Long-Term Load Forecasting Considering Volatility Using Multiplicative Error Model

Long-term load forecasting plays a vital role for utilities and planners in terms of grid development and expansion planning. An overestimate of long-term electricity load will result in substantial wasted investment in the construction of excess power facilities, while an underestimate of future load will result in insufficient generation and unmet demand. This paper presents first-of-its-kind approach to use multiplicative error model (MEM) in forecasting load for long-term horizon. MEM originates from the structure of autoregressive conditional heteroscedasticity (ARCH) model where conditional variance is dynamically parameterized and it multiplicatively interacts with an innovation term of time-series. Historical load data, accessed from a U.S. regional transmission operator, and recession data for years 1993-2016 is used in this study. The superiority of considering volatility is proven by out-of-sample forecast results as well as directional accuracy during the great economic recession of 2008. To incorporate future volatility, backtesting of MEM model is performed. Two performance indicators used to assess the proposed model are mean absolute percentage error (for both in-sample model fit and out-of-sample forecasts) and directional accuracy.Comment: 19 pages, 11 figures, 3 table

Infrastructure investment in network industries: The role of incentive regulation and regulatory independence

This paper finds that coherent regulatory policies can boost investment in network industries of OECD economies. Rate-of-return regulation is generally thought to result in overinvestment, while incentive regulation is believed to entail underinvestment. Yet, previous empirical work has generally found that the introduction of incentive regulation has not systematically changed investment in network industries. According to the theoretical literature, regulatory uncertainty exposes both types of regimes to the danger of underinvestment. However, regulatory uncertainty is arguably higher under rate-of-return regulation because investment decisions (what can be included in the rate base) are usually evaluated in a discretionary manner, while firms operating under incentive regulation are less affected by this behaviour. In addition, incentive regulation encourages investment in cost-reducing technologies. Using Bayesian model averaging techniques, this paper shows that incentive regulation implemented jointly with an independent sector regulator (indicating lower regulatory uncertainty) has a strong positive impact on investment in network industries. In addition, lower barriers to entry are also found to encourage sectoral investment. These results support the importance of implementing policies in a coherent framework.http://deepblue.lib.umich.edu/bitstream/2027.42/64379/1/wp956.pd

Valuing fuel diversification in optimal investment policies for electricity generation portfolios

Optimal capacity allocation for investments in electricity generation assets can be deterministically derived by comparing technology specific long-term and short-term marginal costs. In an uncertain market environment, Mean-Variance Portfolio (MVP) theory provides a consistent framework to valuate financial risks in power generation portfolios that allows to derive the efficient fuel mix of a system portfolio with different generation technologies from a welfare maximization perspective. Because existing literature on MVP applications in electricity generation markets uses predominantly numerical methods to characterize portfolio risks, this article presents a novel analytical approach combining conceptual elements of peak-load pricing and MVP theory to derive optimal portfolios consisting of an arbitrary number of plant technologies given uncertain fuel prices. For this purpose, we provide a static optimization model which allows to fully capture fuel price risks in a mean variance portfolio framework. The analytically derived optimality conditions contribute to a much better understanding of the optimal investment policy and its risk characteristics compared to existing numerical methods. Furthermore, we demonstrate an application of the proposed framework and results to the German electricity market which has not yet been treated in MVP literature on electricity markets.power plant investments, peak load pricing, mean-variance portfolio theory, fuel mix diversification

Infrastructure investment in network industries: The role of incentive regulation and regulatory independence

This paper finds that coherent regulatory policies can boost investment in network industries of OECD economies. Rate-of-return regulation is generally thought to result in overinvestment, while incentive regulation is believed to entail underinvestment. Yet, previous empirical work has generally found that the introduction of incentive regulation has not systematically changed investment in network industries. According to the theoretical literature, regulatory uncertainty exposes both types of regimes to the danger of underinvestment. However, regulatory uncertainty is arguably higher under rate-of-return regulation because investment decisions (what can be included in the rate base) are usually evaluated in a discretionary manner, while firms operating under incentive regulation are less affected by this behaviour. In addition, incentive regulation encourages investment in cost-reducing technologies. Using Bayesian model averaging techniques, this paper shows that incentive regulation implemented jointly with an independent sector regulator (indicating lower regulatory uncertainty) has a strong positive impact on investment in network industries. In addition, lower barriers to entry are also found to encourage sectoral investment. These results support the importance of implementing policies in a coherent framework.network industries; regulation; incentive regulation; price cap; cost-plus regulation;rate-of-return regulation; regulatory independence; investment.

Infrastructure Investment in Network Industries: The Role of Incentive Regulation and Regulatory Independence

This paper finds that coherent regulatory policies can boost investment in network industries of OECD economies. Rate-of-return regulation is generally thought to result in overinvestment, while incentive regulation is believed to entail underinvestment. Yet, previous empirical work has generally found that the introduction of incentive regulation has not systematically changed investment in network industries. According to the theoretical literature, regulatory uncertainty exposes both types of regimes to the danger of underinvestment. However, regulatory uncertainty is arguably higher under rate-of-return regulation because investment decisions (what can be included in the rate base) are usually evaluated in a discretionary manner, while firms operating under incentive regulation are less affected by this behaviour. In addition, incentive regulation encourages investment in cost-reducing technologies. Using Bayesian model averaging techniques, this paper shows that incentive regulation implemented jointly with an independent sector regulator (indicating lower regulatory uncertainty) has a strong positive impact on investment in network industries. In addition, lower barriers to entry are also found to encourage sectoral investment. These results support the importance of implementing policies in a coherent framework.network industries, regulation, incentive regulation, price cap, cost-plus regulation, rate-of-return regulation, regulatory independence, investment

Financing Capture Ready Coal-Fired Power Plants in China by Issuing Capture Options

‘Capture Ready’ is a design concept enabling fossil fuel plants to be retrofitted more economically with carbon dioxide capture and storage (CCS) technologies, however financing the cost of capture ready can be problematic, especially in the developing world. We propose that fossil fuel plants issue tradable Capture Options to acquire financing. The Capture Option concept could move CCS forward politically in countries such as China, speed up CCS technology development, help Capture Ready investors diversify risk, and offer global warming investors an alternative investment opportunity. As a detailed case study, we assess the value of a Capture Option and Capture Ready plant for a 600 MW supercritical pulverized coal power plant in China, using a cash flow model with Monte-Carlo simulations. The gross value of Capture Ready varies from CNY3m ($0.4m) to CNY633m ($84.4m) at an 8% discount rate and the Capture Option is valued at CNY113m ($15.1m) to CNY1255m ($167.3m) for two of the four scenarios analyzed

World Nuclear Industry Status Report 2013

Two years after the Fukushima disaster started unfolding on 11 March 2011, its impact on the global nuclear industry has become increasingly visible. Global electricity generation from nuclear plants dropped by a historic 7 percent in 2012, adding to the record drop of 4 percent in 2011. This World Nuclear Industry Status Report 2013 (WNISR) provides a global overview of the history, the current status and the trends of nuclear power programs worldwide

Sharpening the Cutting Edge: Corporate Action for a Strong, Low-Carbon Economy

Outlines lessons learned from early efforts to create a low-carbon economy, current and emerging best practices, and next steps, including climate change metrics, greenhouse gas reporting, effective climate policy, and long-term investment choices