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.     

Integrating Real Options Analysis with long-term electricity market models

In liberalized electricity markets, the investment postponement option is deemed decisive for understanding the addition of new generating capacity. Basically, it refers to the possibility for investors to postpone projects for a period while waiting for the arrival of new and better information about the market evolution. When such development involves major uncertainties, the generation business becomes riskier, and the investors' “wait-and-see” behavior might limit the timely addition of new power plants. In that sense, the literature provides solid empirical evidence about the occurrence of construction cycles in the deregulated electricity industry. However, the strategic flexibility inherent to the option to defer new power plants has not yet been rigorously incorporated to investment signals in existing market models. Therefore, this paper proposes a novel methodology to assess the long-term development of liberalized power markets based on a more realistic approach for valuing generation investments. The work is based on a stochastic dynamic market model, built upon System Dynamics simulation approach. The decision-making framework considers that the addition of new capacity is driven by the economic value of the strategic flexibility associated with deferring investments under uncertainties. Thus, the value of the postponement option is quantified in monetary terms through Real Options Analysis. Simulations confirm the cyclical behavior of the energy-only market in the long run, as suggested by the empirical evidence found in the literature. In addition, sensitivity analysis regarding some relevant exogenous variables depicts an even more fluctuating evolution of the capacity due to the combination of strong demand growth rates with large volatilities. Finally, the model validity is assessed through a formal procedure according to the scope of System Dynamics modeling approach.     

A decision support tool for the analysis of pricing,investment and regulatory processes in a decentralized electricity market

After the liberalization of the electricity generation industry, capacity expansion decisions are made by multiple self-oriented power companies. Unlike the centralized environment, decision-making of market participants is now guided by price signal feedbacks and by an imperfect foresight of the future market conditions (and competitor actions) that they will face. In such an environment, decision makers need to better understand long-term dynamics of the supply and demand sides of the power market. In this study, a system dynamics model is developed, to better understand and analyze the decentralized and competitive electricity market dynamics in the long run. The developed simulation model oversees a 20-year planning horizon; it includes a demand module, a capacity expansion module, a power generation module, an accounting and finance module, various competitors, a regulatory body and a bidding mechanism. Many features, singularities and tools of decentralized markets, such as; capacity withholding, enforced divestment, long-term contracts, price-elastic demands, incentives/disincentives, are also incorporated into the model. Public regulators and power companies are potential users of the model, for learning and decision support in policy design and strategic planning. Results of scenario analysis are presented to illustrate potential use of the model.     

Measuring the competitiveness benefits of a transmission investment policy: The case of the Alberta electricity market

Transmission expansions can increase the extent of competition faced by wholesale electricity suppliers with the ability to exercise unilateral market power. This can cause them to submit offer curves closer to their marginal cost curves, which sets market-clearing prices closer to competitive benchmark price levels. These lower wholesale market-clearing prices are the competitiveness benefit consumers realize from the transmission expansion. This paper quantifies empirically the competitiveness benefits of a transmission expansion policy that causes strategic suppliers to expect no transmission congestion. Using hourly generation-unit level offer, output, market-clearing price and congestion data from the Alberta wholesale electricity market from January 1, 2009 to July 31, 2013, an upper and lower bound on the hourly consumer competitiveness benefits of this transmission policy is computed. Both of these competitiveness benefits measures are economically significant, which argues for including them in transmission planning processes for wholesale electricity markets to ensure that all transmission expansions with positive net benefits to electricity consumers are undertaken.     

Quantifying multiscale inefficiency in electricity markets

One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies.     

Cross-border effects in interconnected electricity markets - an analysis of the Swiss electricity prices

Electricity markets in Europe become increasingly interconnected due to new grid connections and market coupling regulations. This paper examines the interdependencies between the Swiss electricity market and those of neighbouring countries. The Swiss market serves as a good example for a smaller electricity market which is increasingly affected by developments in the large neighbouring countries. To study these cross-border effects, especially those on Swiss electricity prices, we apply two different methodologies, an econometric and a Nash-Cournot equilibrium model.The analyses show that the Swiss electricity price correlates strongly with the German electricity price in the summer, but tends to follow the French electricity price in the winter. Another finding is that gas prices and the electricity load of neighbouring countries have a significant influence on prices. In particular, the load of France and Italy is driving up Swiss prices in the winter, while the German electricity demand and renewable energy generation have a larger influence on Swiss prices in the summer.     

