Managing volumetric risk of long-term power purchase agreements

The electricity market in the UK has been reformed over recent years resulting in the introduction of ‘Contracts for Difference’ as an option for wind producers. They can use these contracts only if at the same time they enter into other market contracts, i.e., Power Purchase Agreements or participation in the wholesale market. Most wind producers prefer the option of holding a long-term Power Purchase Agreement with another party. However, these agreements do not always offer the best terms for a wind producer due to them selling energy at lower electricity prices than those of the wholesale market spot prices. In addition, direct participation in the wholesale market can lead to high imbalance costs for the wind producers. In this paper, we propose an optimal dispatch model solved via dynamic programming optimisation to examine these two different business cases for wind operators alongside the existence (or not) of subsidised Contracts for Difference. A case study with an onshore UK wind farm and a lithium-based battery is provided. The proposed methodology was designed flexibly, so that it can be applied to different wind farm and battery configurations, as well as energy market structures. It is found that it is not always more profitable for the wind operator to hold a Power Purchase Agreement with another party than owning a battery storage unit and trading wind energy directly into the wholesale market. The discount rate of the Power Purchase Agreements, the capital cost of the wind farm and the strike price of the Contracts for Difference are critical factors affecting the profitability of both business cases. In addition, if subsidies are totally removed from both of them, then these are no longer economically justifiable, unless significant reductions are achieved in the capital costs of wind farms and battery storage units. Lastly, we show that considering only the calendar life of the battery (and not the cycle life) leads to significant underestimation of the investment costs.

This study presents a technoeconomic analysis of a hybrid wind‐PV (photovoltaic) power plant (HPP) compared to onshore wind power plants (WPPs) and photovoltaic power plants (PVPPs) in the Nordic electricity market, focusing on locations in Finland and Sweden. Wind power capacity has recently increased significantly in the Nordics, increasing the profit cannibalization of wind power. Renewable energy subsidies have been phased out in Finland and Sweden, thus new wind and PV power value creation is formed from the power market. The PV power capacity has also encountered significant growth in the Nordics. However, the capacity is still relatively low, allowing more revenue for produced PV power compared to wind power. The lower PV power profit cannibalization has increased interest in HPPs instead of WPPs. This contribution studies the economic feasibility of wind and PV power in changing market conditions in the Nordic electricity market. The market operation is modeled with three different configurations including selling all the power into the day ahead spot market and baseload or pay‐as‐produced power purchase agreement (PPA). In addition, a battery energy storage system (BESS) investment is analyzed using the operating strategy of shifting production to more profitable spot price hours. This study shows that due to the profit cannibalization and high cost of capital, the power plants are currently not profitable in the Nordic electricity market except when the bidding area has high average spot prices. The worst profitability was with WPPs when exposed to the market shape risk and with PVPPs when pay‐as‐produced PPA was agreed upon due to the higher levelized cost of electricity. However, the PV power profit cannibalization is expected to increase in the future as more PVPPs operate in the Nordic power market. Thus, the PVPP shape risk may increase in the future as well.

This paper provides a comprehensive analysis of how the correlation between wind power and electricity prices affects the offer strategies of wind power producers (WPPs). In a market that has a high penetration of wind energy, the correlation can be noticeable and thus should be considered by the WPPs when building offer strategies. First, this paper aims to build an advanced offer curve that considers the joint information of wind power and real-time (RT) prices. Then, we explore the sensitivity of the expected profit, value at risk (VaR), and conditional value at risk (CVaR) for the advanced offer curves to the probabilistic parameters of wind power and RT prices. We find that an offer curve which reflects this correlation generally results in a small improvement in expected profit, but a meaningful reduction in risks. The benefits of the advanced offer curves increase as the correlation becomes more negative or the variances of wind power and prices increase.

European countries are increasing their share of power production from wind and solar energy to mitigate climate change. Also the relative contributions from PV and wind power production in Europe change over time. At present, the installed capacity of photovoltaic (PV) power for all of Europe is smaller than that of wind power with a ratio of 3:4. Future scenarios for the installations of PV and wind power capacities for 2050 suggest that this ratio will substantially change. Namely, the PV power capacity might exceed the wind power capacity with a ratio of 3:2 to 2:1. We test the hypothesis that the weather dependency of anomalies in the PV plus wind power production will change in the future compared to today. Specifically, we examine which synoptic weather patterns are associated with anomalies in the PV plus wind power production for the present and future installed capacities in Europe. To that end, we developed a renewable energy model for the installed capacity of 2019 and 2050. This model allows us to simulate hourly PV and wind power production at 6 km horizontal resolution for all of Europe. We analyze the weather dependency of power-production anomalies by pairing our model output with results of the classification of weather patterns from the German Weather Service. Our results highlight similar weather patterns associated with positive anomalies in the hourly PV plus wind power production for the 2019 and 2050 installation, namely weather patterns with prevailing westerly winds. However, weather patterns associated with negative anomalies strongly change between the two installations. We also assess the dependency of the results on the duration of the production anomalies. Particularly for long production anomalies, the associated weather patterns are different for the 2019 and 2050 installation. One exception is the weather pattern Anticyclonic Southeasterly that is associated with the lowest 10-day power production in Europe for both 2019 and 2050. Regionally, weather patterns have different impacts on different regions in Europe, when comparing the associated patterns between the 2019 and 2050 installation. For instance, anomalously low power production differ for the Iberian peninsula and Southeastern Europe when the two installed capacities are compared. Taken together, our study gives a systematic overview on changes in the weather dependency of anomalies in the mix of PV and wind power between 2019 and 2050.

