Pablo Dueñas

A new approach to model load levels in electric power systems with high renewable penetration

In medium- and long-term power system models, it is a common approach to approximate the demand curve by load levels in order to make the models computationally tractable. However, in such an approach, the chronological information between individual hours is lost. In this paper, we propose a novel approach to power system models which constitutes an alternative to the traditional load levels. In particular, we introduce the concept of system states as opposed to load levels, which allows us to better incorporate chronological information in power system models, thereby resulting in a more accurate representation of system outcomes such as electricity prices and total cost. Moreover, the system states can be defined taking into account various important system features at once, as opposed to load levels which are defined using just one specific feature, i.e., demand or net demand. Therefore the system states approach better captures other results such as reserve prices, which are not driven by the usual feature used to define load levels. In a case study, we compare the newly proposed methodology to a standard load level approach, which validates that the system states approach better captures power system outcomes.

Electricity and Natural Gas Interdependency: Comparison of Two Methodologies for Coupling Large Market Models Within the European Regulatory Framework

Power generation growth based on natural gas fired power plants (NGFPPs) has lead to increasing interactions between electric power and natural gas industries. More companies are progressively and simultaneously participating as big players in both markets. However, each company has traditionally been settled in one side, holding a particular competitive advantage: electric power generation companies mainly know how to operate their generation assets, whereas gas companies mainly know how to manage their gas supply contracts and make use of often regulated gas assets. Multi-product energy companies have even created independent departments which decisions are usually taken uncoordinatedly. In any case, companies (or departments) usually support their decision-making process in mathematical tools which represent each market with detail. This paper presents two methodologies for coupling two interdependent electricity and gas market models formulated as optimization problems. Each methodology fulfills different department wishes. The “electricity-perspective” methodology maximizes electricity market profits after calculating equivalent gas contracts with the gas market model. In contrast, the “gas-perspective” methodology minimizes gas operation costs after obtaining the relationship between the marginal revenue and the gas consumption with the electricity market model. This coordinated solution would allow companies to obtain synergies, resulting in a competitive advantage over other companies that operate uncoordinatedly in both markets.

Gas–Electricity Coordination in Competitive Markets Under Renewable Energy Uncertainty

As climate concerns, low natural gas prices, and renewable technologies increase the electric power sectors dependence on natural gas-fired power plants, operational and investment models for gas and electric power systems will need to incorporate the interdependencies between these two systems to accurately capture the impacts of one on the other. Currently, few hybrid gas-electricity models exist. This paper reviews the state of the art for hybrid gas-electricity models and presents a new model and case study to illustrate a few potential coupling effects between gas and electric power systems. Specifically, the proposed model analyzes the optimal operation of gas-fired power plants in a competitive electricity market taking into consideration gas purchases, gas capacity contracting, and residual demand uncertainty for the generation company due to renewable energy sources.

Strategic Management of Multi-Year Natural Gas Contracts in Electricity Markets

Combined cycle gas turbine (CCGT) plants show some advantages, such as better economies of scale, or lower CO2 emission rates, in comparison to other technologies. In addition, due to their flexible operation, CCGT plants are a useful support for the integration of the growing renewable energy installed capacity. Consequently, during the last years, CCGT plants have proliferated in electricity systems, increasing the global demand of natural gas (NG). In order to guarantee the NG supply and to hedge the price volatility, electricity generation companies (Gencos) sign supply contracts with NG producers. Typically, NG producers force long-term contracts in order to recover their huge capital investments. Therefore, Gencos should optimize the exercise of the supply contracts in the long-term scope in order to maximize their profits in the electricity market. However, the optimal exercise of the supply contracts on behalf of the Gencos could be impeded because of possible bottlenecks in the NG system. Accordingly, this paper proposes a methodology to incorporate both the characteristics of NG supply contracts and the congestions in the NG system in an electricity market model that could support the decision-making process on behalf of the Gencos. A study case illustrates the methodology.

