Chilean Power System Research Articles

Bus Basis Model Applied to the Chilean Power System: A Detailed Look at Chilean Electric Demand

This paper presents a methodology to forecast electrical demand for the Chilean Electrical Power System considering a national, regional, district and bus spatial disaggregation. The methodology developed was based on different kinds of econometric models and end-use models to represent the massification of low carbon emission technologies such as electromobility, electric heating, electric water heating, and distributed generation. In addition, the methodology developed allows for the projection of the electric demand considering different kinds of clients as regulated and non-regulated clients, and different economic sectors. The model was applied to forecast the long-term electricity demand in Chile for the period 2022–2042 for 207 districts and 474 buses. The results include projections under the base case and low carbon scenarios, highlighting the significant influence of new technologies on future demand.

Data-driven optimization for seismic-resilient power network planning

Many regions of the planet are exposed to seismic hazards that can cause devastating consequences on power systems. Due to these systems’ crucial role, the evaluation and planning for their safe and reliable operation are paramount. This paper develops a novel data-driven optimization framework to assess the power network’s seismic resilience and plan cost-effective investments for its enhancement. Under a robust optimization scheme, an earthquake attacker–defender model finds the worst-case realization of random earthquake network contingencies within an uncertainty set defined with a large number of scenarios generated by state-of-the-art engineering methods. Moreover, data-driven stochastic-robust optimization is employed in a two-stage seismic-resilient power network planning model, leveraging multiple seismic sources’ distributional information. Transmission line expansions and siting and sizing of battery energy storage systems are decided in the first stage, while the second stage decides operational variables. Experiments on a 281-node Chilean power system provide insights for seismic-resilient planning and demonstrate the efficiency of the proposed approach.

Medium-term stochastic hydrothermal scheduling with short-term operational effects for large-scale power and water networks

The high integration of variable renewable sources in electric power systems entails a series of challenges inherent to their intrinsic variability. A critical challenge is to correctly value the water available in reservoirs in hydrothermal systems, considering the flexibility that it provides. In this context, this paper proposes a medium-term multistage stochastic optimization model for the hydrothermal scheduling problem solved with the stochastic dual dynamic programming algorithm. The proposed model includes operational constraints and simplified mathematical expressions of relevant operational effects that allow more informed assessment of the water value by considering, among others, the flexibility necessary for the operation of the system. In addition, the hydrological uncertainty in the model is represented by a vector autoregressive process, which allows capturing spatio-temporal correlations between the different hydro inflows. A calibration method for the simplified mathematical expressions of operational effects is also proposed, which allows a detailed short-term operational model to be correctly linked to the proposed medium-term linear model. Through extensive experiments for the Chilean power system, the results show that the difference between the expected operating costs of the proposed medium-term model, and the costs obtained through a detailed short-term operational model was only 0.1%, in contrast to the 9.3% difference obtained when a simpler base model is employed. This shows the effectiveness of the proposed approach. Further, this difference is also reflected in the estimation of the water value, which is critical in water shortage situations.

Unit Commitment Problem with Energy Storage Under Correlated Renewables Uncertainty

Unit Commitment Problem with Energy Storage Under Correlated Renewables Uncertainty” introduces a novel approach to address the challenges of renewable integration. The study acknowledges the growing variability and correlation in power availability due to renewable generation and proposes a day-ahead unit commitment (UC) problem formulation that incorporates energy storage and considers multistage correlated uncertainty. Using a variant of the stochastic dual dynamic programming (SDDP) method, which can handle temporal correlations effectively, the researchers solve the complex UC problem. Results obtained from the IEEE 118-bus system demonstrate the significant advantages of considering multistage uncertainty and correlations. Applying their approach to the Chilean power system, the researchers present superior UC solutions that adapt generation to changing uncertainty at a lower cost. Additionally, they propose a more efficient deterministic UC solution that outperforms current industry practices. These advancements promise to enhance the integration of renewable energy sources, enabling a more sustainable and environmentally friendly future.

Frequency and Inertial Response Analysis of Loads in The Chilean Power System

The integration of power electronics-interconnected generation systems to the grid has fostered a significant number of concerns on power system operations, particularly on the displacement of synchronous generators that leads to a reduction in the grid’s overall inertia and frequency response. These concerns have raised a significant amount of state-of-the-art mathematical proposals on how to estimate system inertia; however, the majority of the proposals do not differentiate generator inertia from load inertia. When inertia prediction for control room applications is required in real-time, the current state-of-the-art proposals use the inertia of generators as a proxy for a minimum, overall inertia estimate, counting the number of units committed in real-time and adding up their inertia. However, as dynamic conditions are becoming challenging with the integration of power electronics-interconnected generation systems, it is important to quantify the amount of inertia from the loads, for which the state-of-the-art proposals present very limited advancement, particularly in applications with real data. This work presents a set of recorded actual events in the Chilean power system to estimate the contribution of loads to inertia and frequency response to assess whether the loads have a significant role in frequency stability. The contribution of this work is as follows: first, reporting real data of a power system from the PMU and SCADA systems that are usually classified as not public; and, second, to derive a conclusion from the data to assess the role of loads in frequency stability in a real case.

