• A study of the dynamic effects of CRMs on generation investments is provided.
• Capacity market and strategic reserve mechanism are compared.
• Both CRMs reduce the cyclical tendencies prone to appear in energy-only market.
• The capacity market experiences fewer shortages and generation costs are lower.
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.
Power market reforms in recent decades and in particular development of competition on the generation side have changed the way investment decisions are made (Dyner and Larsen, 2001). In previous regulated systems, investment risks were passed through the tariffs to the consumers. Since only one player was involved, coordination in generation investments was not an issue. Now, investors perform their own development planning in reaction to complex and hardly predictable price signals, aiming to earn the highest profit. It makes coordination in investments more complex, which can lead to long-term inefficiencies.
Literature has shown that many market failures can disturb the achievement of an optimal level of investment under the so called “energy-only” market design (Hobbs et al., 2001; De Vries, 2004; Bidwell and Henney, 2004; Joskow, 2007). Moreover, it has shown that generation adequacy is not only about investing in the optimal amount of capacity but also about doing it at the right time.1 Indeed, the dynamic aspects of generation investments also matter regarding the adequacy issue.2 In particular, the risk of cyclical tendencies in generation investments, known as boom and bust cycles, has been highlighted (Ford, 1999, 2001, 2002; Green, 2006; Arango and Larsen, 2011). These tendencies are materialized by phases of undercapacity and overcapacity. Such phases are prejudicial to society since more shortages than the optimal level are required during undercapacity phases and more generation capacity than the optimal amount is built during overcapacity phases. Undercapacity phases are explained by the tendency of investors to delay their investments. This is mostly due to uncertainties, impossibility to predict futures prices in a perfect way and risk aversion (De Vries, 2004). Investors tend to wait for clearer signals of profitability to be sure their plants will be profitable (Dixit and Pindyck, 1994). Long lead time, capital intensiveness and irreversibility of investments also intensify these effects. Conversely, once investments seem to be profitable enough, players are prone to overinvest. A herd behavior or an underestimation about competitors' decisions can explain this (Green, 2006). Such underestimation can be intentional, investors being skeptical about completion of competitors announced power plants, or unintentional, investors having limited information about competitors' decisions (Ford, 2001).
Therefore, to provide optimal investment signals and solve these adequacy issues, new mechanisms called capacity remuneration mechanisms (CRM) have been (or are going to be) implemented. The debates and discussions currently taking place in Europe on this topic mostly focus on two mechanisms, the capacity market and the strategic reserve mechanism.3 These two mechanisms are studied in this paper. In the capacity market (also known as capacity requirements), an obligation of installed capacity is computed several years in advance, equal to the peak demand forecast together with a capacity margin. This obligation can be proportionally shared between suppliers in the case of a decentralized capacity market or borne by a single buyer (for instance the TSO4 ) in the case of a centralized capacity market. A new market for capacity is then created, juxtaposed to the commodity energy market, to exchange capacity credits and reach this capacity obligation. This design has been selected in France or in Great-Britain. In the strategic reserve mechanism, the TSO sets, several years or months in advance, the amount of required strategic reserves based on the difference between estimated peak demand (plus a capacity margin) and what the market would otherwise provide without the mechanism. These reserves are provided through a competitive tender and are deployed only as a last resort to avoid shortages. It has been implemented in Sweden and in Finland and recently in Belgium. Germany is also considering the introduction of this mechanism (McGraw Hill Financial, 2015). Besides, the European Commission (2013) recommends the implementation of a strategic reserve mechanism which it assesses as less distortionary for the energy market and easier to implement.
One of the key questions in the current literature involves assessing the performances of these CRMs and comparing them to select the best one to implement. For instance, in Europe, the implementation of these mechanisms has to be validated by the European Commission based on the comparison of several economic criteria. Several authors have thus compared qualitatively the different CRMs with regard to a selection of economic criteria (e.g. provision of adequate incentives, feasibility, risks of market power abuse), mainly from a static point of view (e.g. Finon and Pignon (2006)). Moreover, due to the importance of the investment cycles as described in the literature, the performances of these CRMs also have to be assessed dynamically, in particular to study to what extent they can reduce these prejudicial cyclical tendencies. To this end, simulation models are needed. Indeed, to gain an understanding of the dynamics of the industry, Gary and Larsen (2000) showed that inclusions of information feedback loops, instead of equilibrium assumptions, are fundamental. Therefore, equilibrium models cannot be used anymore to understand and model the cyclical tendencies (of course, the same can be said about optimization models, e.g. minimizing costs). Among the different simulations models, Systems Dynamics (SD) modeling, a methodology developed by Forrester (1961), is the main model used in the current literature to model these feedback loops and to study dynamic aspects of investments. SD enables to study inter-relationships among the different components, understand feedback mechanisms and then assess the dynamic responses. Thus, using this methodology, cycle behaviors can be analyzed, as well as the influence of CRM on such cycles. For instance, Olsina et al. (2006), Syed Jalal and Bodger (2010), De Vries (2004), Kadoya et al. (2005) and Hani et al. (2006) have applied SD to study the investment dynamics in electricity markets and to highlight the cyclical behavior. A more extensive review of SD models in generation capacity simulation can be found in Teufel et al. (2013).
