Forecasting Feds Fund Rate: 1982-2014

Federal funds rate in the US is the interest rate that the banks pay each other for lending funds overnight. Fed funds rate is an important benchmark in the economy because of its significant impact on many other financial indices. The target rate is determined by Federal Open Market Committee (FOMC). Federal Reserve’s method of determining “reaction function” is subject to speculation for a long time. Taylor believed that the reaction function can be specified as a weighted average of deviations of inflation and unemployment from target values. But this model, even though worked for a long time, are under attack by new economists and like many old models are obsolete because of the various structural change in the society and economy. In this work, different models and different parameters are used to determine the reaction function. According to the results, VAR model gives the best FERMS (5.7%). Another interesting observation is that the inflation rate does not granger-cause Feds fund target rate which is not consistent with Taylor rule. On the other hand, the unemployment rate plays an important role in the Feds reaction function

Forecasting Feds Fund Rate: 1982-2014

Federal funds rate in the US is the interest rate that the banks pay each other for lending funds overnight. Fed funds rate is an important benchmark in the economy because of its significant impact on many other financial indices. The target rate is determined by Federal Open Market Committee (FOMC). Federal Reserve’s method of determining “reaction function” is subject to speculation for a long time. Taylor believed that the reaction function can be specified as a weighted average of deviations of inflation and unemployment from target values. But this model, even though worked for a long time, are under attack by new economists and like many old models are obsolete because of the various structural change in the society and economy. In this work, different models and different parameters are used to determine the reaction function. According to the results, VAR model gives the best FERMS (5.7%). Another interesting observation is that the inflation rate does not granger-cause Feds fund target rate which is not consistent with Taylor rule. On the other hand, the unemployment rate plays an important role in the Feds reaction function

An Investigation of Areva Inc. Huge Financial Loss in the Aftermath of Fukushima Nuclear Disaster

Areva is a French multinational company, mainly known for its nuclear power activities. This Company is active in all parts of value chain of nuclear energy. After Fukushima disaster, this company faced a huge financial loss. This study investigates the reasons for the loss and how Areva could manage the loss better. Diversification, increasing the flexibility of its human resource management, not taking any unsafe bet after 2008 vulnerable global market, adopting more realistic and risk-averse approach for estimation of the cost of its nuclear projects are suggested as a preventive and corrective measures

An Investigation of Evergreen Solar Inc. Bankruptcy by Considering Financial and Engineering Facets

In this paper, a company, Evergreen Solar Inc., located in Massachusetts, which was manufacturing solar panels for the photovoltaics industry is investigated. The company filed for bankruptcy on year 2011, closed its factory in Massachusetts and relocated manufacturing to China. In this paper, first, an introduction to solar energy will be provided. A history of the company then will be discussed. Finally, by considering the company’s financial data, the market and industry involved as well as engineering aspects, the major reasons for the aforesaid bankruptcy will be examined

Integration of Energy Storage and Distributed Generation (DG) in Distribution Systems: Economic Analysis and Development Perspective

This paper sheds light on distributed generation (DG) and energy storage and their impacts on electricity distribution networks. The purpose is to consider the various technologies of DG and energy storage and their financial and dynamic influence on the distribution network performance. In this paper, some different business cases in the U.S. related to energy storage and DG are investigated. One of these cases is related to Hawaiian Electric CO. One of the goals of Hawaiian Electric Co. for 2030 is to provide at least 65 percent of its electricity from renewable resources and working on providing sufficient energy storage. The company is considering energy storage project proposals on Oahu in order to provide their services by 2017. The paper will provide a look inside the company and how they are managing their existing projects and their future plans

An Investigation of Areva Inc. Huge Financial Loss in the Aftermath of Fukushima Nuclear Disaster

Areva is a French multinational company, mainly known for its nuclear power activities. This Company is active in all parts of value chain of nuclear energy. After Fukushima disaster, this company faced a huge financial loss. This study investigates the reasons for the loss and how Areva could manage the loss better. Diversification, increasing the flexibility of its human resource management, not taking any unsafe bet after 2008 vulnerable global market, adopting more realistic and risk-averse approach for estimation of the cost of its nuclear projects are suggested as a preventive and corrective measures

