不能完全满足可再生能源发电项目投资决策的需要,本文提出了在可再生能源发电项目投资决策中引入实物期权的思路,初步讨论了可再生能源发电项目投资的实物期权模型,并以风力发电项目投资为例具体讨论了实物期权模型的应用方法.     

复合实物期权方法在风电项目投资决策中的应用

鉴于目前风电项目评价中一般采取传统的现金流贴现(DCF)方法,忽视了现实投资机会中战略经营的柔性价值,导致部分优质项目淘汰;而且当前学者们关于风电项目投资决策中这种柔性价值的研究,主要集中于风电项目投资机会中单个实物期权的模型和应用研究,但是现实中风电项目投资机会往往具有复合实物期权特性.从风电项目分期投资开发中复合实物期权特性分析着手,结合具体的风电项目实例,运用复合实物期权二叉树定价模型进行计算其投资价值,并同传统的DCF方法进行投资决策比较分析.可以看出,复合实物期权二叉树分析方法能够有效评估项目灵活性的价值,为经营灵活性和战略适应性进行定价.     

基于实物期权理论的供电企业安全投资决策模型

针对传统安全投资决策方法的缺陷,将实物期权理论引入到供电企业安全投资决策中,构建了实物期权理论的供电企业安全投资决策框架,并建立了基于二叉树模型的供电企业安全投资决策模型。实例验证了模型的有效性,为供电企业安全投资提供了新的思路。     

基于实物期权的电动汽车充电站投资决策评估研究

目前关于电动汽车充电站建设的研究局限于选址和定容,考虑投资风险并进行长期规划的研究较少。为避免传统投资决策方法忽略不确定性的投资风险,提出基于实物期权的电动汽车充电站投资决策评估方法。首先,针对充电站投资的收益进行分析,提出充电站投资收益具有多重不确定性;然后,在B-S模型基础上嵌套充电量波动和充电站成本变动的波动率模型;最后,通过对不同区域充电站投资的实物期权价值进行仿真分析,验证了模型的有效性。     

基于实物期权理论的风电项目投资评价方法研究

传统的投资决策方法(如净现值法)只适用于期限短、不确定性小的项目投资决策,而实物期权法恰好能克服以上问题。实物期权法弥补了传统投资决策方法的缺陷,可以在不确定性较高的环境下准确地评估项目的价值,相对于传统的评价方法更适合风电项目的投资评价。影响实物期权价值的因素中只有标的资产波动率σ(即市场风险)是引入实物期权方法时应予确认的未知变量,它的取得需要考虑多项风险对项目价值的影响,而准确识别各种风险并精确计算出其对项目价值的影响程度相当困难。因此,可应用BP神经网络算法来模拟项目价值波动率。首先选用3层的BP神经网络模型,包括输入层、隐含层、输出层;然后确定影响项目价值波动率的因素,并模拟计算。实证研究表明,将基于BP神经网络修改后的实物期权方法应用于对风电项目价值的评估,具有充分的理论基础,并且是可行的。但该模型还有一些需要改进的地方,比如在BP神经网络的训练过程中需要大量的样本,这些数据的采集可能会存在问题;在讨论如何确定市场价格波动率时,还可以考虑更多影响因素,从而使计算结果更为准确。     

基于实物期权法的600 MW火电机组CCS-EOR项目价值评估

600 MW燃煤发电机组项目采用CCS-EOR技术脱除CO₂,将捕集的CO₂用于油田驱油。通过合理假设,采用B-S期权中欧式看涨模型求解,基于实物期权法分析项目的价值,对比实物期权法与净现值法计算项目的差异,对比原油价格和碳交易价格的波动率的变化,计算实物期权法三种假设条件下的项目价值变化规律,在原油价格变动的条件下计算实物期权法与净现值法对项目价值的影响度。结果表明：结合实物期权法与净现值法,对项目投资时间的决策优于净现值单一的决策判断条件;实物期权法对项目的投资可将风险、不确定条件等转化为项目的期权价值,有效弥补了净现值法在项目决策中立即投资和放弃投资单一决策的不足;随选定参数波动率的不断增大,实物期权法计算所得项目价值敏感度逐渐提高。     

基于实物期权理论的光伏发电投资决策模型

在新的电力市场环境下,光伏发电项目投资面临更多的投资风险。为了有效保证电力供应和二氧化碳排放的降低,需要政府有关部门制定合适的政策引导投资者向清洁能源发电项目投资。即无论是政策制定者还是投资者都迫切需要一个客观的决策框架来指导不确定性环境下的发电项目投资。针对光伏发电项目特点,并综合当前在该领域的研究成果,提出了基于实物期权理论的光伏发电投资决策模型,丰富并发展了实物期权理论在电力投资决策中的应用,有一定的理论和实际指导意义。     