Literature has also used this method to study and compare the dynamic properties of CRMs in order to select the most effective one to implement. For instance, Assili et al. (2008) and Park et al. (2007) study how an improved variable capacity payment mechanism can reduce investment cycles. De Vries and Heijnen (2008) compare capacity payments, operating reserves pricing and capacity markets under uncertainty of the future growth load. They show that all these mechanisms perform better than a competitive energy-only market, capacity obligations having the strongest stabilizing effect, both with respect to investment and prices. Hobbs et al. (2007) assess the capability of the capacity market in the PJM system to reduce investment cycles. They show that a downward sloping demand curve on the capacity market reduces fluctuations in installed capacity, compared to a vertical curve. Hasani and Hosseini (2011) compare the capacity payment mechanism and the capacity market through nine technical and economic indicators (in particular regarding shortages, electricity prices and revenues of peak technology). Hasani and Hosseini (2013) develop a SD model to compare different designs of capacity payment in the Iranian power market, in particular assessing the reserve margin and the generation expansion costs. They find that a capacity payment mechanism with different payments for each region according to the regions' reliability indices shows lower capacity expansion costs and enables to avoid shortages. Finally, Cepeda and Finon (2011) study the problems related to long-term security of supply in regional electricity markets when different CRMs are implemented. They find that the lack of harmonization between local markets in CRMs may lead to undesirable side effects.
However, the current literature can be improved on two points.First, the strategic reserve mechanism, one of the main CRMs implemented and discussed in Europe, is rarely studied from a dynamic point of view. Thus, policymakers cannot compare this mechanism with other CRMs to select the best one to implement. Moreover, in the studies mentioned above, comparisons are often based on an adequacy criterion (i.e. to what extent the CRM can reduce shortages). However, the efficiency of the mechanism, i.e. the costs to build and operate power plants to reduce shortages, is often disregarded. Yet, efficiency is one of the main criteria to consider from an economic point of view, in particular when maximizing the social welfare: CRMs have to reduce shortages but not at any cost for society. Policymakers should decide which CRM to implement regarding not only the effectiveness criterion (i.e. the adequacy) but also the efficiency one (i.e. the investment and generation costs).
These two missing points are studied in this paper. Its purpose is to assess the dynamic effects of the capacity market and the strategic reserve mechanism, two of the main CRMs considered in Europe, and to compare them with regard to the effectiveness and efficiency criteria. The most suitable and convenient method to study these dynamic aspects of investments is SD modeling, which is used in this paper. To the knowledge of the authors, the results of this study should not be dependent on the original modeling choice, as long as the model is a SD simulation. As a consequence, the model chosen in this paper is based on Hobbs (2005) and Hobbs et al. (2007) as it is well exposed and explained in the original papers, and then easily tractable. This original model, where only the capacity market is studied for the PJM system,5 is expanded to consider a strategic reserve mechanism and an energy-only market. Moreover, in order to be able to compute the generation costs accurately, a bidding behavior based on avoidable costs and endogenous shutdown decisions are added. The model used in this paper simulates investment decisions in a liberalized market regime under uncertainty on the load growth. Three different market designs are studied: the energy-only market (as a reference case), the capacity market and the strategic reserve mechanism. Then, these market designs are compared based on social welfare using Monte-Carlo simulations for different growth loads. This social welfare is evaluated thanks to total generation costs and shortage costs.
This paper is organized as follows: Section 2 presents the model used in this paper to study players' decisions under the energy-only market, the capacity market and the strategic reserve mechanism. Results of these simulations and comparisons of market performances are outlined in Section 3. Finally, Section 4 concludes the paper.