Fco. Alberto Campos

Optimal Demand-Side Bidding Strategies in Electricity Spot Markets

This paper proposes a methodology for determining the optimal bidding strategy of a retailer who supplies electricity to end-users in the short-term electricity market. The aim is to minimize the cost of purchasing energy in the sequence of trading opportunities that provide the day-ahead and intraday markets. A genetic algorithm has been designed to optimize the parameters that define the best purchasing strategy. The proposed methodology has been tested using real data from the Spanish day-ahead and intraday markets over a period of two years with a significant cost reduction with respect to trading solely in the day-ahead market.

Connecting the Intraday Energy and Reserve Markets by an Optimal Redispatch

Electricity markets based on simple bids provide a very high degree of transparency and simplicity. However, simple bids fail to capture many well-known characteristics of generating units and, therefore, the responsibility for obtaining feasible schedules is transferred to market participants. The purpose of this paper is to help the generating utility to automatically analyze the last energy program cleared in the market and, in case this program is technically unfeasible, to provide an alternative schedule by re dispatching the generating units. This is achieved by formulating an optimization problem where the objective is to find the cheapest and feasible instantaneous power trajectory of each generator, trying to minimize the differences between its hourly average values and the last energy program. As the objectives of the utility can vary during the day, three different models are presented. Two of them are formulated as a joint energy and reserve dispatch in order to take into account possible commitments acquired in the ancillary services market of AGC regulation. In this sense, a novel approach for considering discontinuous ancillary regulation curves is proposed. Some numerical examples are included to illustrate the essential features of the models.

Hourly energy and reserve joint dispatch with a hydro-thermal technological based representation

Intermittent technologies are enhancing both the economic and technological value of ancillary services in the electric power system. Some of these services commonly denoted as reserves have been liberalized and are offered in the balancing markets in the European Union countries, or in the regulation markets in the USA. This paper presents a deterministic single-node centralized energy and secondary reserve dispatch that outputs hourly scheduled energies and reserves, and both commodities prices. In this model, units of each generation company are simplified into technologies and sub-technologies for faster performance, but still considering inter temporal constraints such as ramps and responding time for reserves, and unit commitment decisions such as start-up and shut-down costs. Detailed short-term hydro-thermal constraints (topology, efficiency, etc.) have been simplified by means of weekly constraints based on historical data (inflows, installed capacity, productions). The model has been validated by comparing its output prices and productions with the real ones occurred during 2010 in the Spanish market with satisfactory results. Furthermore, a study-case on high penetration of solar generation in the Spanish system reveals strong interactions between the energy and reserve markets and points out the importance of hydro technologies in the system.

Wind and solar integration with plug-in electric vehicles smart charging strategies

Combining large penetration of Plug-in Electric Vehicles (PEVs) and generation from Renewable Energy Sources (RES) seems a promising solution for energy cost saving and emission reduction. Indeed, RES generation increases instability grid problems due to its intermittency and lack of correlation with final energy usage. But the energy storage of the PEVs connected to the grid, controlled with smart charging and generating strategies, can compensate these uncertainties: energy surplus at low demands and high RES production (strong wind or sunshine) can be returned from PEVs to the grid at larger demand periods, and even provide regulation services. This paper analyses the combined impact of PEVs and RES penetration in the current Spanish power system with a detailed hydro-thermal Unit Commitment (UC) model for energy and reserve. Different charging strategies (from plug-and-charge to V2G with regulation) and wind and solar power penetration are tested with a full year simulation with weekly water management. Simulations show how PEVs smart charging strategies adapt PEVs operation to the existing generation structure, contributing efficiently to higher RES penetration rates, decreasing emissions and system operation costs.

Impact of plug-in-electric vehicles penetration on electricity demand, prices and thermal generation dispatch

This paper proposes an optimization model based on a centralized dispatch to analyze the impact of plug-in electric vehicles (PEV) penetration on the Spanish electricity demand and price. Different charging strategies, from the plug-and-charge strategy to the smartest vehicle-to-grid (V2G) capabilities, have been simulated and compared with the non PEV scenario, under different penetration values. Traditional generation resources have been represented with technical aspects such as ramps and minimum loads. Hydraulic resources management is also partially supported but limited to weekly management. Distribution network constraints and how they could limit the contribution of PEV to the grid services have been neglected. The model considers both load and reserve requirements to evaluate the PEV contribution to energy production or consumption, but also to secondary reserve regulation. Interesting results comparing the different simulation scenarios are discussed in the case examples.