Wind power is one of the most rapidly growing clean and renewable energy sources. However, due to the uncertainty and intermittency of wind power, the increasing penetration of wind power into the electric power system will pose challenges to power system operators. Moreover, as a participant in a competitive electricity market, a wind power producer's behavior and profit will be influenced by other participants' behaviors. This paper proposes a model of using stochastic programming to generate optimal bidding strategies to maximize the total profits of wind and conventional power producers in both the energy market and a bilateral reserve market, where the reserve price is settled between wind and conventional power producers by using game theory. Case studies using real-world data for games in an electricity market with different types of players are performed to show the effectiveness of the proposed model.

We model the logarithm of the spot price of electricity with a normal inverse Gaussian (NIG) process and the wind speed and wind power production with two Ornstein–Uhlenbeck processes. In order to reproduce the correlation between the spot price and the wind power production, namely between a pure jump process and a continuous path process, respectively, we replace the small jumps of the NIG process by a Brownian term. We then apply our models to two different problems: first, to study from the stochastic point of view the income from a wind power plant, as the expected value of the product between the electricity spot price and the amount of energy produced; then, to construct and price a European put-type quanto option in the wind energy markets that allows the buyer to hedge against low prices and low wind power production in the plant. Calibration of the proposed models and related price formulas is also provided, according to specific datasets.

FuelCell Energy signs PPAs for two large projects in Connecticut

Power purchase agreements aim to secure long-term contracts between sellers and buyers, particularly in renewable energy transactions. However, successful negotiations for a fixed long-term price and energy volume while ensuring maximum utility for stakeholders remains a significant challenge. This paper introduces a comprehensive model for negotiating 24/7 power purchase agreements, focusing on hourly pricing to address deficits and surpluses throughout each day of the contract timeline. The model incorporates demand flexibility through battery storage, settling on the strike price using Nash Bargaining theory and optimal management of energy consumption relative to market price fluctuations. A soft margin support vector machine classification model determines the buyer’s maximum acceptable price. Moreover, Gaussian process classification is employed to calculate a probabilistic, risk-adjusted strike price, enabling a data-driven approach to power purchase negotiations. The proposed model’s performance is demonstrated through a detailed case study of Norway, illustrating how demand flexibility can significantly lower long-term power purchase agreement contract prices. The analysis of yearly price trends indicates that incorporating flexibility resources in long-term energy contracts may lead to a reduction in strike prices by around 25%. Moreover, such flexibility enhances demand-generation matching, thereby increasing renewable energy transactions within such agreements.

Power Purchase Agreements (PPAs) enjoy great success in Europe. This is especially true of Green Corporate PPAs (GC PPAs), also known as Corporate Renewable PPAs, which are agreements under which a corporate customer agrees to purchase renewable electricity directly from the electricity producer, pursuant to the definition set forth in the 2018 Renewable Energy Directive (‘RED II’) (Directive (EU) 2018/2001 of the European Parliament and of the Council of 11 Dec. 2018 on the promotion of the use of energy from renewable sources (recast).). Nearly 14GW in PPAs were entered into in 2018 worldwide, of which 1.9GW in Europe (2017: 1GW) and approx. 8GW in the United States (2017: 2.4GW) (Europe Corporate Renewable, PPA Market Report 2018 – 2027.). Wind energy accounts for 85% of GC PPAs entered into in Europe to date, with solar energy accounting for the remaining 15%. This progress can be explained partly by an increase in energy demand worldwide, the companies’ willingness to reduce their carbon footprint and control energy costs, the need for clear and foreseeable price signals for investors and producers, but also the development of public support schemes for renewable energies (‘RE’). Power Purchase Agreement, Renewable Energy, Electricity, French Law, Energy transition, Corporate Social Responsibility

To reach Carbon Peak in 2030 and Carbon Neutrality in 2060, China is developing renewable energy at a fast pace. Renewable energy enterprises will participate in the power market in an all-round way as China gradually improves its electricity market. Signing the Power Purchase Agreement (PPA) helps renewable energy companies to avoid market risk and achieve sustainable development. Therefore, a novel PPA pricing model is proposed in our research. Based on the theory of the Levelized Cost of Energy (LCOE), our model considers system operating costs in China’s dual-track electric power sector, which is both government-guided and market-oriented. First of all, key influencing factors of the PPA agreement are analyzed in view of the developments of the renewable energy and electricity markets in China. Next, the design of pricing strategies for renewable energy power plants to cope with market challenges is presented through a photovoltaic project case study. The results show that when the operating costs of the system are considered and other conditions remain unchanged, the investment payback period of the new energy power station will change from 10.8 years to 13.6 years. Furthermore, correlation degree and sensitivity coefficient (SAF) were introduced to conduct correlation analysis and sensitivity analysis of key elements that affect the pricing of the PPA. Finally, it is concluded that the utilization hours of power generation have the most significant effect on the PPA price, while the system’s operating cost is the least sensitive factor. The study expands the application of LCOE, and provides a decision-making solution for the PPA pricing of renewable energy power enterprises. It is expected to help promote power transactions by renewable energy companies.

