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.     

The electricity generation adequacy problem: Assessing dynamic effects of capacity remuneration mechanisms

Following liberalization reforms, the ability of power markets to provide satisfactory incentives for capacity investments has become a major concern. In particular, current energy markets can exhibit a phenomenon of investment cycles, which generate phases of under and over-capacity, and hence additional costs and risks for generation adequacy. To cope with these issues, new mechanisms, called capacity remuneration mechanisms (CRM), have been (or will be) implemented. This paper assesses the dynamic effects of two CRMs, the capacity market and the strategic reserve mechanism, and studies to what extent they can reduce the investment cycles. Generation costs and shortage costs of both mechanisms are also compared to conclude on their effectivity and economic efficiency. A simulation model, based on system dynamics, is developed to study the functioning of both CRMs and the related investment decisions. The results highlight the benefits of deploying CRMs to solve the adequacy issue: shortages are strongly reduced compared to an energy-only market. Besides, the capacity market appears to be more beneficial, since it experiences fewer shortages and generation costs are lower. These comparisons can be used by policy makers (in particular in Europe, where these two CRMs are mainly debated) to determine which CRM to adopt.     

Generation capacity adequacy in interdependent electricity markets

This paper deals with the practical problems related to long-term security of supply in regional electricity markets with transmission constraints. Differences between regulatory policies and market designs in terms of generation adequacy policies may distort the normal functioning of the neighboring markets, as well as the reliability of supply. We test the effect of heterogeneous regulatory design between two interdependent markets: energy-only market, price-capped market without capacity mechanisms and price-capped markets with forward capacity contracts obligation. We rely on a long-term market simulation model in system dynamics that characterizes expansion decision in a competitive regime. The results show that differences in market designs affect both price and reliability of supply in the two markets. We examine both the short and long terms effect, and how free-riding may occur where capacity adequacy policies are adopted in one market but not the other. The main finding is that the lack of harmonization between local markets in policies to ensure capacity adequacy may lead to undesirable side effects.     

Demand response modeling considering Interruptible/Curtailable loads and capacity market programs

Recently, a massive focus has been made on demand response (DR) programs, aimed to electricity price reduction, transmission lines congestion resolving, security enhancement and improvement of market liquidity. Basically, demand response programs are divided into two main categories namely, incentive-based programs and time-based programs. The focus of this paper is on Interruptible/Curtailable service (I/C) and capacity market programs (CAP), which are incentive-based demand response programs including penalties for customers in case of no responding to load reduction. First, by using the concept of price elasticity of demand and customer benefit function, economic model of above mentioned programs is developed. The proposed model helps the independent system operator (ISO) to identify and employ relevant DR program which both improves the characteristics of the load curve and also be welcome by customers. To evaluate the performance of the model, simulation study has been conducted using the load curve of the peak day of the Iranian power system grid in 2007. In the numerical study section, the impact of these programs on load shape and load level, and benefit of customers as well as reduction of energy consumption are shown. In addition, by using strategy success indices the results of simulation studies for different scenarios are analyzed and investigated for determination of the scenarios priority.     

Investment incentives in the Korean electricity market

This paper develops a model-based analysis of the effects of various capacity incentive systems on new investment in the Korean electricity market. The restructuring process in Korea allocated power generation to six firms, competing within a wholesale market, albeit strictly on a cost basis. Because of this cost-based pool, capacity payments were also introduced to encourage new investment. However, it is an open question whether the current fixed capacity payment scheme is enough to secure resource adequacy, and consideration is being given to alternative mechanisms such as the use of LOLP. Using a detailed market simulation model, based on system dynamics, we compare these approaches in terms of how they may influence the investors’ decisions and thereby determine the system reserve margin. The simulation results suggest that there may be serious problems in staying with the current fixed capacity payments in order to achieve resource adequacy. In contrast, an LOLP-based capacity mechanism may, in the longer term, increase the reserve margin compared with a fixed capacity payment. More generally, this paper indicates how crucial the effective modeling of the investment behavior of the independent power producers is for adequate policy support, even if they only constitute a fringe in a substantially centrally influenced market.     