Dynamic Ramping Model Including Intraperiod Ramp-Rate Changes in Unit Commitment

The growing increase of renewable generation worldwide is posing new challenges for a secure, reliable, and economic operation of power systems. In order to face the uncertain and intermittent production of renewable sources, operating reserves must be allocated efficiently and accurately. Nowadays, these reserves are mainly assigned to thermal units, especially gas-fired generators, due to their operation flexibility and fast response. However, the ramping capabilities of these units define the grade of flexibility offered to the system operation. In practical applications, ramping limits are dynamic, i.e., they are a function of the units generating output. Omitting this feature leads to suboptimal or even infeasible reserve allocations, thus increasing not only operating reserve requirements but also transactions in real-time balancing markets needed to back up deviations of renewable generation. This paper contributes with a mixed-integer linear programming model for units’ dynamic ramping allowing intraperiod changes in the unit commitment problem. As a result, operating reserves are better allocated and the units’ flexibility is managed more efficiently than traditional ramping models found in the literature. Different case studies illustrate the functioning and benefits of the proposed formulation.

The interdependency of electricity and natural gaas markets: Coupling of models

The growth of power generation based on natural gas fired power plants (NGFPPs) in the recent years has lead to increasing interactions between electricity and natural gas systems, which can be used as a competitive advantage for an agent operating in both markets. Therefore, the larger is NGFPPs consumption the larger is the interdependence between electricity and natural gas systems, and the analysis of the integration of both systems becomes more necessary. The objective of this paper is to analyze economic interactions that can arise in the medium term when a company operates in both systems. Each system (electricity and natural gas) will be represented by an optimization model under perfect competition behavior. A method to couple both independent optimization models will be discussed.

A medium-term operation model for a natural gas system

During last decades, consumption of natural gas has been continuously increasing worldwide. Hence, infrastructure has been developed to transport the natural gas from the well to the final consumer. Natural gas chain value can be segmented in upstream and downstream sectors. The organization of the upstream sector is similar to that of the oil sector, whereas the organization of the downstream sector resembles much that of the electricity sector. The frontier between both sectors is usually placed in the international borders. Specifically, the operation model focuses on the downstream sector. The supply activity and the utilization of the different infrastructure such as the liquefied natural gas terminal or the storage facilities are considered. The upstream sector is not completely ignored as it is characterized in the supply activity. The operation model can be a support for taking decisions in the medium term on behalf of involved companies in the gas market as illustrated by the case study.

Closure to Discussion on “Gas-Electricity Coordination in Competitive Markets Under Renewable Energy Uncertainty”

As climate concerns, low natural gas prices, and renewable technologies increase the electric power sectors dependence on natural gas-fired power plants, operational and investment models for gas and electric power systems will need to incorporate the interdependencies between these two systems to accurately capture the impacts of one on the other. Currently, few hybrid gas-electricity models exist. This paper reviews the state of the art for hybrid gas-electricity models and presents a new model and case study to illustrate a few potential coupling effects between gas and electric power systems. Specifically, the proposed model analyzes the optimal operation of gas-fired power plants in a competitive electricity market taking into consideration gas purchases, gas capacity contracting, and residual demand uncertainty for the generation company due to renewable energy sources.

Analysis of an electricity market equilibrium model with Large-Scale penetration of Wind Energy

This paper presents an analysis of the behavior of an electricity market equilibrium model under a scenario with Large-Scale penetration of Wind Energy. The objective is to assess the robustness of this kind of models under the new context in which wind power is becoming increasingly important. In the model, different load level specifications are implemented as well as different scenarios of hydro conditions. The results show that the conjectural variation equilibrium model is robust to represent an electricity market with high penetration of wind energy.

An Optimization-Based Conjectured Response Approach to Medium-term Electricity Markets Simulation

Medium-term generation planning may be advantageously modeled through market equilibrium representation. There exist several methods to define and solve this kind of equilibrium. We focus on a particular technique based on conjectural variations. It is built on the idea that the equilibrium is equivalent to the solution of a quadratic minimization problem. We also show that this technique is suitable for complex system representation, including stochastic risk factors (i.e., hydro inflows) and network effects. We also elaborate on the use of the computed results for short-term operation.