Large-scale solutions

For more than a century, we have accepted the premise that once electricity is produced, it cannot be stored. This lack of storage causes extreme electricity price volatility (compared with other commodities) and hourly fluctuations in wholesale market prices, and has prompted specialized real-time markets that provide price fluctuations in 5- or 10-min intervals. The hourly volatility reflects the widely disparate costs of production from different resources that lead to a steep supply curve in most markets; that steep supply curve, coupled with highly variable demand and an inelastic demand curve in today's markets, makes for high volatility.     

Investigating the need of nuclear power plants for sustainable energy in Iran

Over the decades, the consumption of all types of energy such as electricity increased rapidly in Iran. Therefore, the government decided to redevelop its nuclear program to meet the rising electricity demand and decrease consumption of fossil fuels. In this paper, the effect of this policy in four major aspects of energy sustainability in the country, including energy price, environmental issues, energy demand and energy security have been verified. To investigate the relative cost of electricity generated in each alternative generator, the simple levelized electricity cost was selected as a method. The results show that electricity cost in fossil fuel power plants presumably will be cheaper than nuclear. Although the usage of nuclear reactor to generate power is capable of decreasing hazardous emissions into the environment, there are many other effective policies and technologies that can be implemented. Energy demand growth in the country is very high; neither nuclear nor fossil fuel cannot currently cope with the growth. So, the only solution is rationalizing energy demand by price amendment and encouraging energy efficiency. The major threats of energy security in Iran are high energy consumption growth and economic dependency on crude oil export. Though nuclear energy including its fuel cycle is Iran's assured right, constructing more nuclear power plants will not resolve the energy sustainability problems. In fact, it may be the catalyst for deterioration since it will divert capital and other finite resources from top priority and economic projects such as energy efficiency, high technology development and energy resources management.     

How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models

Based on a dynamic model for the high/low range of electricity prices, this article analyses the effects of Germany's green energy policy on the volatility of the electricity market. Using European Energy Exchange data from 2000 to 2015, we find rather high volatility in the years 2000–2009 but also that the weekly price range has significantly declined in the period following the year 2009. This period is characterised by active regulation under the Energy Industry Law (EnWG), the EU Emissions Trading Directive (ETD) and the Renewable Energy Law (EEG). In contrast to the preceding period, price jumps are smaller and less frequent (especially for day-time hours), implying that current policy measures are effective in promoting renewable energies while simultaneously upholding electricity market stability. This is because the regulations strive towards a more and more flexible and market-oriented structure which allows better integration of renewable energies and supports an efficient alignment of renewable electricity supply with demand.     

Nuclear power in open energy markets: A case study of Turkey

For many decades, like many developed countries, Turkey has controlled her electricity sector as a state-owned monopoly. However, faced with rapid electricity demand growth, Turkey started to consider nuclear option. The present paper aims at evaluating both the present status of nuclear power in general and its implications for Turkish energy market in particular. After examining existing nuclear power technology and providing a brief overview of nuclear power economics; it focuses on the repercussions of nuclear power for Turkish energy market. The paper concludes that, in the short run, it may be considered to keep nuclear power within Turkish energy mix because it is an important carbon-free source of power that can potentially make a significant contribution to both Turkey's future electricity supply and efforts to strengthen Turkey's security of supply. However, in the long term, nuclear power should be retained in Turkey only if it has a lower cost than competing technologies.     

Price volatility in commodity markets with restricted participation

In commodity markets, price volatility may rise significantly if the product granularity increases. To gain insights into the underlying drivers, we analyze price volatility based on the example of German electricity markets. We develop a theoretical model to reproduce the price formation in the day-ahead and intraday auction which are sequential short-term electricity markets with 60-minute and 15-minute products. As cross-border trade is allowed in the day-ahead but not in the intraday auction, the model accounts for the impact of restricted market participation. The theoretical model is then transferred into an empirical analysis to first validate the modeling approach and second to comparatively assess the impact of increasing product granularity and restricted market participation. The empirical results indicate that the disproportional rise in quarter-hourly price volatility is mainly triggered by limited market participation and not only by the high volatility of renewable supply and demand. Since restricted market participation refers to a lack of market coupling, we derive a proxy for efficiency losses ranging from EUR 55 million to EUR 108 million that may be reduced if markets are coupled.     

