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The forward curve dynamics in the Nordic electricity market is examined. Six years of price data on futures and forward contracts traded in the Nordic electricity market are analysed. For the forward price function of electricity, we specify a multi‐factor term structure models in a Heath‐Jarrow‐Morton framework. Principal component analysis is used to reveal the volatility structure in the market. A two‐factor model explains 75 per cent of the price variation in our data, compared to approximately 95 per cent in most other markets. Further investigations show that correlation between short‐ and long‐term forward prices is lower than in other markets. We briefly discuss possible reasons why these special properties occur, and some consequences for hedging exposures in this market.

This chapter examines the efficiency of the Midcontinent Independent System Operator (MISO), Inc., electricity exchange following its major expansion in terms of market participants and geographic scope in 2014. Specifically, hourly day-ahead (forward) and real-time (spot) prices from 2014 to 2016 reveal that forward premiums are prevalent despite the increase in market size. Furthermore, these forward premiums do not adhere to Bessembinder and Lemmon’s (2002) commonly used general equilibrium model for electricity forward premia. A technical trading rule based on the relationship between day-ahead prices across hubs that was found to be profitable prior to MISO’s expansion still produces economically and statistically significant returns after the exchange’s growth.

Midwest Independent Transmission System Operator, Inc. (MISO) is a nonprofit regional transmission organization (RTO) that oversees electricity production and transmission across 13 states and 1 Canadian province. MISO also operates an electronic exchange for buying and selling electricity for each of its five regional hubs.

MISO oversees two types of markets. The forward market, which is referred to as the day-ahead (DA) market, allows market participants to place demand bids and supply offers on electricity to be delivered at a specified hour the following day. The equilibrium price, known as the locational marginal price (LMP), is determined by MISO after receiving sale offers and purchase bids from market participants. MISO also coordinates a spot market, which is known as the real-time (RT) market. Traders in the RT market must submit bids and offers by 30minutes prior to the hour for which the trade will be executed. After receiving purchase and sale offers for a given hour in the RT market, MISO then determines the LMP for that particular hour.

The existence of the DA and RT markets allows producers and retailers to hedge against the large fluctuations that are common in electricity prices. Hedge ratios on the MISO exchange are estimated using various techniques. No hedge ratio technique examined consistently outperforms the unhedged portfolio in terms of variance reduction. Consequently, none of the hedge ratio methods in this study meet the general interpretation of FASB guidelines for a highly effective hedge.

We consider the partial hedging of stochastic electricity load pattern with static forward strategies. We assume that the company under consideration maximizes the risk adjusted expected value of its electricity cash flows. First, we calculate an optimal hedge ratio and after that we use this hedge ratio to solve the optimal hedging time. Our results indicate, for instance that agents with high load volatility hedge later than agents that have low load volatility. Moreover, negative correlation between forwards and electricity load pattern postpones the hedging timing.

This chapter focuses on the common occurrence of wholesale electricity prices that fall below the cost of production. This “negative pricing” in effect represents payment to high-volume consumers for taking excess power off the grid, thus relieving overload. Occurrences of negative pricing have been observed since the wholesale electricity markets have been operating, and occur during periods of low demand, while generators are being kept in reserve for rapid engagement when demand increases (it is expensive and time-consuming to shut down generators and then restart them, so they are often kept in “spooling mode”). In such situations power production may temporarily exceed demand, potentially overloading the system. When the federal government began subsidizing the construction of wind generation projects, with regulations in place requiring transmission grids to accept all of the electricity produced by the wind generators, negative pricing became more frequent.

This study aims to formulate a mechanism design in the derivatives market, summarizing a framework to set up the Brazilian electricity futures market.

This exploratory study formulates a mechanism design in the derivatives market, summarizing a framework to set up the Brazilian electricity futures market.

The results show a positive economic outcome for the creation of the Brazilian futures electricity market.

The main feature in this work is to summarize a framework to set up the Brazilian electricity futures market applying mechanism design, applicable in other countries. The features of the mechanism are the space of expected results (Z), the strategies to survey the environmental space (θ) and the mechanism design – messages space (M).

The physical nature of electricity generation and delivery creates special problems for the design of efficient markets, notably the need to manage delivery in real time and the volatile congestion and associated costs that result. Proposals for the operation of the deregulated electricity industry tend towards one of two paradigms: centralized and decentralized. Transmission congestion management can be implemented in the more centralized point‐to‐point approach, as in New York state, where derivative transmission congestion contracts (TCCs) are traded, or in the more decentralized flowgate‐based approach. While it is widely accepted that theoretically TCCs have attractive properties as hedging instruments against congestion cost uncertainty, whether efficient markets for them can be established in practice has been questioned. Based on an empirical analysis of publicly available data from years 2000 and 2001, it appears that New York TCCs provided market participants with a potentially effective hedge against volatile congestion rents. However, the prices paid for TCCs systematically diverged from the resulting congestion rents for distant locations and at high prices. The price paid for the hedge not being in line with the congestion rents, i.e., unreasonably high risk premiums are being paid, suggests an inefficient market. The low liquidity of TCC markets and the deviation of TCC feasibility requirements from actual energy flows are possible explanations.

In the hybrid electricity market consisting of renewable and conventional energy, the generation output of renewable power is uncertain because of its intermittency, and the power market demand is also fluctuant. Meanwhile, there is fierce competition among power producers in the power supply market and retailers in the demand market after deregulation, which increases the difficulty of renewable energy power grid-connection. To promote grid-connection of renewable energy power in the hybrid electricity market, the authors construct different contract decision-making models in the “many-to-many” hybrid power supply chain to explore the pricing strategy of renewable energy power grid-connecting.

Considering the dual-uncertainty of renewable energy power output and electricity market demand, the authors construct different decision-making models of wholesale price contract and revenue-sharing contract to compare and optimize grid-connecting pricing, respectively, to maximize the profits of different participants in the hybrid power supply chain. Besides, the authors set different parameters in the models to explore the influence of competition intensity, government subsidies, etc. on power pricing. Then, a numerical simulation is carried out, they verify the existence of the equilibrium solutions satisfying the supply chain coordination, compare the differences of pricing contracts and further analyze the variation characteristics of optimal contract parameters and their interaction relations.

Revenue-sharing contract can increase the quantity of green power grid-connection and realize benefits Pareto improvement of all parties in hybrid power supply chain. The competition intensity both of power supply and demand market will have an impact on the sharing ratio, and the increase of competition intensity results in a reduction of power supply chain coordination pressure. The power contract price, spot price and selling price have all been reduced with the increase of the sharing ratio, and the price of renewable power is more sensitive to the ratio change. The sharing ratio shows a downward trend with the increase of government green power subsidies.

On the basis of expanding the definition of hybrid power market and the theory of newsvendor model, considering the dual-uncertainty of green power generation output and electricity market demand, this paper builds and compares different contract decision-making models to study the grid-connection pricing strategy of renewable energy power. And as an extension of supply chain structure types and management, the authors build a “many-to-many” power supply chain structure model and analyze the impact of competition intensity among power enterprises and the government subsidy on the power grid-connecting pricing.