Cristian A. Díaz

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.

Cost-benefit analysis of plug-in electric vehicles penetration

It is expected that in the near future the number of Plug-in Electric Vehicles (PEV) could increase significantly due to their low pollution emissions, high fuel economy, and mitigation of security issues related to oil technical and economic management. Many works have dealt with the impact of PEV on the power and distribution grids, and on other particular aspects, but very few perform more general cost benefit analyses of their global impact. This paper does it in two steps. First, a hydro-thermal unit commitment for a full year simulation provides electricity and reserve prices for different charging strategies. Then, the model computes economic estimations for the costs of the charging infrastructure, specific PEV costs and main externalities (emissions, health benefits and energetic dependence). The model is intended to provide meaningful results on the global economic balance of PEV penetration, helping for example in feed-in tariffs, fuel taxes redesign or other regulatory analyses.

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.

Short term constraints for a long term joint energy and reserve equilibrium

The increasing penetration of interruptible sources of energy is making security of supply a key aspect of present and future networks management, and reserves markets are gaining significant relevance. Demand representation used in traditional long term market models normally consists in a set of non chronological demand levels corresponding to hours with similar demand values. However, reserve issues are closely related with short term constraints (such as ramps), and this lack of chronological coupling does not allow for an appropriate representation of these technical constraints. This paper presents a joint energy and reserve conjectural equilibrium model that provides signal prices for both commodities and computes productions accordingly by satisfying system demand and reserve requirements. Generation is represented at a technological level, and water contributes to energy and reserve requirements with daily constraints. To reduce the feasible region, clustering is used to simplify hourly demand series into only a few daily patterns. In addition, keeping the link between hours and demand levels allows the model to combine short term technical constraints with traditional long term strategic planning constraints.

Two-zone electricity equilibrium computation with Mixed Integer Programming

Cross-border energy markets are becoming more relevant and line congestions may cause significant modifications in their underlined bidding strategies, increasing the market power. This environment requires the development of new tools to measure biased behaviors, and also to try to mitigate them. The related literature makes use of techniques to simulate the bidding strategies, mostly based in optimization models, with or without equilibrium constraints, or mixed complementary problems, and embedded in ad-hoc iterative procedures. This paper presents a model for a two areas system, assuming a conjectural equilibrium. A Mixed Integer Programming method has been implemented to solve the equilibrium conditions, where a binary variable is used to represent the lines power flow status (congested or not) between both two areas. Instead of an ad-hoc algorithm, the Branch and Bound algorithm is used for the resolution, which can assure convergence in specific situations where previous algorithms may diverge.

Estimation of the Spanish secondary reserves requirements

The increasing penetration of Intermittent Generation (IG) is being accompanied by the revision of the needs of traditional regulation reserves, as well as the discussion of new flexibility products for system balancing. In the context of electricity generation models, it is of high relevance to adequately represent, not only the energy, but also the reserve dispatch constraints, by providing the models with the expected secondary reserve requirements (SRR), so as to output more realistic energy and reserve schedules and prices. This paper analyses the SRR published by the Spanish System Operator and uses several forecasting tools for determining its main explanatory variables. Results confirm that the SRR have remained almost constant during the years of significant IG growth (and even slightly decreasing in the most recent years), and that the best SRR estimation models found use the demand and its inter-hour variations as the main explanatory variables, but not wind productions as could be expected.