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

Survey Paper: A survey on the communication architectures in smart grid

Electricity market modeling trends

This paper considers stochastic programming models for decision-making under uncertainty in the context of electricity markets. It provides a brief overview of modeling and solution techniques within a mathematical programming framework. Tutorial as well as recent references are provided. This paper provides the guidelines for discussion in a panel session organized by the authors on "Decision Making under Uncertainty in Electricity Markets", scheduled for the IEEE PES 2006 General Meeting.

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Decision Making Under Uncertainty in Electricity Markets

Solar energy has experienced phenomenal growth in recent years due to both technological improvements resulting in cost reductions and government policies supportive of renewable energy development and utilization. This study analyzes the technical, economic and policy aspects of solar energy development and deployment. While the cost of solar energy has declined rapidly in the recent past, it still remains much higher than the cost of conventional energy technologies. Like other renewable energy technologies, solar energy benefits from fiscal and regulatory incentives, including tax credits and exemptions, feed-in-tariff, preferential interest rates, renewable portfolio standards and voluntary green power programs in many countries. The emerging carbon credit markets are expected to provide additional incentives to solar energy deployment; however, the scale of incentives provided by the existing carbon market instruments, such as, the Clean Development Mechanism of the Kyoto Protocol is limited. Despite the huge technical potential, the development and large scale deployment of solar energy technologies world-wide still has to overcome a number of technical, financial, regulatory and institutional barriers. The continuation of policy supports might be necessary for several decades to maintain and enhance the growth of solar energy in both developed and developing countries.

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Solar energy: Markets, economics and policies

This work presents a binary expansion (BE) solution approach to the problem of strategic bidding under uncertainty in short-term electricity markets. The BE scheme is used to transform the products of variables in the nonlinear bidding problem into a mixed integer linear programming formulation, which can be solved by commercially available computational systems. The BE scheme is applicable to pure price, pure quantity, or joint price/quantity bidding models. It is also possible to represent transmission networks, uncertainties (scenarios for price, quantity, plant availability, and load), financial instruments, capacity reinforcement decisions, and unit commitment. The application of the methodology is illustrated in case studies, with configurations derived from the 80-GW Brazilian system.

Strategic bidding under uncertainty: a binary expansion approach

This report assesses the potential of electricity contract auctions as a procurement option for the World Bank's client countries. It focuses on the role of auctions of electricity contracts designed to expand and retain existing generation capacity. It is not meant to be a 'how-to' manual. Rather, it highlights some major issues and options that need to be taken into account when a country considers moving towards competitive electricity procurement through the introduction of electricity auctions. Auctions have played an important role in the effort to match supply and demand. Ever since the 1990s, the use of long-term contract auctions to procure new generation capacity, notably from private sector suppliers, has garnered increased affection from investors, governments, and multilateral agencies in general, as a means to achieve a competitive and transparent procurement process while providing certainty of supply for the medium to long term. However, the liberalization of electricity markets and the move from single-buyer procurement models increased the nature of the challenge facing system planners in their efforts to ensure an adequate and secure supply of electricity in the future at the best price. While auctions as general propositions are a means to match supply with demand in a cost-effective manner, they can also be and have been used to meet a variety of goals.

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Electricity Auctions: An Overview of Efficient Practices

Time-of-use (ToU) electricity tariffs are currently employed or considered for implementation in many jurisdictions around the world. In ToU modalities, a set of different tariffs for different hours of the day and/or seasons of the year is defined at the beginning of a given horizon, and then kept constant until its end. While designing ToU tariffs, one of the most significant sources of uncertainty to be considered relates to price-elasticities of demand. We propose an approach for ToU tariff design based in quadratically constrained quadratic programming and stochastic optimization techniques, addressing these uncertainties and dealing with various aspects of tariff design from the point of view of the regulator/regulated utility.

Time-of-Use Tariff Design Under Uncertainty in Price-Elasticities of Electricity Demand: A Stochastic Optimization Approach

This work presents a new methodology for the allocation of transmission service cost among network users in energy markets. The proposed method is based on an optimization/game-theoretic framework (Aumann-Shapley) that retains the desirable properties of other existing methodologies such as the Average Participations Factors (APF) and Long Run Marginal Costs (LRMC). The approach is shown to be computationally feasible and presents desirable characteristics in terms of economic coherence and isonomy. Computational results are presented for the Brazilian power system and compared with those obtained by three other methodologies: LRMC, APF, and the current method adopted in Brazil.

An Aumann-Shapley Approach to Allocate Transmission Service Cost Among Network Users in Electricity Markets

In a competitive environment with bid-based markets, power generation companies desire to develop bidding strategies that maximize their revenue In this paper we ask: What approaches and methodologies have been used to model the bidding problem for hydro-electric producers? We present the problem's developments over time and, through reviewing different variants of the problem, progressively build to the case in which the agent is a price-maker hydro-electric producer In each variant of the bidding problem, we examine how the approaches used to solve it may or may not be applicable to other variants Last, for the price-maker hydro-electric producer's bidding problem, we recognize the most recent developments and illuminate a path for future efforts

Luiz Barroso

Papers

Strategic bidding under uncertainty: a binary expansion approach

Electricity Auctions: An Overview of Efficient Practices

Time-of-Use Tariff Design Under Uncertainty in Price-Elasticities of Electricity Demand: A Stochastic Optimization Approach

An Aumann-Shapley Approach to Allocate Transmission Service Cost Among Network Users in Electricity Markets

Optimal Bidding Strategies for Hydro-Electric Producers: A Literature Survey