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.     

Investment risks in power generation: A comparison of fossil fuel and renewable energy dominated markets

Due to their high capital intensity, weather dependent renewable energies (RES) such as solar and wind face considerable investment risks in power markets. In addition, their uncertain production volumes also affect the investment risks of other plant types through the impact on power prices and residual demand. Increasing RES shares thus potentially increase overall investment risks in power markets, which many analysts consider to be a potential problem. Against this background, this paper compares investment risks of different technologies in markets with increasing shares of variable RES. It further analyses how generation mixes are affected by these investment risks if the risks are evaluated on a stand-alone basis or in a plant portfolio context of a private firm. For this purpose, a stylized investment and dispatch model is used to conduct Monte Carlo simulations from which risk measures are derived. The results show that capital intensive RES face the highest stand-alone risks, since their profits are most affected by the power price risk. However, the results further indicate that the stand-alone risks of variable RES decrease with their share in the market because of a negative correlation of output and price risk. In addition, RES have a risk benefit in firm plant portfolios in terms of constituting a hedge against losses of fossil fuel plants. This positive portfolio effect, however, rapidly decreases and becomes negative with increasing RES shares in the market.     

The impact of Chinese carbon emission trading scheme (ETS) on low carbon energy (LCE) investment

China is planning to introduce emission trading scheme (ETS) to decrease CO₂ emission. As low carbon energy (LCE) will play a pivotal role in reducing CO₂ emissions, our paper is to assess the extent and the conditions under which a carbon ETS can deliver LCE investment in China. We chose wind technology as a case study and a real-option based model was built to explore the impact of a number of variables and design features on investment decisions, e.g. carbon and electricity price, carbon market risk, carbon price floor and ceiling and on-grid ratio. We compute critical values of these variables and features and explore trade-offs among them. According to our work, a carbon ETS has a significant effect on wind power plant investment although it cannot support investment in wind power on its own. Carbon price stabilization mechanisms such as carbon price floor can significantly improve the effect of carbon ETS but the critical floor to support investment is still much higher than the carbon price in China pilot ETSs. Our results show that other policy measures will be needed to promote low-carbon energy development in China.     

Optimal investment strategies in decentralized renewable power generation under uncertainty

This paper presents a method for evaluating investments in decentralized renewable power generation under price un certainty. The analysis is applicable for a client with an electricity load and a renewable resource that can be utilized for power generation. The investor has a deferrable opportunity to invest in one local power generating unit, with the objective to maximize the profits from the opportunity. Renewable electricity generation can serve local load when generation and load coincide in time, and surplus power can be exported to the grid. The problem is to find the price intervals and the capacity of the generator at which to invest. Results from a case with wind power generation for an office building suggests it is optimal to wait for higher prices than the net present value break-even price under price uncertainty, and that capacity choice can depend on the current market price and the price volatility. With low price volatility there can be more than one investment price interval for different units with intermediate waiting regions between them. High price volatility increases the value of the investment opportunity, and therefore makes it more attractive to postpone investment until larger units are profitable.     

Electrolysers for mitigating wind curtailment and producing ‘green’ merchant hydrogen

The implementation electrolysis plant in combination with wind power plant is proposed, to absorb wind generation otherwise curtailed while generating ‘green’ hydrogen for the merchant hydrogen market. The objective are to (i) achieve exceptionally high wind power penetrations in future power systems, and (ii) derive hydrogen for sale in the existing merchant industrial market from surplus (zero cost) renewable electricity. The economic rationale is investigated for an isolated power system as a function wind penetration, wind curtailment target, electrolyser cost, hydrogen system efficiency and hydrogen sales price. The main outputs are the total annualized cost of wind power plant with electrolysis plant, net annual revenues and discounted pay-back periods. Unprecedented low values of pay-back period are attainable, relative to the implementation of wind power plant at low wind penetrations (Φ_W). For example, at Φ_W = 50%, a wind curtailment target of 80% allows the investment to be recovered after 4-7 years, provided the hydrogen system efficiency is ≥50% and the hydrogen sales price is 20-30 $/kg. Making use of some non-curtailed wind electricity to boost the utilization of the electrolyser stock is also investigated as a means for improving the return on investment.     