A real options model for renewable energy investment with application to solar photovoltaic power generation in China

This paper proposes a real options model for evaluating renewable energy investment by considering uncertain factors such as CO₂ price, non-renewable energy cost, investment cost and market price of electricity. A phase-out mechanism is built into the model to reflect the long-term changes of subsidy policy. We apply the proposed model to empirically evaluate the investment value and optimal timing for solar photovoltaic power generation in China. Our empirical results show that the current investment environment in China may not be able to attract immediate investment, while the development of carbon market helps advance the optimal investment time. A sensitivity analysis is conducted to investigate the dynamics of investment value and optimal timing under the changes of unit generating capacity, subsidy level, market price of electricity, CO₂ price and investment cost. It is found that the high investment cost and the volatility of electricity and CO₂ prices, are not conducive to attract immediate investment. Instead, increasing the level of subsidy, promoting technological progress and maintaining the stability of market are useful to stimulate investment.     

Efficient pricing and investment in electricity markets with intermittent resources

Facing growing technological and environmental challenges, the electricity industry needs effective pricing mechanism to promote efficient risk management and investment decisions. In a restructured electricity market with competitive wholesale prices and traditionally regulated retail rates, however, there are technical and institutional barriers that prevent dynamic pricing with price responsive demand. In regions with limited energy storage capacity, intermittent renewable resources present special challenges. This could adversely affect the effectiveness of public policies causing inefficient investments in energy technologies. In this paper, we present an updated economic model of pricing and investment in restructured electricity market and use the model in a simulation study for an initial assessment of renewable energy strategy and alternative pricing mechanisms. A key objective of the study is to shed light on the policy issues so that effective decisions can be made to improve efficiency.     

Policy changes and the dynamics of capacity expansion in the Swiss electricity market

Capacity of supply is a crucial matter in electricity markets as it directly influences reliability of supply, price volatility and blackout risk. In this paper, we analyse the dynamics of capacity expansion in the Swiss electricity market and the impact of different policies such as nuclear phaseout and management of electricity exchanges – imports and exports – policies. This article develops the conceptualization model presented in [Ochoa, P., 2007b. Policy changes in the Swiss electricity market: a system dynamics analysis of likely market responses. Socio-Economic Planning Sciences 41 (4):336–349.]. We build a system dynamics model based on the dynamics of capacity expansion explained in the latter paper and present and analyse different scenarios. We conclude that international electricity exchanges are important for the Swiss market as they help to lower costs and to increase the income of the utility companies; however, we illustrate the need for explicit policies for managing imports and exports of electricity to avoid import dependence from neighbouring countries.     

An improved mechanism for capacity payment based on system dynamics modeling for investment planning in competitive electricity environment

Many countries have experienced restructuring in their electric utilities. This restructuring has presented the power industries with new challenges, the most important of which is long-term investment planning under uncertain conditions. This paper presents an improved mechanism for capacity payment. The mechanism has been investigated based on system dynamic modeling. In our proposed mechanism, generators will recover a part of their investment through capacity payment. While the payment for any plant remains constant during the operation period, it depends on the investment needed to build it. The main factors affecting long-term planning have been considered in our model. The approach can be used to investigate the effects of fixed as well as variable capacity payment in market investment. We used the probability density function of load as a new concept to calculate average market price. Delays in unit constructions, estimation of demand, and market capacity growth during construction periods have been included in the proposed algorithm as parameters, which affect the regulator's decision for changing capacity payment. The model can be used by regulators to investigate strategies that may affect the fluctuations in the market.     

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.     

Capacity choices in liberalised electricity markets

This paper addresses the issue of investment in electricity generation in the context of a liberalised market. We use the main results derived from a theoretical model where firms invest strategically to simulate the Spanish electricity system with real-world data. Our results indicate that, under reasonable parameter constellations regarding the number of agents, the level of capacity resulting from private decisions falls well short of the social optimum. Last, we show that two regulatory mechanisms that have been used to generate additional incentives for private agents to install capacity (capacity payment and price-adder) are ineffective and/or prohibitively costly.     

Contract market power and its impact on the efficiency of the electricity sector

This paper analyzes the pro-competitive effects of financial long-term contracts in oligopolistic electricity markets. This is done in a model that incorporates the main features of the industry: non-storable production, time-varying price-elastic demand, and sequential investment and production decisions. The paper considers contracts for difference that have as reference price the average spot price. Assuming that the spot market coordinator sets competitive prices, the paper shows that installed capacity increases with the quantity of energy contracted, reaching the welfare-maximizing capacity when energy contracted equals this same level. Next, the paper studies the case where the quantity of energy contracted is endogenous and contracts are traded before capacity decisions are taken. Regarding purchasers of contracts, two polar cases are considered: either they are price-taker speculators or they are an aggregation of consumers that auctions a long (buy) contract for a given energy quantity. In the former case the strike price equals the reference price, i.e., arbitrage is perfect, and the quantity of energy contracted falls short of the efficient level. In turn, in the latter case, the strike price equals the average efficient spot price. Moreover, an aggregation of all consumers would choose to auction the social optimum quantity.     