A techno-economic analysis of tidal energy technology

The choice of which type of electrical power generation technology to adopt is driven by a number of factors including: cost of generated electricity; responsiveness of generating plant to demand; security of supply/resource availability; environmental impact; and execution risk. Within these, tidal energy is unique as a renewable technology since it has the capability of providing predictable, firm power contributing to security of supply. This predictability gives tidal energy additional value in a future electricity market. Especially one where stochastic renewable technologies contribute to a sizable component of the power supplied; and where reserve capacity is required to maintain supply during periods of non-availability. In the shorter term, in order for tidal energy to gain commercial acceptance, tidal technologies under development need to produce electricity at a competitive price. This paper examines the drivers influencing electricity pricing; current tidal energy developments, aimed at reducing capital costs; and bench-mark these against offshore wind.     

White Certificates for energy efficiency improvement with energy taxes: A theoretical economic model

In this paper we analyze interactions of two energy policy instruments, namely a White Certificates (WhC) scheme as an innovative policy instrument for energy efficiency improvement and energy taxation. These policy instruments differ in terms of objectives and final impacts on the price of electricity. We examine the effect of these policy instruments in the electricity sector, focusing on electricity producers and suppliers in a competitive market. Using microeconomic theory, we identify synergies between market players and demonstrate the total effect on the electricity price when suppliers internalize the behaviour of producers in their decisions. This model refers to an ideal market situation of full liberalization. The cases we examine consist of electricity producers with and without a carbon tax, electricity suppliers with and without an electricity tax, and with WhC obligations. Furthermore, we present a parallel implementation of WhC for electricity suppliers with carbon tax on electricity producers and an electricity tax with WhC obligations to electricity suppliers. We demonstrate differences in optimization behaviour of producers and suppliers. Based on a couple of cases of WhC with carbon and electricity taxes, various positive and negative effects of both schemes in terms of target achievement and efficiency are present, which can lead to an added value of such schemes in the policy mix, although uncertainties of outcomes are quite high. A basic finding is that in a merit order several parameters can increase final electricity price after the implementation of different policies: demand for electricity and electricity supply cost at a large scale and then follow the level of level of obligation for energy saving, level of penalty, and price of WhC (representing the marginal costs of energy saving projects). The impact magnitude of parameters depends on the values chosen and on the initial position of suppliers (i.e. if their actual behaviour deviates from full compliance with targets).     

The effect of variable renewable energy sources on electricity price volatility: the case of the Iberian market

The relationship between variable renewable energy supply (V-RES) and electricity price volatility is a controversial issue in the economic literature. In general, the literature has been inconclusive about the sign of the impact of installed capacity of these technologies on price volatility. This paper investigates the impact of V-RES on price volatility for the Iberian Market of Electricity (MIBEL), in the period ranging from 2010 to 2015. Using regression analysis and EGARCH models, we conclude that V-RES, and more specifically wind power supply, heightens price volatility. Likewise, greater intraday variability of V-RES also induces higher price volatility. Finally, following an analysis of the connection with the French market, we find that market coupling could help alleviate the sensitivity of price volatility to wind power supply variability.     

Intermittently renewable energy,optimal capacity mix and prices in a deregulated electricity market

This paper assesses the effect of intermittently renewable energy on generation capacity mix and market prices. We consider two generating technologies: (1) conventional fossil-fueled technology such as combined cycle gas turbine (CCGT), and (2) sunshine-dependent renewable technology such as photovoltaic cells (PV). In the first stage of the model (game), when only the probability distribution functions of future daily electricity demand and sunshine are known, producers maximize their expected profits by determining the CCGT and PV capacity to be constructed. In the second stage, once daily demand and sunshine conditions become known, each producer selects the daily production by each technology, taking the capacities of both technologies as given, and subject to the availability of the PV capacity, which can be used only if the sun is shining. Using real-world data for Israel, we confirm that the introduction of PV technology amplifies price volatility. A large reduction in PV capacity cost increases PV adoption but may also raise the average price. Thus, when considering the promotion of renewable energy to reduce CO₂ emissions, regulators should assess the behavior of the electricity market, particularly with respect to characteristics of renewable technologies and demand and supply uncertainties.     