An investigation on the impacts of regulatory interventions on wind power expansion in generation planning

Large integration of intermittent wind generation in power system has necessitated the inclusion of more innovative and sophisticated approaches in power system investment planning. This paper presents a novel framework on the basis of a combination of stochastic dynamic programming (SDP) algorithm and game theory to study the impacts of different regulatory interventions to promote wind power investment in generation expansion planning. In this study, regulatory policies include Feed-in-Tariff (FIT) incentive, quota and tradable green certificate. The intermittent nature and uncertainties of wind power generation will cause the investors encounter risk in their investment decisions. To overcome this problem, a novel model has been derived to study the regulatory impacts on wind generation expansion planning. In our approach, the probabilistic nature of wind generation is modeled. The model can calculate optimal investment strategies, in which the wind power uncertainty is included. This framework is implemented on a test system to illustrate the working of the proposed approach. The result shows that FITs are the most effective policy to encourage the rapid and sustained deployment of wind power. FITs can significantly reduce the risks of investing in renewable energy technologies and thus create conditions conducive to rapid market growth.     

How does market power affect the impact of large scale wind investment in 'energy only' wholesale electricity markets?

In the short run, it is well known that increasing wind penetration is likely to reduce spot market electricity prices due to the merit order effect. The long run effect is less clear because there will be a change in new capacity investment in response to the wind penetration. In this paper we examine the interaction between capacity investment, wind penetration and market power by first using a least-cost generation expansion model to simulate capacity investment with increasing amounts of wind generation, and then using a computer agent-based model to predict electricity prices in the presence of market power. We find the degree to which firms are able to exercise market power depends critically on the ratio of capacity to peak demand. For our preferred long run generation scenario we show market power increases for some periods as wind penetration increases however the merit order counteracts this with the results that prices overall remain flat. Returns to peakers increase significantly as wind penetration increases. The market power in turn leads to inefficient dispatch which is exacerbated with large amounts of wind generation.     

基于风电机组可靠性的风电场平准化成本模型研究

考虑综合风电场总体运行成本、风电机组可靠性及风电场发电量等多个维度,从风电场全生命周期视角出发,建立基于风电机组可靠性的风电场平准化成本模型,并通过算例分析得出,提升风电机组可靠性可降低风电机组的故障维护成本,提高风电场运行小时数,进而降低风电场平准化成本。在此基础上测算当前阶段风电实现平价上网需达到的利用小时数,最后给出促进风电发展的合理化建议。     

Risk‐based optimal energy management of virtual power plant with uncertainties considering responsive loads

This paper proposes a stochastic scheduling model to determine optimal operation of generation and storage units of a virtual power plant (VPP) for participating in a joint energy and regulation service (RS) market under uncertainty. Beside electricity, the VPP provides required RSs according to the probability of delivery request in the electricity market. A new model for providing RS is introduced in which the dispatchable generation units are financially compensated with their readiness declarations and will be charged/paid for their real‐time down/up regulations. Besides, the VPP sets up incentive price‐quantity curves to benefit from the potential of demand side management in both energy and RS market. Within the model presented here, the VPP consists of two types of generation units: wind turbine and standby diesel generator; the latter is modeled by considering CO₂‐emission penalty costs. The given uncertainties are divided into two parts. Firstly, the uncertainties from the energy market price are simulated using information gap decision theory to evaluate the risk‐based resource scheduling for both risk‐taker and risk‐averse VPP. Other uncertainties affecting decision making such as wind turbine generation, load, regulation up/down calling probabilities, and regulation market prices are modeled via scenario trees. Three typical case studies are implemented to validate the performance and effectiveness of the proposed scheduling approach.     

Constraints on the effective utilization of wind power in China: An illustration from the northeast China grid

Even though China's wind power industry has experienced a rapid growth since the beginning of this century, the utilization of wind power is still worrisome. In 2010, about 30% of China's total installed capacity could not get access to the grid. And about 10% of China's total wind power generation was curtailed. The problem of wind power curtailment is more prominent in Northeast-China region. The main particularity of Northeast China Grid is as follows: during the long heating period in winter, combined heat and power thermal plants need to modify the turbine generator's output to meet the heating demand and thus the thermal power peak regulation capacity is reduced, as a result the barriers of wind power consumption are increased. This paper provides a new perspective of the constraints on the effective utilization of wind power in the Northeast China Grid. We argue that there are two categories of constrained factors: structural factor and operational factor. The former includes grid structure, wind source structure, power source structure, and market structure. The latter includes power price mechanism, dispatch mode arrangement, wind power integration codes, and wind power forecast. At last, we make policy recommendations: promote the coordination between wind farm investment and grid construction, strengthen interprovincial power trade mechanism, implement flexible pricing mechanisms as well as improve current dispatch mode, etc.     