Investment in wind power and pumped storage in a real options model

Promoting renewable energy has been a key ingredient in energy policy seeking to de-carbonize the energy mix and will continue to do so in the future given the European Union's high ambitions to further curb carbon emissions. A wide range of instruments has been suggested and implemented in various countries of the EU. A prominent policy promoting investment in renewable technologies is the use of feed-in tariffs, which has worked well at large scale in, e.g. Germany, but which has only been implemented in a very limited way in countries such as the UK.Being subject to environmental uncertainties, however, renewables cannot be seen in isolation: while renewables-based technologies such as wind and solar energy, for example, suffer from uncertain loads depending on environmental conditions, hydropower allows for the storage of water for release at peak prices, which can be treated as a premium (partially) offsetting higher upfront investment costs. In addition, electricity prices will respond to changes in electric capacity in the market, which is often neglected in standard investment models of the electricity sector.This paper contributes to the existing literature in two ways: it provides a review of a renewables-based technology in a specific policy context and provides additional insight by employing a real options approach to investigate the specific characteristics of renewables and their associated uncertainties in a stylized setting taking explicitly into account market effects of investment decisions. The prices of the model are determined endogenously by the supply of electricity in the market and by exogenous electricity price uncertainty. The inclusion of market effects allows us to capture the full impact of public incentives for companies to invest into wind power and hydro pumped storage installations.     

Optimizing hydrogen production capacity and day ahead market bidding for a wind farm in Texas

Producing green hydrogen from wind energy is one potential method to mitigate curtailment. This study develops a general approach to examine the economic benefit of adding hydrogen production capacity through water electrolysis along with the fuel cell and storage facilities in a wind farm in north Texas. The study also investigates different day ahead market bidding strategies in the existence of these technologies. The results show that adding hydrogen capacity to the wind farm is profitable when hydrogen price is greater than $3.58/kg, and that the optimal day ahead market bidding strategy changes as hydrogen price changes. The results also suggest that both the addition of a fuel cell to reconvert stored hydrogen to electricity and the addition of a battery to smooth the electricity input to the electrolyzer are suboptimal for the system in the case of this study. The profit of a particular bidding scenario is most sensitive to the selling price of hydrogen, and then the input parameters of the electrolyzer. This study also provides policy implications by investigating the impact of different policy schemes on the optimal hydrogen production level.     

电力市场中热电联产机组两部制电价机制的研究

通过比较热电联产机组与常规火电机组的优势劣势,分析了国内外电力市场中热电联产机组的扶持政策和运营情况,提出了热电联产机组参与电力市场的两部制电价机制设计方法,给出了热电联产机组两部制电价中可用容量、可用小时数、容量电价、电量电价等参数的计算方法,形成了一套科学合理的价格形成机制,使其与常规火电机组可以参与同一电力市场竞价上网。     

Electricity market-clearing prices and investment incentives: The role of pricing rules

Pricing rules in wholesale electricity markets are usually classified around two major groups, namely linear (aka non-discriminatory) and non-linear (aka discriminatory). As well known, the major difference lies on the way non-convexities are considered in the computation of market prices.According to the classical marginal pricing theories, the resulting market prices are supposed to serve as the key signals around which capacity expansion revolves. Thus, the implementation of one or the other pricing rule can have a different effect on the investment incentives perceived by generation technologies, affecting the long-term efficiency of the whole market scheme.The objective of this paper is to assess to what extent long-term investment incentives can be affected by the pricing rule implemented. To do so, we propose a long-term capacity expansion model where investment decisions are taken based on the market remuneration. We use the model to determine the optimal mix in a real-size thermal system with high penetration of renewable energy sources (since its intermittency enhances the relevance of non-convexities), when alternatively considering the aforementioned pricing schemes.     