Energy‐cost‐aware flow shop scheduling considering intermittent renewables,energy storage,and real‐time electricity pricing

The industrial sector is one of the major energy consumers that contribute to global climate change. Demand response programs and on‐site renewable energy provide great opportunities for the industrial sector to both go green and lower production costs. In this paper, a 2‐stage stochastic flow shop scheduling problem is proposed to minimize the total electricity purchase cost. The energy demand of the designed manufacturing system is met by on‐site renewables, energy storage, as well as the supply from the power grid. The volatile price, such as day‐ahead and real‐time pricing, applies to the portion supplied by the power grid. The first stage of the formulated model determines optimal job schedules and minimizes day‐ahead purchase commitment cost that considers forecasted renewable generation. The volatility of the real‐time electricity price and the variability of renewable generation are considered in the second stage of the model to compensate for errors of the forecasted renewable supply; the model will also minimize the total cost of real‐time electricity supplied by the real‐time pricing market and maximize the total profit of renewable fed into the grid. Case study results show that cost savings because of on‐site renewables are significant. Seasonal cost saving differences are also observed. The cost saving in summer is higher than that in winter with solar and wind supply in the system. Although the battery system also contributes to the cost saving, its effect is not as significant as the renewables.     

Re-examining uranium supply and demand: New insights

In this paper, we derive a simultaneous system of equations which aims at analysing the uranium supply and demand. In addition to reviewing and updating previous studies dealing with the uranium market analysis, in particular Amavilah (1995), the contribution of the paper lies in putting attention to some questions which are still either controversial or unanswered. They are especially related to the controversial hypothesis of the interdependence between uranium market and other commodities markets, both, with respect to the demand side, i.e. oil and coal markets, and the supply side, i.e. gold market. The paper also casts lights on electricity and uranium price effects on uranium demand as well as on the simultaneous interdependencies that may exist between nuclear consumption and nuclear installed capacity.     

Generators' bidding behavior in the NYISO day-ahead wholesale electricity market

This paper proposes a statistical and econometric model to analyze the generators' bidding behavior in the NYISO day-ahead wholesale electricity market. The generator level bidding data show very strong persistence in generators' grouping choices over time. Using dynamic random effect ordered probit model, we find that persistence is characterized by positive state dependence and unobserved heterogeneity and state dependence is more important than unobserved heterogeneity. The finding of true state dependence suggests a scope for economic policy intervention. If NYISO can implement an effective policy to switch generators from higher price groups to lower price groups, the effect is likely to be lasting. As a result, the market price can be lowered in the long-run. Generators' offered capacity is estimated by a two-stage sample selection model. The estimated results show that generators in higher-priced groups tend to withhold their capacity strategically to push up market prices. It further confirms the importance of an effective policy to turn generators into lower price groups in order to mitigate unexpected price spikes. The simulated market prices based on our estimated aggregate supply curve can replicate most volatility of actual DA market prices. Applying our models to different demand assumptions, we find that demand conditions can affect market prices significantly. It validates the importance of introducing demand side management during the restructure of electricity industry.     

The future developments of the electricity prices in view of the implementation of the Paris Agreements: Will the current trends prevail,or a reversal is ahead?

We assess the impact on the European electricity market of the European Union “Clean energy for all Europeans” package, which implements the EU Nationally Determined Contribution in Paris COP 21. We focus on the year 2030, which is the year with defined climate targets. For the assessment, we employ a game-theoretic framework of the wholesale electricity market, with high technical detail. The model is applied to two core scenarios, a Base scenario and a Low Carbon scenario to provide insights regarding the future electricity capacity, generation mix, cross-border trade and electricity prices. We also assess three additional variants of the core scenarios concerning different levels of: a) fossil and CO₂ prices; b) additional flexibility provided by batteries; c) market integration. We find that the electricity prices in 2030 substantially increase from today's level, driven by the increase in fuel and CO₂ prices. The flexibility from batteries helps in mitigating the price peaks and the price volatility. The increased low marginal cost electricity generation, the expansion of non-dispatchable and distributed capacities, and the higher market integration further reduce the market power from producers in the electricity markets from today's level.     

