Offering a unifying theoretical perspective not readily available in any other text, this innovative guide to econometrics uses simple geometrical arguments to develop students' intuitive understanding of basic and advanced topics, emphasizing throughout the practical applications of modern theory and nonlinear techniques of estimation. One theme of the text is the use of artificial regressions for estimation, reference, and specification testing of nonlinear models, including diagnostic tests for parameter constancy, serial correlation, heteroscedasticity, and other types of mis-specification. Explaining how estimates can be obtained and tests can be carried out, the authors go beyond a mere algebraic description to one that can be easily translated into the commands of a standard econometric software package. Covering an unprecedented range of problems with a consistent emphasis on those that arise in applied work, this accessible and coherent guide to the most vital topics in econometrics today is indispensable for advanced students of econometrics and students of statistics interested in regression and related topics. It will also suit practising econometricians who want to update their skills. Flexibly designed to accommodate a variety of course levels, it offers both complete coverage of the basic material and separate chapters on areas of specialized interest.

Estimation and Inference in Econometrics

A survey of index decomposition analysis in energy and environmental studies

This paper discusses conceptual frameworks for actively involving highly distributed loads in power system control actions. The context for load control is established by providing an overview of system control objectives, including economic dispatch, automatic generation control, and spinning reserve. The paper then reviews existing initiatives that seek to develop load control programs for the provision of power system services. We then discuss some of the challenges to achieving a load control scheme that balances device-level objectives with power system-level objectives. One of the central premises of the paper is that, in order to achieve full responsiveness, direct load control (as opposed to price response) is required to enable fast time scale, predictable control opportunities, especially for the provision of ancillary services such as regulation and contingency reserves. Centralized, hierarchical, and distributed control architectures are discussed along with benefits and disadvantages, especially in relation to integration with the legacy power system control architecture. Implications for the supporting communications infrastructure are also considered. Fully responsive load control is illustrated in the context of thermostatically controlled loads and plug-in electric vehicles.

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Achieving Controllability of Electric Loads

The smart grid concept continues to evolve and various methods have been developed to enhance the energy efficiency of the electricity infrastructure. Demand Response (DR) is considered as the most cost-effective and reliable solution for the smoothing of the demand curve, when the system is under stress. DR refers to a procedure that is applied to motivate changes in the customers' power consumption habits, in response to incentives regarding the electricity prices. In this paper, we provide a comprehensive review of various DR schemes and programs, based on the motivations offered to the consumers to participate in the program. We classify the proposed DR schemes according to their control mechanism, to the motivations offered to reduce the power consumption and to the DR decision variable. We also present various optimization models for the optimal control of the DR strategies that have been proposed so far. These models are also categorized, based on the target of the optimization procedure. The key aspects that should be considered in the optimization problem are the system's constraints and the computational complexity of the applied optimization algorithm.

A Survey on Demand Response Programs in Smart Grids: Pricing Methods and Optimization Algorithms

The UK Energy Research Centre (UKERC) has launched a major new report on how 'Rebound Effects' can result in energy savings falling short of expectations, thereby threatening the success of UK climate policy. 

An example of a rebound effect would be the driver who replaces a car with a fuel-efficient model, only to take advantage of its cheaper running costs to drive further and more often. Or a family that insulates their loft and puts the money saved on their heating bill towards an overseas holiday.

The rebound effect: an assessment of the evidence for economy-wide energy savings from improved energy efficiency

Consumer demand for ‘green power’ and energy efficiency

Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets

This paper sets forth a comprehensive theory for the real-time pricing of electricity that includes selected ancillary services and extends the theory to incorporate constraints on power quality and environment impact that often influence the operation of a power system. This paper is Part I of a two paper set. It sets forth the mathematical development of the extended model for real-time pricing. The formulation is novel in that it combines the dynamic equations for load-frequency control with the static equations of a constrained optimal power flow. Part II derives optimal nodal specific real-time prices for both real and reactive power. The prices derived include additive premia, or opportunity costs, reflecting the effects of voltage regulation, maintenance of generation and transmission reserves, regulation of frequency and tie-line flows, removal and/or control of power harmonics and others.

Advanced pricing in electrical systems. I. Theory

Part I of this paper set forth a mathematical formulation of a model for real-time pricing of electricity that included selected ancillary services and extended the theory to incorporate constraints on power quality and environment impact that often influence the operation of a power system. Derived herein are optimal real-time prices for both real and reactive power. The optimal prices are temporally and spatially differentiated. The prices derived include additive premia, or opportunity costs, reflecting the effects of voltage regulation, maintenance of generation and transmission reserves, regulation of frequency and tie-line flows, removal and/or control of power harmonics and others. This paper concludes with a discussion of the implications of the optimal prices for pricing of both retail and wholesale services.

Jay Zarnikau

Papers

Consumer demand for ‘green power’ and energy efficiency

Merit-order effects of renewable energy and price divergence in California’s day-ahead and real-time electricity markets

Advanced pricing in electrical systems. I. Theory

Advanced pricing in electrical systems. II. Implications

Demand participation in the restructured Electric Reliability Council of Texas market