市场环境下基于合作博弈的风-水-火电厂收益分配研究

随着电力系统的市场化发展,发电侧各电厂企业在保证区域电能供需平衡的前提下期望用合作的方式来获取更多收益并对其进行有效分配。通过非合作博弈的方式给出风、水、火区域电网常规的调度方式,并计算出风、水、火电厂的收益;以市场环境下各主体的趋利性作为出发点引入合作博弈思想,使风、水、火电厂3个参与者构成一个－联盟,保证有功功率供应的基础上,给予单位电量收益更多的水电、风电更多发电指标,并提出一种偏差MDP指标分配方式,分析表明Shapley值法及偏差MDP指标法处于核心中。同时,与非合作博弈条件下风、水、火电厂的收入相比,偏差MDP分配方式下各电厂收入分别提高了38.2%、20.5%、6.1%。     

Private and social benefits of a pumped hydro energy storage with increasing amount of wind power

In this paper, we calculate the long-term profitability of a pumped hydro energy storage (PHES) plant that is planned to be built in an old mine. We model the optimal PHES operation for several scenarios with different wind power penetration levels. Our modelling approach first involves estimating wholesale electricity prices for the day-ahead, intraday and balancing market as a function of wind power penetration. The estimated price profiles are implemented in a dynamic programming model, where the PHES plant maximises its balancing market revenue given the optimal commitment in the day-ahead market. We show that increasing the wind penetration changes the optimal PHES operation and increases the PHES profits. Additionally, we quantify how the costs of wind power balancing are affected by the PHES investment. Policy implications are drawn based on the estimated private and social benefits from the investment.     

Interconnector capacity allocation in offshore grids with variable wind generation

Different capacity allocation regimes have a strong impact on the economics of offshore wind farms and on interconnectors in offshore grids. Integrating offshore generation in offshore grids is currently a subject of discussion for different regions, e.g. the North Sea. A novel question is how the interconnector capacity should be allocated for wind generation and for international power trading. The main difficulty arises from the stochastic nature of wind generation: in a case with radial connections to the national coast, the wind park owner has the possibility of aggregating the offshore wind park with onshore installations to reduce balancing demand. This is not necessarily the case if the interconnector capacity is sold through implicit or explicit auctions. Different design options are discussed and quantified for a number of examples based on Danish, Dutch, German and Norwegian power markets. It is concluded that treating offshore generation as a single price zone within the interconnector reduces the wind operator's ability to pool it with other generation. Furthermore, a single offshore price zone between two markets will always receive the lower spot market price of the neighbouring zones, although its generation flows only to the high‐price market. Granting the high‐price market income for wind generation as the opposite design option reduces congestion rents. Otherwise, compensation measures through support schemes or different balancing responsibilities may be discussed. Copyright © 2012 John Wiley & Sons, Ltd.     

偏差电量考核下风光储混合发电商的市场均衡博弈研究

为了更直观地分析风光储混合发电商对市场均衡博弈结果和市场力的影响,在偏差电量考核衡量风光储混合发电出力随机波动性的基础上,综合考虑各发电商的出力限制和储能系统的运行约束,建立以风光储混合发电商和传统发电商收益最大化为目标的市场均衡博弈模型,调用CPLEX软件求解利用非线性互补函数处理得到的混合整数规划模型,并对比分析了风光储混合发电商作为价格接受者和影响者参与电力市场竞争对均衡博弈电价和投标出力的影响。结果表明,风光储混合发电商参与电力市场竞争可抑制传统发电商的市场力,对电价有显著的"削峰填谷"作用;当风光储混合发电商作为价格影响者时,对电价的影响会减弱,但其收益有所增加。     

Risk constrained self-scheduling of hydro/wind units for short term electricity markets considering intermittency and uncertainty

In view of the intermittency and uncertainty associated with both the electricity production sector of restructured power system and their competitive markets, it is necessary to develop an appropriate risk managing scheme. So that it is desirable to trade-off between optimum utilization of intermittent generation resources (i.e. renewable energy resources), uncertain market prices and related risks in order to maximize participants' benefits and minimize the corresponding risks in the multi-product market environment. The main goal of this paper is to investigate risk management by introducing a novel multi-risk index to quantify expected downside risk (EDR) which is caused by both the wind power and market price uncertainties. Value-at-Risk (VaR) method is used to assess the mentioned risk issue by the proposed weighted EDR, so that an optimal trade-off between the profit and risk is made for the system operations. Also, the roulette wheel mechanism is employed for random market price scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents. Moreover, the autoregressive integrated moving average (ARIMA) model is employed to characterize the stochastic wind farm (WF) generation by predetermined mean level and standard deviation of wind behavior as well as temporal correlation. The problem is formulated as a mixed-integer stochastic framework for a hydro-wind power system scheduling and tested on a generation company (GENCO).     