Effects of technological learning and uranium price on nuclear cost: Preliminary insights from a multiple factors learning curve and uranium market modeling

This paper studies the effects of returns to scale, technological learning, i.e. learning-by-doing and learning-by-searching, and uranium price on the prospects of nuclear cost decrease. We use an extended learning curve specification, named multiple factors learning curve (MFLC). In a first stage, we estimate a single MFLC. In a second stage, we estimate the MFLC under the framework of simultaneous system of equations which takes into account the uranium supply and demand. This permits not only to enhance the reliability of the estimation by incorporating the uranium price formation mechanisms in the MFLC via the price variable, but also to give preliminary insights about uranium supply and demand behaviors and the associated effects on the nuclear expansion.Results point out that the nuclear cost has important prospects for decrease via capacity expansion, i.e. learning-by-doing effects. In contrast, they show that the learning-by-searching as well as the scale effects have a limited effect on the cost decrease prospects. Conversely, results also show that uranium price exerts a positive and significant effect on nuclear cost, implying that when the uranium price increases, the nuclear power generation cost decreases. Since uranium is characterized by important physical availability, and since it represents only a minor part in the total nuclear cost, we consider that in a context of increasing demand for nuclear energy the latter result can be explained by the fact that the positive learning effects on the cost of nuclear act in a way to dissipate the negative ones that an increase in uranium price may exert. Further, results give evidence of important inertia in the supply and demand sides as well as evidence of slow correlation between the uranium market and oil market which may limit the inter-fuels substituability effects, that is, nuclear capacity expansion and associated learning-by-doing benefits.     

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.     

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.     

Expanding electricity capacity in Thailand to meet the twin challenges of supply security and environmental protection

Rapid growth in electricity demand in Thailand is a major challenge for electric utilities trying to ensure adequate supply. Continued reliance on natural gas for power supply makes the supply mix non-diversified and exposes the country to supply risks while a diversification to other fossil fuels imposes additional environmental burdens. To find an acceptable solution to this twin challenge, this paper assesses four scenarios of electricity capacity expansion planning for Thailand for the period between 2011 and 2025 under two different assumptions of fuel prices to reflect the case of international high oil price affecting cost of fuels for power generation in Thailand. It is found that the lowest environmental emissions are obtained from the scenario where power generation is highly dominated by natural gas. In contrast, the least cost electricity generation is achieved from the case if nuclear power plant is added into the Thai power system. Reliance on natural gas for power generation increases the spending on gas purchase as a share of the gross domestic product (GDP)—between 2.38% and 3.61% of (GDP). In addition, fuel import dependence, particularly for natural gas and coal, increases exposing the country to possible price volatility.     

Demand bidding construction for a large consumer through a hybrid IGDT-probability methodology

This paper provides a technique to derive the bidding strategy in the day-ahead market for a large consumer that procures its electricity demand in both day-ahead market and a subsequent adjustment market. It is considered that hourly market prices are normally distributed and this correlation is modeled by variance–covariance matrix. The uncertainty of procurement cost is modeled using concepts derived from information gap decision theory which allows deriving robust bidding strategies with respect to price volatility. First Order Reliability Method is applied to construct the robust bidding curve. The proposed technique is illustrated through a realistic case study.     

Price,environment and security: Exploring multi-modal motivation in voluntary residential peak demand response

Peak demand on electricity grids is a growing problem that increases costs and risks to supply security. Residential sector loads often contribute significantly to seasonal and daily peak demand. Demand response projects aim to manage peak demand by applying price signals and automated load shedding technologies. This research investigates voluntary load shedding in response to information about the security of supply, the emission profile and the cost of meeting critical peak demand in the customers’ network. Customer willingness to change behaviour in response to this information was explored through mail-back survey. The diversified demand modelling method was used along with energy audit data to estimate the potential peak load reduction resulting from the voluntary demand response. A case study was conducted in a suburb of Christchurch, New Zealand, where electricity is the main source for water and space heating. On this network, all water heating cylinders have ripple-control technology and about 50% of the households subscribe to differential day/night pricing plan. The survey results show that the sensitivity to supply security is on par with price, with the emission sensitivity being slightly weaker. The modelling results show potential 10% reduction in critical peak load for aggregate voluntary demand response.     

Capacity commitment and price volatility in a competitive electricity market

The long lead time required to add new capacity in the electricity generation industry means that daily demands are necessarily served by capacity already installed. However, in a competitive market, even if the installed capacity was designed to serve the projected demands, frequent surpluses and occasional full utilization inevitably lead to price volatility. This paper develops a two-stage model of the generation market in which capacity construction occurs in stage 1, before demand realization, and price determination occurs in stage 2, when the equilibrium price ensures that the realized demand does not exceed the installed capacity. We show that price volatility and price spikes are inevitable, and that while price capping can mitigate high and volatile prices, it causes unmet demands and reduction in system reliability. This paper accentuates the interdependence among generating capacity, price volatility and service reliability, a primary cause of concern in the debate on electricity market reform.