Application Of Possibility Theory To Robust Cournot Equilibrium In The Electricity Market

It is known that Cournot game theory has been one of the theoretical approaches more used to model electricity market behavior. Nevertheless, this approach is highly influenced by the residual demand curves of the market agents, which are usually not precisely known. This imperfect information has normally been studied with probability theory, but possibility theory might sometimes be more helpful in modeling, not only uncertainty, but also imprecision and vagueness. In this paper, two dual approaches are proposed to compute a robust Cournot equilibrium, when the residual demand uncertainty is modeled with possibility distributions. Additionally, it is shown that these two approaches can be combined into a bicriteria programming model, which can be solved with an iterative algorithm. Some interesting results for a real-size electricity system show the robustness of the proposed methodology.

MORSE: Tools for long-term strategic analysis of the Spanish electricity sector

MORSE is a set of tools developed for the Spanish electrical utility Endesa, for long term simulation and strategic analysis of the Spanish electricity sector. MORSE has three different types of modules: forecasting modules, to model the main businesses of the sector, data preparation modules, to define the sector structure, to import data from other Endesa planning tools and to prepare it for the forecasting modules, and analysis and reports modules, to prepare simulation scenarios to be feed to the forecasting modules, execute them, and collect and organize their outputs in appropriate reports. The pool simulation model of the system, EQUITEC, is a Conjectured Supply Function Equilibrium, where generation companies are represented at a technology level, and conjectures are endogenously computed under hypothesis of local linearity near the equilibrium point. The inclusion in EQUITEC of network and zonal constraints is currently being analyzed.

Curve fitting with Mixed Integer Programming: Applications to electricity markets models

Long term electricity markets models tend to use simplified representations of both the demand and the generation units, to reduce the amount of input data and decision variables used, and also to decrease their execution times. On the one hand, hourly demand curves are usually simplified into a reduced set of non-chronological demand levels, each one representing hours with similar demand values. On the other hand, individual generation units are condensed into technologies grouping their costs curves by similarity in different appropriated technological cost mappings. This paper proposes several novel Mixed Integer Programming models to solve these two curve-fitting problems when the approximating function is a Piece-Wise Linear Function. By means of two real cases study it shows that the approximation approach has real applicability since it does not significantly compromise the traditional system representation.

Dynamics of Market Power in ERCOT System: A Fundamental CSFE With Network Constraints

Previous studies of market power within a regional system have considered multiple competing generation operators and the role of transmission constraints. However, these studies typically assume simplified structures in which each operator is restricted to a unique node in a transmission constrained network. Real systems typically have operators making decisions for units in several zones at once. Past studies also implicitly treated market power as a static concept for a given set of market rules and network configuration. We demonstrate that market power is dynamic, and can vary significantly with fuel prices and even with large-scale weather patterns. We also demonstrate the impact on region-wide market power of operators that manage units in multiple zones. We use the Electric Reliability Council of Texas (ERCOT) as an illustrative case study, and apply a conjectured supply function equilibrium (CSFE) approach that accounts for transmission constraints. We show that the companies with greater influence on the market price will depend on the relative prices of coal and natural gas. We also show that a weather event, such as a period without any wind, can have a substantial impact on market power.

Impact of the EU ETS on the European electricity sector

In the course of its first (2005-2007) and part of its second (2008-2010) trading periods the EU ETS has revealed insufficient tightness and some inefficiencies in the allocation mechanisms used. Recent amendments to the Emissions Trading Directive will start applying after 2013, such as a reinforced EU-wide emission cap and the end of free allowances for the power sector. Even under stricter rules, there is some uncertainty about the effectiveness of the EU ETS to reduce emissions from power generation in the near future with the available technologies. This paper studies the impact of different CO2 price scenarios on the operation of the European power system in 2015 for a given generation portfolio. A mid-term planning model assuming perfect competition and market splitting between countries is used. Results show how CO2 price impacts are limited to bring on emission reductions due to the existing technologies and cross-border transmission capacities.