Study of MW-scale biogas-fed SOFC-WGS-TSA-PEMFC hybrid power technology as distributed energy system: Thermodynamic,exergetic and thermo-economic evaluation

Advanced biogas power generation technology has been attracting attentions, which contributes to the waste disposal and the mitigation of greenhouse gas emissions. This work proposes and models a novel biogas-fed hybrid power generation system consisting of solid oxide fuel cell, water gas shift reaction, thermal swing adsorption and proton exchange membrane fuel cell (SOFC-WGS-TSA-PEMFC). The thermodynamic, exergetic, and thermo-economic analyses of this hybrid system for power generation were conducted to comprehensively evaluate its performance. It was found that the novel biogas-fed hybrid system has a gross energy conversion efficiency of 68.63% and exergy efficiency of 65.36%, indicating high efficiency for this kind of hybrid power technology. The market sensitivity analysis showed that the hybrid system also has a low sensitivity to market price fluctuation. Under the current subsidy level for the distributed biogas power plant, the levelized cost of energy can be lowered to 0.02942 $/kWh for a 1 MW scale system. Accordingly, the payback period and annual return on investment can reach 1.4 year and about 20%, respectively. These results reveal that the proposed hybrid system is promising and economically feasible as a distributed power plant, especially for the small power scale (no more than 2 MW).     

Investors’ reaction to the government credibility problem: A real option analysis of emission permit policy risk

In relation to creating a CO₂ emission permit market, there are two types of climate change policy risks: (1) It is uncertain whether and when a cap-and-trade system will be implemented; and (2) once a policy is in place, there may be government credibility issues. This paper examines the effect of these policy risks on real option decisions of electric power plant investment. To model both an investment decision and generation flexibility, this study evaluates an exotic compound American option on multiple strips of European spread options through the implementation of least squares Monte Carlo simulation. Government credibility risk leads to more investment in “less green” resources and induces additional cash flow variation, which increases the average time to investment (value of waiting). However, in an extreme case, government credibility can actually hasten investment because the risk may be more favorable to electric power companies. Furthermore, if emission trading is planned to be implemented in the future (e.g., 2020), and the market believes that the probability of successful implementation is low, firms will build a “less green” plant early to benefit from the period before the green rule is applied.     

Pre-feasibility study of wind power generation in holyrood, newfoundland

The largest commercial thermal generating plant in Newfoundland is in Holyrood, Conception Bay. It has a generating capacity of 500 MW of electricity. During peak generation (winter months), the plant runs at near capacity with generation reaching as high as 500 MW. In addition to thermal generation about 900 MW is supplied to the grid by a number of hydro plants. This paper presents a pre-feasibility study of 25% of thermal power generation using wind turbines in the Holyrood area. Purpose of supplementing power generation from the thermal plant is to reduce emissions and fuel costs. Simulation results indicate that 16 Enercon's E-66, 2 MW wind turbines if installed near the site will provide a 25% renewable fraction. Supplementing 25% of the generation at Holyrood with wind power will reduce the cost of energy by CA$0.013/kWh. It will also reduce carbon emissions by almost 200,000 tons/year. This study indicates that a wind farm project at the Holyrood thermal generation station site is feasible.     

基于CVaR方法的风力发电项目投资风险度量

风力发电项目具备较为独立的特点,将CVaR方法引入风力发电项目的投资风险度量,不仅可以全面衡量技术风险、经济风险、政策风险等相关风险因素,同时可以最大限度地考虑投资者的损失承受底线。借助蒙特卡洛方法模拟风力发电的上网电量,很好地计量了风力发电的不确定性所带来的风险。以内蒙古地区某一风力发电项目为实例,分别计算了其VaR值和CVaR值。计算结果表明,CVaR方法能够更加谨慎有效地估计风力发电项目投资者的潜在损失。文章进一步研究了贴现率和电价等风险因素对风力发电项目整体风险的影响,认为较低的贴现率和较高的电价水平能够帮助投资者很好地规避投资风险。     

The Clean-Development Mechanism,stochastic permit prices and energy investments

We analyze the impact on energy investments stemming from different emission permit classes, by considering permits that are allocated inside the European Emission Trading Scheme and secondary Certified Emission Reduction (sCER) permits originating from the Clean Development Mechanism. One price taking firm which is subject to emission regulation has the choice to invest in gas or wind power plant. The firm faces uncertainty regarding stochastically evolving permit prices, while it receives a premium on the electricity price for wind energy. As a first step, we determine the value of the option to invest into a gas power plant over time. Then, we calculate the investment probability of a gas power investment in a range of policy scenarios. We find that allowing the usage of sCER permits in the present policy framework has a positive impact on gas power investment. Decoupling the price processes has a similar effect. If the quota of sCER permits is doubled, the decrease in the investment probability for wind power is large. We carry out sensitivity tests for different parameter values, and find that investment behavior changes significantly with differing interest rates, the wind energy premium and volatility.