INVESTMENT PLANNING FOR ELECTRICITY GENERATION EXPANSION

Some of the essential features of electricity generation expansion planning are discussed here. The emphasis in this paper is on the development of a methodology to analyse electricity planning problems when the variables are deterministic and stochastic in nature. Our analysis with a test problem indicates that if the stochastic nature of supply and demand can be specified, a more cost effective electricity generation expansion plan can be prepared. The proposed methodology is expected to be useful for energy planners in modelling and implementing investment plans for energy supply. © 1997 by John Wiley & Sons, Ltd.     

Expectations and forward risk premium in the Spanish deregulated power market

Deregulation in energy markets has entailed important changes in the way agents conduct business. Price risk arises as a result of fluctuations in the future price of electricity and agents assume long or short positions in the forward and spot markets to hedge their exposure to price risk. The presence of forward risk premium in prices is evidence of the fact that agents act in the market according to risk considerations. This work aims to analyse the information content of the difference between the forward and spot prices (the so-called forward premium) regarding the agents’ decisions. We find that the sign and magnitude of the ex post forward premium depend on the unexpected variation in demand and on the unexpected variation in the hydroelectric capacity, and that both the ex post and the ex ante forward premia are negatively related to the variance of spot price, as Bessembinder and Lemmon (2002) predict. We provide additional insights about relevant aspects of spot price pricing in the Spanish electricity market such as the positive relation between spot prices and CO₂ emission allowance prices or the impact on spot prices of the set of market matching rules introduced in March 2006.     

Restructuring the Russian electricity sector: Re-creating California?

The Russian Federation has begun restructuring its electricity sector, following the standard restructuring model of complete vertical separation of generation from transmission, with the aim of creating competition in regional generation markets. This paper examines the structure of the six principal regional generation markets that are in their early stages of development and argues that they are likely to be characterized by high levels of market power on the part of individual privatized generation companies, especially during the peak winter demand season. These levels—considerably higher than those that caused competitive problems in California—seem to create a serious risk of price spikes in deregulated wholesale electricity markets, and thus of significant price increases to consumers of electricity.     

Financial optimization in the Turkish electricity market: Markowitz's mean-variance approach

Electricity constitutes the input into many products that produced by industry and used by people. Hence, it can be considered as a product or service that has vital importance in human life and economy. Since it has such special properties of instantaneous production and consumption obligation and unfeasible storage, electricity market is not like other markets. In a competitive electricity market, generation company faces price risks and delivery risks. So that risk management is an important part of a generation company and can deeply effect companies’ profitability. This paper focuses on electricity generation asset allocation between bilateral contracts, such as forward contracts, and daily spot market, considering constraints of generating units and spot price risks. The problem is to find the optimal portfolio based on known electricity generation total costs, bilateral contract prices, it employed Turkish historical balanced market hourly system marginal and day-ahead hourly market prices between of 2006 and 2011. There are limited studies about portfolio optimization in electricity markets in literature and this paper should be considered frontier study taking spot market's hourly prices separately as risky assets. Markowitz mean-variance optimization which is claimed to be the beginning of modern portfolio theory in financial sector is used to demonstrate this approach. Mean-variance optimization has been successfully applied to all cases that modeled for electricity market. Some suggestions for future work are also listed in this paper.     

A strategic review of electricity systems models

Electricity systems models are software tools used to manage electricity demand and the electricity systems, to trade electricity and for generation expansion planning purposes. Various portfolios and scenarios are modelled in order to compare the effects of decision making in policy and on business development plans in electricity systems so as to best advise governments and industry on the least cost economic and environmental approach to electricity supply, while maintaining a secure supply of sufficient quality electricity. The modelling techniques developed to study vertically integrated state monopolies are now applied in liberalised markets where the issues and constraints are more complex. This paper reviews the changing role of electricity systems modelling in a strategic manner, focussing on the modelling response to key developments, the move away from monopoly towards liberalised market regimes and the increasing complexity brought about by policy targets for renewable energy and emissions. The paper provides an overview of electricity systems modelling techniques, discusses a number of key proprietary electricity systems models used in the USA and Europe and provides an information resource to the electricity analyst not currently readily available in the literature on the choice of model to investigate different aspects of the electricity system.     