From nuclear phase-out to renewable energies in the Swiss electricity market

Liberalisation and the ever larger share of variable renewable energies (VRES), e.g. photovoltaic (PV) and wind energy, affect security of supply (SoS). We develop a system dynamics model to analyse the impact of VRES on the investment decision process and to understand how SoS is affected. We focus on the Swiss electricity market, which is currently undergoing a liberalisation process, and simultaneously faces the encouragement of VRES and a nuclear phase out. Our results show that nuclear production is replaced mainly by PV and imports; the country becomes a net importer. This evolution points to a problem of capacity adequacy. The resulting price rise, together with the subsidies needed to support VRES, lead to a rise in tariffs. In the presence of a high share of hydro, the de-rated margin may give a misleading picture of the capacity adequacy. We thus propose a new metric, the annual energy margin, which considers the energy available from all sources, while acknowledging that hydro-storage can function as a battery. This measure shows a much less reassuring picture of the country’s capacity adequacy.     

Fuel cost uncertainty,capacity investment and price in a competitive electricity market

This paper studies the effect of natural-gas fuel cost uncertainty on capacity investment and price in a competitive electricity market. Our model has a two-stage decision process. In the first stage, an independent power producer (IPP) builds its optimal capacity, conditional on its perceived uncertainties in fuel cost and electricity demand. In the second stage, equilibrium prices and quantities are determined by IPPs competing in a Cournot market. Under the empirically reasonable assumption that per MWh fuel costs are log-normally distributed, we find that a profit-maximizing IPP increases its capacity in response to rising fuel cost volatility. Consequently, the expected profit of the IPP and expected consumer surplus increase with volatility, rejecting the hypothesis that rising fuel cost uncertainty tends to adversely affect producers and consumers. Expected consumer surplus further increases if the IPP hedges the fuel cost risk. However, the IPP's optimal strategy is not to do so. The policy implication of these results is that the government should not intervene to reduce the price volatility of a well-functioning spot market for natural gas, chiefly because such intervention can have the unintended consequence of discouraging generation investment, raising electricity prices, and harming consumers.     

Endogenous price zones and investment incentives in electricity markets: An application of multilevel optimization with graph partitioning

In the course of the energy transition, load and supply centers are growing apart in electricity markets worldwide, rendering regional price signals even more important to provide adequate locational investment incentives. In this paper, we focus on electricity markets with zonal pricing from a long-run perspective, i.e., we include capacity investment decisions. For a fixed number of zones, we endogenously derive the optimal configuration of price zones and available transfer capacities. We build on the multilevel mixed-integer nonlinear model with graph partitioning on the first level developed in Grimm et al. (2019) and adapt it to be able to solve the model to global optimality even for large instances. By applying the model to the German electricity market, we find that a considerable share of the maximum possible welfare gains can already be achieved by implementing a few (two or three) optimally configured price zones with restrictive inter-zonal ATCs. Moreover, ATCs between zones are an important influencing factor for the achievable welfare gains and investment incentives. Finally, our results show that hypothetical nodal prices are not a good guidance to partition nodes into optimal zones.     

Cooperation mechanisms to achieve EU renewable targets

There are considerable benefits from cooperating among member states on meeting the 2020 renewable energy sources (RES) targets. Today countries are supporting investments in renewable energy by many different types of support schemes and with different levels of support. The EU has opened for cooperation mechanisms such as joint support schemes for promoting renewable energy to meet the 2020 targets. The potential coordination benefits, with more efficient localisation and composition of renewable investment, can be achieved by creating new areas/sub-segments of renewable technologies where support costs are shared and credits are transferred between countries.Countries that are not coordinating support for renewable energy might induce inefficient investment in new capacity that would have been more beneficial elsewhere and still have provided the same contribution to meeting the 2020 RES targets. Furthermore, countries might find themselves competing for investment in a market with limited capital available. In both cases, the cost-efficiency of the renewable support policies is reduced compared to a coordinated solution.Barriers for joint support such as network regulation regarding connection of new capacity to the electricity grid and cost sharing rules for electricity transmission expansion are examined and examples given. The influence of additional renewable capacity on domestic/regional power market prices can be a barrier. The market will be influenced by for example an expansion of the wind capacity resulting in lower prices, which will affect existing conventional producers. This development will be opposed by conventional producers, whereas consumers will support such a strategy.A major barrier is the timing of RES targets and the uncertainty regarding future targets. We illustrate the importance of different assumptions on future targets and the implied value of RES credits. The effect on the credit price for 2020 is presented in an exemplary case study of 200 MW wind capacity.