Impacts of variable renewable energy on wholesale markets and generating assets in the United States: A review of expectations and evidence

We synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted or might in the future impact bulk power system assets, pricing, and costs in the United States. Most studies of future scenarios indicate that VRE reduces wholesale energy prices and capacity factors of thermal generators. Traditional baseload generators are more exposed to these changing market conditions than low-capital cost and more flexible intermediate and peak-load generators. From analysis of historical data we find that VRE is already influencing the bulk power market through changes in temporal and geographic patterns areas with higher levels of VRE. The most significant observed impacts have concentrated in areas with significant VRE and/or nuclear generation along with limited transmission, with negative pricing also often occurring during periods with lower system-wide load. So far, however, VRE, has had a relatively modest impact on historical average annual wholesale prices across entire market regions, at least in comparison to other drivers. The reduction of natural gas prices is the primary contributor to the decline in wholesale prices since 2008. Similarly, VRE impacts on thermal plant retirements have been limited and there is little relationship between the location of recent retirements and VRE penetration levels. Although impacts on wholesale prices have been modest so far, impacts of VRE on the electricity market will be more significant under higher VRE penetrations

Assessing the role of fluctuating renewables in energy transition: Methodologies and tools

Due to the environmental impacts brought by current energy schemes, the energy transition, a new paradigm shift from fossil fuels to renewable energy, has been widely accepted and is being realized through collective international, regional, and local efforts. Electricity, as the most direct and effective use of renewable energy sources (RES), plays a key role in the energy transition. In this paper, we first discuss a viable pathway to energy transition through the electricity triangle, highlighting the role of RES in electricity generation. Further, we propose methodologies for the planning of wind and solar PV, as well as how to address their uncertainty in generation expansion problems. Finally, by using a web-based tool, “RES-PLAT”, we demonstrate the scheme in a case study in Egypt, which evaluates the impacts and benefits of a large-scale RES expansion

The Market Viability of Nuclear Hydrogen Technologies.

The Department of Energy Office of Nuclear Energy is supporting system studies to gain a better understanding of nuclear power's potential role in a hydrogen economy and what hydrogen production technologies show the most promise. This assessment includes identifying commercial hydrogen applications and their requirements, comparing the characteristics of nuclear hydrogen systems to those market requirements, evaluating nuclear hydrogen configuration options within a given market, and identifying the key drivers and thresholds for market viability of nuclear hydrogen options. One of the objectives of the current analysis phase is to determine how nuclear hydrogen technologies could evolve under a number of different futures. The outputs of our work will eventually be used in a larger hydrogen infrastructure and market analysis conducted for DOE-EE using a system-level market simulation tool now underway. This report expands on our previous work by moving beyond simple levelized cost calculations and looking at profitability, risk, and uncertainty from an investor's perspective. We analyze a number of technologies and quantify the value of certain technology and operating characteristics. Our model to assess the profitability of the above technologies is based on Real Options Theory and calculates the discounted profits from investing in each of the production facilities. We use Monte-Carlo simulations to represent the uncertainty in hydrogen and electricity prices. The model computes both the expected value and the distribution of discounted profits from a production plant. We also quantify the value of the option to switch between hydrogen and electricity production in order to maximize investor profits. Uncertainty in electricity and hydrogen prices can be represented with two different stochastic processes: Geometric Brownian Motion (GBM) and Mean Reversion (MR). Our analysis finds that the flexibility to switch between hydrogen and electricity leads to significantly different results in regards to the relative profitability of the different technologies and configurations. This is the case both with a deterministic and a stochastic analysis, as shown in the tables below. The flexibility in output products clearly adds substantial value to the HPE-ALWR and HTE-HTGR plants. In fact, under the GBM assumption for prices, the HTE-HTGR plant becomes more profitable than the SI-HTGR configuration, although SI-HTGR has a much lower levelized cost. For the HTE-HTGR plant it is also profitable to invest in additional electric turbine capacity (Case b) in order to fully utilize the heat from the nuclear reactor for electricity production when this is more profitable than producing hydrogen. The technologies are all at the research and development stage, so there are significant uncertainties regarding the technology cost and performance assumptions used in this analysis. As the technologies advance, the designers need to refine the cost and performance evaluation to provide a more reliable set of input for a more rigorous analysis. In addition, the durability of the catalytic activity of the materials at the hydrogen plant during repetitive price cycling is of prime importance concerning the flexibility of switching from hydrogen to electricity production. However, given the potential significant economic benefit that can be brought from cogeneration with the flexibility to quickly react to market signals, DOE should consider R&D efforts towards developing durable materials and processes that can enable this type of operation. Our future work will focus on analyzing a range of hydrogen production technologies associated with an extension of the financial analysis framework presented here. We are planning to address a variety of additional risks and options, such as the value of modular expansion in addition to the co-generation capability (i.e., a modular increase in the hydrogen production capacity of a plant in a given market with rising hydrogen demand), and contrast that with economies-of-scale of large-unit designs

Wind Power Forecasting : State-Of-The-Art 2009.

Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem

A Quick Guide to Wind Power Forecasting : State-Of-The-Art 2009.

This document contains a summary of the main findings from our full report entitled 'Wind Power Forecasting: State-of-the-Art 2009'. The aims of this document are to provide guidelines and a quick overview of the current state-of-the-art in wind power forecasting (WPF) and to point out lines of research in the future development of forecasting systems

Electrify Italy

This study explores a possible pathway to implement a new energy paradigm in Italy based on electrification. The objectives are: • To build a forward-looking vision of possible scenarios at 2022, 2030 and 2050 by integrating a multi-focus perspective on the penetration of renewables and the electrification potential of the residential, industrial and transport sectors. • To estimate the potential benefits of further electrification through the calculation of Key Performance Indicators in four different areas: energy, economy, environment and society. The study shows how the electricity triangle, a paradigm based on clean generation by renewable sources, electrification of final uses, and electricity exchange through efficient smart grids, closes the loop of clean energy and efficient consumption. This leads to improvements in energy, environment, economy and social performances, and boosts the share of renewables in final consumption

Fuel Mix Characteristics and Expected Stock Returns of European Power Companies

This article investigates the impact of the fuel mix structure in power generation portfolios on expected stock returns for major European power companies. The 22 biggest publicly listed European power producers are examined between January 2005 and December 2010. Based on the capital asset pricing model (CAPM) and multi-factor market models, the systematic risk of the power companies relative to the overall market performance and other typical energy and macroeconomic risk factors is analyzed. The full-information approach is used to determine technology-specific betas and risk factor sensitivities from the sample. Although most companies are not exclusively in the power producing business, it is shown that the generation fuel mix has a significant impact on the historical stock returns of the investigated companies. In particular, the sample companies exhibit significant differences in the systematic risk of gas and nuclear generation technologies compared with renewable technologies measured by technology-specific, delevered beta factors. This study extends existing literature and contributes new insights in two ways: Firstly, this is to our knowledge the first empirical analysis comparing the financial risk of different electricity generation technologies. Secondly, the results provide practical benefit to determine adequate riskadjusted capital costs for typical generation technologies. Therewith, this study is relevant for evaluating all kinds of power plant investments