Statistical analysis of negative prices in European balancing markets

The presence of renewable power generation technologies increases the need for system flexibility due to their variable nature. The increasing share of variable renewables in European power systems create a downward adequacy problem, which deals with the ability of power systems to cope with periods of excess generation. The occurrence of negative prices on Central Western European electricity markets confirms the relevance of this issue, which is referred to as “incompressibility of power systems” and is assessed as a barrier for further renewable power integration. The objective of this article is to identify the main drivers of negative price periods in European balancing markets, by means of both an empirical and regression analysis. Results confirm a positive relation with the scheduled generation of renewables and inflexible base load, as well as a negative relation with the scheduled system load. Furthermore, the occurrence of negative prices is related to the positive and negative forecast error of renewable generation and demand, respectively. It is concluded that negative balancing market prices provide a market signal for investments in flexibility sources such as flexible generation, demand response, electricity storage, and interconnector capacity.     

全国碳市场背景下电力行业碳价传导机制研究

电力行业作为典型的能源密集型行业,是全世界各地碳市场的重点管控对象。本文对国内外电力市场、碳市场及碳价传导的问题进行了研究,发现欧洲、美国的电力市场更趋近于买方市场,碳价对终端电价的影响较小。而由于中国电力体制的特殊性,电价由政府主管部门进行管控,因而在政府不通过行政手段调节碳成本传递机制的情况下,碳成本将无法向发电企业下游传导,使得发电企业暴露在碳成本波动的风险下。同时,在对碳成本传导机制研究的基础上给出了具体建议。     

Survey of Western U.S. electric utility resource plans

We review long-term electric utility plans representing ~90% of generation within the Western U.S. and Canadian provinces. We address what utility planners assume about future growth of electricity demand and supply; what types of risk they consider in their long-term resource planning; and the consistency in which they report resource planning-related data. The region is anticipated to grow by 2% annually by 2020 – before Demand Side Management. About two-thirds of the utilities that provided an annual energy forecast also reported energy efficiency savings projections; in aggregate, they anticipate an average 6.4% reduction in energy and 8.6% reduction in peak demand by 2020. New natural gas-fired and renewable generation will replace retiring coal plants. Although some utilities anticipate new coal-fired plants, most are planning for steady growth in renewable generation over the next two decades. Most planned solar capacity will come online before 2020, with most wind expansion after 2020. Fuel mix is expected to remain ~55% of total generation. Planners consider a wide range of risks but focus on future demand, fuel prices, and the possibility of GHG regulations. Data collection and reporting inconsistencies within and across electric utility resource plans lead to recommendations on policies to address this issue.     

Modeling long-term dynamics of electricity markets

In the last decade, many countries have restructured their electricity industries by introducing competition in their power generation sectors. Although some restructuring has been regarded as successful, the short experience accumulated with liberalized power markets does not allow making any founded assertion about their long-term behavior. Long-term prices and long-term supply reliability are now center of interest. This concerns firms considering investments in generation capacity and regulatory authorities interested in assuring the long-term supply adequacy and the stability of power markets. In order to gain significant insight into the long-term behavior of liberalized power markets, in this paper, a simulation model based on system dynamics is proposed and the underlying mathematical formulations extensively discussed. Unlike classical market models based on the assumption that market outcomes replicate the results of a centrally made optimization, the approach presented here focuses on replicating the system structure of power markets and the logic of relationships among system components in order to derive its dynamical response. The simulations suggest that there might be serious problems to adjust early enough the generation capacity necessary to maintain stable reserve margins, and consequently, stable long-term price levels. Because of feedback loops embedded in the structure of power markets and the existence of some time lags, the long-term market development might exhibit a quite volatile behavior. By varying some exogenous inputs, a sensitivity analysis is carried out to assess the influence of these factors on the long-run market dynamics.     