基于实物期权的水电站项目投资时机决策模型及应用

为弥补水电站项目传统投资决策方法的缺陷,结合水电站项目投资特点,修改了传统净现值法中投资可逆和投资时机不可延迟的假设,基于实物期权理论建立了水电站项目投资时机决策模型,给出了水电站项目最佳投资时机项目价值计算公式,最后通过数学算例验证了模型的可行性,并在此基础上分析了延迟投资的机会成本系数对项目最佳投资时机的影响。结果表明,投资的不可逆性和可延迟性很大程度上影响了项目价值的评估及最佳投资时机的选择,该模型的建立为水电站项目投资时机的合理选择提供了参考。     

基于实物期权的电网项目投资决策经济性评价

针对传统的净现值法应用中的缺陷日益显露.基于电网投资的特点,引入了实物期权法,给出了电网投资中实物期权法的一般步骤,采用B-S模型与净现值法分析了电网建设过程中的不确定因素,并采用分阶段投资期权模型对投资项目做了进一步研究.结果表明,实物期权法更准确-估价结果更符合电网投资的实际价值,为正确作出风险投资决策提供了指导.     

不同情景下太阳能光伏分布式电源投资决策评估研究

为研究各种情景及成本不确定性下微网分布式发电投资决策问题,构建了基于不可逆性的微电网光伏分布式电源投资决策模型,以某地区微电网太阳能光伏分布式电源决策评估为例,采用实物期权法获得引发分布式发电投资行为的投资成本限值,分别建立基于微电网运营灵活性及可中断负荷的光伏电源投资期权价值模型,分析了4种工况下的投资期权类型的成本效益现值及净现值,并求出最优期权决策方案和决策值。     

Decision analysis on generation capacity of a wind park

The investment decision on generation capacity of a wind park is difficult when wind studies or data are neither available nor sufficient to provide adequate information for developing a wind power project. Although new measurement is possible but it is definitely time consuming. To determine the optimum capacity, decision analysis techniques are proposed in this paper to cope with uncertainties arising from wind speed distribution and power–speed characteristics. The wind speed distribution is modeled from the measured data, the Rayleigh distribution, and the Weibull distribution. The power–speed curve of a wind turbine from cut-in speed to rated speed is modeled by using linear, parabolic, cubic, and quadratic characteristics. The optimization model is formulated as a mixed-integer nonlinear programming problem. The constraints are considered as interval bounds so that a set of feasible solutions is obtained. The optimum solution can be determined by using the profit-to-cost and profit-to-area ratios as performance metrics of investment. Decision analysis rules are then applied to overcome the uncertainty problem and to refine the investment plan. The proposed procedure has been tested with the wind power project of the Electricity Generating Authority of Thailand.     

Emissions trading and investment decisions in the power sector—a case study in Finland

Organizations, which consider investment in or divestment of power production licences/capacity within the European Community, are exposed to the impacts of the European Union Emission allowance Trading Scheme (EU ETS). In this paper, the consequences of the EU ETS on investment decisions are explored in a country-specific setting in Finland. First, we review the general mechanisms through which the EU ETS influences size, timing and cashflows of an investment. Next, we discuss the projected changes in Finnish power producers’ investment environment and examine the financial impacts due to the EU ETS on a case investment decision, a hypothetical condensing power plant (250 MW_e). The standard discounted cash flow (DCF) analysis is extended to take into account the value of two real options: the option to wait and the option to alter operating scale. In a quantitative investment appraisal, the impact of emissions trading not only depends on the expected level of allowance prices, but also on their volatility and correlation with electricity and fuel prices. The case study shows that the uncertainty regarding the allocation of emission allowances is critical in a quantitative investment appraisal of fossil fuel-fired power plants.     

Dynamic model for market-based capacity investment decision considering stochastic characteristic of wind power

This paper proposes a decentralized market-based model for long-term capacity investment decisions in a liberalized electricity market with significant wind power generation. In such an environment, investment and construction decisions are based on price signal feedbacks and imperfect foresight of future conditions in electricity market. System dynamics concepts are used to model structural characteristics of power market such as, long-term firms’ behavior and relationships between variables, feedbacks and time delays. For conventional generation units, short-term price feedback for generation dispatching of forward market is implemented as well as long-term price expectation for profitability assessment in capacity investment. For wind power generation, a special framework is proposed in which generation firms are committed depending on the statistical nature of wind power. The method is based on the time series stochastic simulation process for prediction of wind speed using historical and probabilistic data. The auto-correlation nature of wind speed and the correlation with demand fluctuations are modeled appropriately. The Monte Carlo simulation technique is employed to assess the effect of demand growth rate and wind power uncertainties. Such a decision model enables the companies to find out the possible consequences of their different investment decisions. Different regulatory policies and market conditions can also be assessed by ISOs and regulators to check the performance of market rules. A case study is presented exhibiting the effectiveness of the proposed model for capacity expansion of electricity markets in which the market prices and the generation capacities are fluctuating due to uncertainty of wind power generation.     