Integration of Energy Storage and Distributed Generation (DG) in Distribution Systems: Economic Analysis and Development Perspective

This paper sheds light on distributed generation (DG) and energy storage and their impacts on electricity distribution networks. The purpose is to consider the various technologies of DG and energy storage and their financial and dynamic influence on the distribution network performance. In this paper, some different business cases in the U.S. related to energy storage and DG are investigated. One of these cases is related to Hawaiian Electric CO. One of the goals of Hawaiian Electric Co. for 2030 is to provide at least 65 percent of its electricity from renewable resources and working on providing sufficient energy storage. The company is considering energy storage project proposals on Oahu in order to provide their services by 2017. The paper will provide a look inside the company and how they are managing their existing projects and their future plans

A novel tool for the evaluation and assessment of demand response activities in the industrial sector

This paper introduces a novel tool for industrial customers to perform a cost-benefit analysis regarding the implementation of Demand Response (DR) strategies in their facilities with the final goal of softening the impact of RES intermittency in the grid. The dynamic simulation tool focuses on assessing the participation of industries in reserve energy markets in the same conditions as generators offering capacity reserve, energy reserve or both of them and taking into account all the technical restrictions of production processes as well as possible extra costs due to the implementation of DR (additional labour cost, productivity losses, etc.) Main innovations of the methodology are the DR assessment carried out per process and the introduction of the margin of decision as a decision making strategy for the energy consumer. Along the paper, the methodology behind this tool is introduced step by step in order to show how the technical, economic and environmental analyses are performed. At the end, it is included the application of the methodology to a real paper factory in Germany. Results of the dynamic simulation tool are provided and discussed, showing the potential of the paper manufacturing in DR programmes as well as the benefits associated to it.This work was completed in the framework of the DRIP project (11ENV/DE/340) co-funded by the European Commission through the LIFE Environment Programme. The authors deeply thank all the participants in the project for their help and support that made possible this work.Rodríguez-García, J.; Álvarez, C.; Carbonell-Carretero, J.; Alcázar-Ortega, M.; Peñalvo López, E. (2016). A novel tool for the evaluation and assessment of demand response activities in the industrial sector. Energy. 113:1136-1146. doi:10.1016/j.energy.2016.07.146S1136114611

Correlation between predictability index and the error performance of customer baseline load (CBL) calculation Correlation Between Predictability index and the Error Performance of Customer Baseline Load (CBL) Calculation

This paper attempts to explore the correlation between the content of high frequency component of customers' historical consumption data (measured by a proposed index called predictability index) and the accuracy of Customer Baseline Load (CBL) calculation methods. In this paper, the customer's consumption signal is transformed from timedomain to frequency domain to separate the high and low frequency components of the consumption signal. Then, after reconstructing the time-domain equivalent of both of these signals, the predictability index for all customers are calculated. The data employed by this study belong to Australian Energy Market Operation (AEMO), and is the hourly Abstract-This paper attempts to explore the correlation between the content of high frequency component of customers' historical consumption data (measure by a proposed index called predictability index) and the accuracy of Customer Baseline Load (CBL) calculation methods. In this paper, the customer's consumption signal is transformed from time-domain to frequency domain to separate the high and low frequency components of the consumption signal. Then, after reconstructing the time-domain equivalent of both of these signals, the predictability index for all customers are calculated. The data employed by this study belong to Australian Energy Market Operation (AEMO), and is the hourly consumption of 189 customers for the time span of a year (2012). This index is proposed to be used for the purpose of clustering the customers into different bins by K-means clustering algorithm. Then the CBL for customers of each bin is calculated by two methods of CAISO and Randomized Controlled Trial (RCT), and then the average error in each bin is computed. Afterwards, the correlation between the average P index of each bin, and its normalized average error is calculated. It is found that there is a strong correlation between the P index and the error performance of the CBL calculation methods