Price formation in electricity forward markets and the relevance of systematic forecast errors

Since the liberalisation of the European electricity sector, forward and futures contracts have gained significant interest of market participants due to risk management reasons. For pricing of these contracts an important fact concerns the non-storability of electricity. In this case, according to economic theory, forward prices are related to the expected spot prices which are built on fundamental market expectations. In the following article the crucial impact parameters of forward electricity prices and the relationship between forward and future spot prices will be assessed by an empirical analysis of electricity prices at the European Energy Exchange and the Nord Pool Power Exchange. In fact, price formation in the considered markets is influenced by historic spot market prices yielding a biased forecasting power of long-term contracts. Although market and risk assessment measures of market participants and supply and demand shocks can partly explain the futures-spot bias inefficiencies in the analysed forward markets cannot be ruled out.     

How competitive are EU electricity markets? An assessment of ETS Phase II

This paper studies the interactions between electricity and carbon allowance prices in the year-ahead energy markets of France, Germany, United Kingdom and the Nordic countries, during Phase II of the EU ETS. VAR and Granger-causality methods are used to analyze causal interfaces, whereas the volatility of electricity prices is studied with basic and asymmetric AR-GARCH models. Among the main results, the marginal rate at which carbon prices feed into electricity prices is shown to be ca. 135% in the EEX and Nord Pool markets, where electricity and carbon prices display bidirectional causality, and 109% in the UK. Therefore, generators in these markets internalized the cost of freely allotted emission allowances into their electricity prices considerably more than the proportionate increase in costs justified by effective carbon intensity. Moreover, electricity prices in France are found to Granger-cause the carbon price. This study also shows how European electricity prices are deeply linked to coal prices among other factors, both in terms of levels and volatility, regardless of the underlying fuel mix, and that coal was marginally more profitable than gas for electricity generation. EU policies aimed at increasing the carbon price are likely to be crucial in limiting the externalities involved in the transition to a low-carbon system.     

Option value of electricity demand response

As electricity markets deregulate and energy tariffs increasingly expose customers to commodity price volatility, it is difficult for energy consumers to assess the economic value of investments in technologies that manage electricity demand in response to changing energy prices. The key uncertainties in evaluating the economics of demand–response technologies are the level and volatility of future wholesale energy prices. In this paper, we demonstrate that financial engineering methodologies originally developed for pricing equity and commodity derivatives (e.g., futures, swaps, options) can be used to estimate the value of demand-response technologies. We adapt models used to value energy options and assets to value three common demand–response strategies: load curtailment, load shifting or displacement, and short-term fuel substitution—specifically, distributed generation. These option models represent an improvement to traditional discounted cash flow methods for assessing the relative merits of demand-side technology investments in restructured electricity markets.     

Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae

We consider the problem of modelling and forecasting the distribution of a vector of prices from interconnected electricity markets using a flexible class of drawable vine copula models, where we allow the dependence parameters of the constituting bivariate copulae to be time-varying. We undertake in-sample and out-of-sample tests using daily electricity prices, and evidence that our model provides accurate forecasts of the underlying distribution and outperforms a set of competing models in their abilities to forecast one-day-ahead conditional quantiles of a portfolio of electricity prices. Our study is conducted in the Australian National Electricity Market (NEM), which is the most efficient power auction in the world. Electricity prices exhibit highly stylised features such as extreme price spikes, price dependency between regional markets, correlation asymmetry and non-linear dependency. The developed approach can be used as a risk management tool in the electricity retail industry, which plays an integral role in the apparatus of modern energy markets. Electricity retailers are responsible for the efficient distribution of electricity, while being exposed to market risk with extreme magnitudes.     

An agent-based analysis of the German electricity market with transmission capacity constraints

While some agent-based models have been developed for analyzing the German electricity market, there has been little research done on the emerging issue of intra-German congestion and its effects on the bidding behavior of generator agents. Yet, studies of other markets have shown that transmission grid constraints considerably affect strategic behavior in electricity markets. In this paper, the implications of transmission constraints on power markets are analyzed for the case of Germany. Market splitting is applied in the case of congestion in the grid. For this purpose, the agent-based modeling of electricity systems (AMES) market package developed by Sun and Tesfatsion is modified to fit the German context, including a detailed representation of the German high-voltage grid and its interconnections. Implications of transmission constraints on prices and social welfare are analyzed for scenarios that include strategic behavior of market participants and high wind power generation. It can be shown that strategic behavior and transmission constraints are inter-related and may pose severe problems in the future German electricity market.