Juan M. Morales

Short-Term Trading for a Wind Power Producer

This paper presents a technique to derive the best offering strategy for a wind power producer in an electricity market that includes various trading floors. Uncertainty pertaining to wind availability, market prices at the different trading stages, and balancing energy needs are properly taken into account. Risk on profit variability is suitably controlled at the cost of a small reduction in expected profit. The proposed technique translates into a linear programming problem of moderate size, which is readily solvable using commercially available software. A variety of numerical case studies demonstrate the interest and effectiveness of the proposed technique. Appropriate conclusions are duly drawn.

Scenario Reduction for Futures Market Trading in Electricity Markets

To make informed decisions in futures markets of electric energy, stochastic programming models are commonly used. Such models treat stochastic processes via a set of scenarios, which are plausible realizations throughout the decision-making horizon of the stochastic processes. The number of scenarios needed to accurately represent the uncertainty involved is generally large, which may render the associated stochastic programming problem intractable. Hence, scenario reduction techniques are needed to trim down the number of scenarios while keeping most of the stochastic information embedded in such scenarios. This paper proposes a novel scenario reduction procedure that advantageously compares with existing ones for electricity-market problems tackled via two-stage stochastic programming.

Simulating the Impact of Wind Production on Locational Marginal Prices

This paper analyzes the impact of wind production on the locational marginal prices of a fully competitive pool-based electricity market. Wind productions are modeled as negative loads and characterized by historical data records. The analysis pertains to the structural relationship between wind production and locational marginal prices, and disregards the collateral effect of strategic offering. The study presented allows a statistical characterization of locational marginal prices as a function of the statistical data of the wind plants and the structure of the considered electric energy system.

Pricing Electricity in Pools With Wind Producers

This paper considers an electricity pool that includes a significant number of wind producers and is cleared through a network-constrained auction, one day in advance and on an hourly basis. The hourly auction is formulated as a two-stage stochastic programming problem, where the first stage represents the clearing of the market and the second stage models the system operation under a number of plausible wind production realizations. This formulation co-optimizes energy and reserve, and allows deriving both pool energy prices and balancing energy prices. These prices result in both cost recovery for producers and revenue reconciliation. A case study of realistic size is used to illustrate the functioning of the proposed pricing scheme.

Pool Strategy of a Price-Maker Wind Power Producer

We consider the problem of a wind power producer trading energy in short-term electricity markets. The producer is a price-taker in the day-ahead market, but a price-maker in the balancing market, and aims at optimizing its expected revenues from these market floors. The problem is formulated as a mathematical program with equilibrium constraints (MPEC) and cast as a mixed-integer linear program (MILP), which can be solved employing off-the-shelf optimization software. The optimal bid is shown to deliver significantly improved performance compared to traditional bids such as the conditional mean or median forecast of wind power distribution. Finally, sensitivity analyses are carried out to assess the impact on the offering strategy of the producers penetration in the market, of the correlation between wind power production and residual system deviation, and of the shape of the forecast distribution of wind power production.

A Transmission-Cost-Based Model to Estimate the Amount of Market-Integrable Wind Resources

In the pursuit of the large-scale integration of wind power production, it is imperative to evaluate plausible frictions among the stochastic nature of wind generation, electricity markets, and the investments in transmission required to accommodate larger amounts of wind. If wind producers are made to share the expenses in transmission derived from their integration, they may see the doors of electricity markets closed for not being competitive enough. This paper presents a model to decide the amount of wind resources that are economically exploitable at a given location from a transmission-cost perspective. This model accounts for the uncertain character of wind by using a modeling framework based on stochastic optimization, simulates market barriers by means of a bi-level structure, and considers the financial risk of investments in transmission through the conditional value-at-risk. The major features of the proposed model, which is efficiently solved using Benders decomposition, are discussed through an illustrative example.

Tools for the Analysis and Design of Distributed Resources—Part III: Market Studies

This paper provides an overview of market issues related to the economic operation of an electric energy system with a high penetration of distributed energy resources. Models and tools to tackle these issues are discussed. A fully-fledged market structure of the pool type is considered. The analysis focuses on a particular distributed resource, wind power, the most economically successful renewable source.

Robust management of Combined Heat and Power systems via linear decision rules

The heat and power outputs of Combined Heat and Power (CHP) units are jointly constrained. Hence, the optimal management of systems including CHP units is a multi-commodity optimization problem. Problems of this type are stochastic, owing to the uncertainty inherent both in the demand for heat and in the electricity prices that owners of CHP units receive for the power they sell in the market. In this work, we model the management problem for a coupled heat-and-power system comprising CHP plants, units solely producing heat as well as heat storages. We propose a robust optimization model including unit commitment, day-ahead power and heat dispatch as well as real-time re-dispatch (recourse) variables. This model yields a solution that is feasible under any realization of the heat demand within a given uncertainty set. Optimal recourse functions for the real-time operation of the units are approximated via linear decision rules to guarantee both tractability and a correct representation of the dynamic aspects of the problem. Numerical results from an illustrative example confirm the value of the proposed approach.

Redefining the Merit Order of Stochastic Generation in Forward Markets

This letter proposes a new merit order for the dispatch of stochastic production in forward markets (e.g., day-ahead markets). The proposed merit order considers not only the marginal cost of the stochastic generating unit, which is often very low or zero, but also the projected cost of balancing its energy deviations during the real-time operation of the power system. We show, through an illustrative example, that the proposed merit order leads to increased market efficiency as the penetration of stochastic generation in the electricity market grows.

Electricity Pool Prices: Long-Term Uncertainty Characterization for Futures-Market Trading and Risk Management

This paper provides a procedure to forecast electricity pool prices one year ahead. A technique to generate pool price scenarios spanning one year into the future is also provided. The information obtained through the above methodology is crucial to make informed decisions in financial markets by electricity producers, retailers and consumers. The proposed forecasting procedure is based on classical time series models and in a novel manner uses as explicative variables the prices of financial market products. A realistic case study is analyzed and results are reported to show the efficaciousness of the methodology proposed. Finally, several relevant conclusions are duly drawn.