Valuation of projects for power generation with renewable energy: A comparative study based on real regulatory options

This comparative study evaluates an investment project on renewable energy based on wind power. We have conducted the study in three European Union countries: Denmark, Finland and Portugal. We have modelled the main uncertainties that affect this kind of project, such as the cost and production of electric power, investment costs and consumer price index. For each of these countries, we have analysed the mechanisms of public support for wind energy. We have identified the real options included in the regulatory frameworks of these three countries and assessed how they affect the expanded net present value of the project. To this end, we have used two different methods of option valuation: the Monte Carlo method and the binomial method. We have proved that the obtained results using both methods are quite similar. Finally, we have evaluated the public incentives for wind energy offered in each of these three countries and concluded that, in economic terms, Finland is the country with the strongest support for this kind of energy, followed by Denmark and, in the last place, Portugal.     

可再生能源等比补贴系数及投资估值模型研究

  目的  随着我国“碳中和、碳达峰”目标的提出,可再生能源发电企业面临着快速扩大装机规模,大力发展投资并购的诉求,在我国存量补贴资金缺口逐步增大的背景下,如何确定可再生能源项目的补贴收入,并采用合理方法对项目估值,一直是并购决策的难点。  方法  重点关注了2020年发布的补贴新政,测算了可再生能源存量补贴的兑付系数,基于多情景假设补贴现金流入的规模及时间。  结果  通过等比补贴系数测算及投资估值模型,明确了我国补贴缺口的收口时间及各年度的等比补贴系数,并基于可再生能源项目特点,研究选定最佳估值方法。  结论  通过估值模型对部分地区的海上风电和陆上风电项目进行了估值,为企业投资及并购提供了重要决策支撑。     

A real option-based simulation model to evaluate investments in pump storage plants

Investments in pump storage plants are expected to grow especially due to their ability to store an excess of supply from wind power plants. In order to evaluate these investments correctly the peculiarities of pump storage plants and the characteristics of liberalized power markets have to be considered. The main characteristics of power markets are the strong power price volatility and the occurrence of prices spikes. In this article a valuation model is developed capturing these aspects using power price simulation, optimization of unit commitment and capital market theory. This valuation model is able to value a future price-based unit commitment planning that corresponds to future scope of actions also called real options. The resulting real option value for the pump storage plant is compared with the traditional net present value approach. Because this approach is not able to evaluate scope of actions correctly it results in strongly smaller investment values and forces wrong investment decisions.     

分布式发电的灵活性投资策略研究

为激励投资者投资以促进分布式发电的建设,研究了天然气价格不确定性下,基于实物期权模型的燃气分布式发电灵活性投资策略.构建了分布式发电投资策略的实物期权模型,提出一种灵活的时序投资策略,并分析了策略的投资阈值和项目价值,计算分析了4种不同的投资策略在不同波动水平下每种策略的天然气投资价格阈值及其适用性.研究结果表明,实物期权理论可有效应用于分布式发电投资策略研究,可为投资者根据价格信息灵活选择投资策略、提高经济效益提供指导.     

Optimum sizing of wind-pumped-storage hybrid power stations in island systems

Pumped storage is generally viewed as the most promising technology to increase renewable energy source (RES) penetration levels in power systems and particularly in small autonomous island grids. Combined wind and pumped-storage “virtual power plants”, called hybrid power stations (HPS), constitute a realistic and feasible option to achieve high penetrations, provided that their components are properly sized. In this paper, the optimum sizing is investigated for a pumped storage HPS operating in an island system. The analysis addresses the sizing of the main HPS components (hydro turbines, pumps, wind farm, reservoirs), adopting either the investor’s perspective, where the objective is to maximize the return on the HPS investment, or a system perspective, where the optimization target is the maximization of RES penetration, along with maintaining the lowest possible generation cost in the system. Genetic Algorithms (GAs) are applied for the optimization and a real isolated island power system is used as a study case. The adopted operating policy and pricing principles, which critically affect the optimal sizing of an HPS project, are based on the existing regulatory framework for storage stations in Greek islands.