Technical and economic viability of greenfield large scale photovoltaic plants in Romania

Malaysia introduced Feed-in Tariff (FiT) in 2004 to incentivise renewable energy projects through the implementation of the National Renewable Energy Policy and Action Plan 2009 and the Renewable Energy Act 2011 (Act 725). Nevertheless, this FiT system failed to assist the country in increasing electricity generation from renewable sources. Later, auctions were introduced to boost the renewable shares, particularly solar photovoltaic power generation, after the quota for solar under the FiT were taken up. The tenders incorporated standard form of the contract along with a long-term Power Purchase Agreements (PPA) which induced for the lowest price for power generation and guaranteed access to the national grid. This measure is considered as an excellent instrument to expand the renewable energy sector. There has always been a question: whether abandoning FiT for auctions is a feasible choice in the interest of sustainable clean energy for sustainable development? The main objective of the present article is to investigate the implementation of auctions to support renewable energy development in Malaysia and to examine whether auctions could replace FiT. This study adopted a doctrinal and comparative approach. It concluded that competitive bidding is preferable to support mature technology and large-scale generations, while FiT should be sustained to support new technologies. The article has also identified several countries such as Germany and India, who have successfully implemented competitive bidding systems to support the aspiration to expand the renewable energy sector.

Analysis and decomposition of active and reactive power spot price in deregulated electricity markets

This paper considers a wind power producer playing strategically in a day-ahead market while willing to set demand response (DR) contracts with a DR aggregator. To this end, a bilevel problem including a single leader and two followers is formulated. The wind power producer is the leader aiming at maximizing its profit through offering into a day-ahead market and clearing its deviation in a balancing market. The strategic behavior of the producer in the day-ahead market is modeled through the market clearing process (follower 1). In addition, the DR aggregator behavior is modeled through a revenue function in which the aggregator is able to sell its DR product to the wind power producer, other competitors and the day-ahead market (follower 2). The overall problem is a stochastic mathematical program with equilibrium constraints (MPEC) in which wind power production and imbalance prices are associated with uncertainty. The problem is then transformed into a linear programming approach. A case of the Nordic market is chosen to assess the validity of the given problem.

In Thailand, electric supply services have all been taken over by the state and operated under state enterprises since 1968. Under a law empowering its monopoly, state utilities accumulated assets and built up their manpower to expand and operate the power system to serve the whole country. During the time of high growth in power demand in early the1990 s, the government initiated a move to privatize state electric utilities, the pace of which was firmed up after 1997, the year of the financial crash. Engagement of independent power producers (IPPs) through the use of long-term power purchase agreements (PPAs) for supply of electric power into the system operated by state electric utilities was also initiated from the mid 1990s. Total capacity of IPPs and Small Power Producers (SPPs) that sell excess power from cogeneration on to the system) rose and by the late 1990s started to create a constraint on system economic dispatch. In 1999 the National Energy Policy Council (NEPC) approved a recommendation of international consultants to transform the electric supply industry into a structure similar to the system in the United Kingdom. The transformation was proposed to precede corporatization and privatization of state electric utilities. The objectives of deregulation were to revoke the monopoly in ESI, to improve transparency in electricity pricing, to reduce debts of state enterprises, and to improve economic efficiency. Industry participants have voiced strong objection to the industry model proposed. With the change of market structure in UK to the New Electricity Trading Arrangement (NETA), the secretariat of NEPC also proposed a new structure similar to NETA. More acceptance from industry participants have been received for the new structure. However, it has been assumed that the proposed structure would bring improvement in system reliability, drawing investment into power generation in a manner that would be efficient. Tariff has also been expected to become lower because of the competition in power generation and retail trading. The authors argue that, for developing countries, issues of timely investment in new generation and delivery capacity, stable and reasonable price of electricity, reliability of power supply, fuel diversity and security, equitable access of supply and promotion of social equity are important. Maintaining a functioning ESI that meet the broad objectives of providing reliable power supply to serve social and economic development needs could be prioritized over introduction of complete competition in wholesale generation and retailing. The authors examine the present situation of the industry and propose a transitional model that would serve the broad objectives and introduce gradual competition in the industry. The proposed design would unbundle generation from transmission and retailing. It would aso eventually promote intra-regional interconnection and electricity trading.