Demand Shaping to Achieve Steady Electricity Consumption with Load Balancing in a Smart Grid

The purpose of this paper is to study conflicting objectives between the grid operator and consumers in a future smart grid. Traditionally, customers in electricity grids have different demand profiles and it is generally assumed that the grid has to match and satisfy the demand profiles of all its users. However, for system operators and electricity producers, it is usually most desirable, convenient and cost effective to keep electricity production at a constant rate. The temporal variability of electricity demand forces power generators, especially load following and peaking plants to constantly manipulate electricity production away from a steady operating point

Customer Engagement Plans for Peak Load Reduction in Residential Smart Grids

In this paper, we propose and study the effectiveness of customer engagement plans that clearly specify the amount of intervention in customer's load settings by the grid operator for peak load reduction. We suggest two different types of plans, including Constant Deviation Plans (CDPs) and Proportional Deviation Plans (PDPs). We define an adjustable reference temperature for both CDPs and PDPs to limit the output temperature of each thermostat load and to control the number of devices eligible to participate in Demand Response Program (DRP). We model thermostat loads as power throttling devices and design algorithms to evaluate the impact of power throttling states and plan parameters on peak load reduction. Based on the simulation results, we recommend PDPs to the customers of a residential community with variable thermostat set point preferences, while CDPs are suitable for customers with similar thermostat set point preferences. If thermostat loads have multiple power throttling states, customer engagement plans with less temperature deviations from thermostat set points are recommended. Contrary to classical ON/OFF control, higher temperature deviations are required to achieve similar amount of peak load reduction. Several other interesting tradeoffs and useful guidelines for designing mutually beneficial incentives for both the grid operator and customers can also be identified

Relationship of Risk Premium with Expected Volatility and Unexpected Volatility in Developing and Developed Economies

After application of ARIMA model to monthly risk premium and Threshold GARCH-In-Mean (TGARCH-M) models to daily risk premium of developed economies i.e. USA, UK, Germany, France and Canada and developing economies i.e. Pakistan, India, Malaysia and China over a period from January 2000 to December 2014, this study reported that in monthly data relationship between risk premium and expected volatility is negative in Pakistan: positive in Indonesia and Canada while insignificant in all other countries. The relationship between risk premium and unexpected volatility is negative in all the countries except Pakistan and China where it is insignificant while positive in USA. By the application of asymmetric volatility model on daily data for the same span, the relationship between risk premium and expected volatility is negative and significant in UK and France while this relationship is insignificant in all other countries. The study also indicates that the arrival of bad news has a greater impact on conditional volatility than the arrival of good news in all the economies whether developing or developed

Managerial Attributes Effect on Mutual Fund Performance: Case from Pakistan, an Emerging Mutual Fund Market

This paper investigates the effect of managerial attributes like, age of manager, qualification of manager, experience of manager, age of fund and management fee on performance of mutual funds. For this purpose open ended equity funds of 19 assets management companies with a data set ranging from 2010 to 2014 is taken. Fixed effect panel regression is used to control the unobserved heterogeneity between the assets management companies. Results reveal that managers qualification, age, total experience in mutual fund industry are positively and significantly related to performance of funds whereas, age of fund is negatively related to fund performance. Secondly, explanatory variable, management fee is not related to performance of mutual fund in Pakistan