Integration of high levels of electrolytic hydrogen production: Impact on power systems planning

The increasing interest in electrolytic hydrogen production using renewable electricity sources will require to adapt power systems to new electrical loads for hydrogen production and supply chains. Such high loads would impact the long-term planning and operation of power systems, as they need to balance the variability of renewable generation sources with electricity demand. This stresses the importance of characterizing the impact of incorporating hydrogen supply chains into power systems and planning accordingly. This study proposes a methodological framework to assess the integration and development of a national power system with electrolytic hydrogen production and supply chain. The framework is based on the well-known optimization tool for energy systems planning, Open Source Energy Modeling System (OSeMOSYS). For a detailed representation, a module was developed where demand side technologies – such as those associated to hydrogen supply chains – can provide operating reserves. As a case study, the integration of the Chilean power system with a hydrogen supply chain for exporting hydrogen between 2018 and 2050 was modeled. Among other findings, results indicate that an on-grid hydrogen supply chain would be more cost-effective than an off-grid one. However, the new electrical loads originated from such hydrogen supply chain would require additional generation capacity — primarily photovoltaic. Other generation capacities such as concentrated solar power, wind, and storage would experience significant variations in their investment requirements, compared to the off-grid hydrogen supply chain scenario. The study revealed that the coordinated operation of electrolyzers is crucial to the operational flexibility of the new electrical system.

Assessing flexibility for integrating renewable energies into carbon neutral multi-regional systems: The case of the Chilean power system

Reducing emissions from power systems requires enhancing the penetration of non-conventional renewable energy sources (NCRE) in the generation mix. However, such penetration requires high levels of operational flexibility in order to ensure an adequate balance between generation and demand. Concentrating solar power plants with thermal storage (CSP-TES) and battery energy storage systems (BESS) have shown to possess technical characteristics compatible with such high flexibility requirements. However, due to the high capital costs of these technologies, decision-makers must seek for cost-effective configurations and operation modes. This study presents the development of a methodological framework for designing the long-term transition of a multi-regional energy system towards a low carbon emission system. The sought system is characterized by a high penetration of NCRE, and the use of CSP-TES, BESS and electricity transmission settings for providing effective levels of operational flexibility. For this, the transformation of the Chilean electricity system between the years 2018–2050 is studied, using a tailored modification of the well-known OSeMOSYS optimization tool for energy systems planning. The main results indicate that by 2050, and considering a baseline scenario defined for 2016, for most of the scenarios studied the renewable electricity generation would be at least a 90 % and CO2 emissions would be 75 % lower. Furthermore, it is shown that providing operational flexibility to the system requires a mixed generation from hydroelectric reservoirs, CSP-TES plants, BESS, pumped-storage hydropower and natural gas generators. The obtained results allow planning the capacity and operation of CSP and BESS plants, which are adapted to the future flexibility requirements of the Chilean electric power system. Incentive policies like stimuli to growth BESS, would favor primarily the photovoltaic growth of the system at the expense of CSP-TES capacity, while CSP-TES growth incentives would maintain photovoltaic generation levels, but would decrease Wind and natural gas generation.

Data-Driven, Web-Based Parameter Identification for a Reduced-Order Model of the Chilean Power System

The current need for power-system control-room operational tools to increase real-time situational awareness has led to various proposals on data analytics algorithms to obtain operational information from SCADA and PMU power system networks. Most of the proposals are implemented in simulation, with reduced practical significance for system operators. This work proposes a web-based simple algorithm to identify the dynamic parameters of a reduced-order model of power system frequency dynamics that is implemented with industrial hardware on a PMU network in the Chilean power system. To demonstrate the applicability of the proposed tool, the algorithm is implemented in a web page with real-time monitoring of the frequency of the Chilean power system, so that utilities and academic institutions with access to PMU measurements can apply the proposed concepts regardless of the topology of the monitored system.

Optimization-based analysis of decarbonization pathways and flexibility requirements in highly renewable power systems

Several countries are adopting plans to reduce the contaminant emissions from the energy sector through renewable energy integration and restrictions on fossil fuel generation. This process poses important computational and methodological challenges on expansion planning modeling due to the operational details needed for a proper analysis. In this context, this paper develops a planning model including an effective representation of the operational aspects of the system to understand the key role of flexible resources under strong decarbonization processes in highly renewable power systems. A case study is developed for the Chilean power system, which is currently undergoing an ambitious coal phase-out process, including the analysis of a scenario that leads to a completely renewable generation mix. The results show that highly renewable generation mixes are feasible, but rely on an effective balance of the key flexibility attributes of the system including ramping, storage, and transmission capacities. Further, such balance allows for faster decarbonization goals to remain in a similar cost range, through the deployment of flexible capacity in earlier stages of the planning horizon.

Towards a complex investment evaluation framework for renewable energy systems: A 2-level heuristic approach

Renewable energy technologies still endure critical technical and financial challenges. These challenges demand for specially tailored decision support tools for planning the (renewable-based) strategical expansion of power systems. However, existing tools not always adequately integrate the tactical and operational dimensions of power systems into the evaluation process; hence, the designed investment strategies might fail to foresee how new infrastructure integrates with the existing power system and also fail to capture the volatile energy market dynamics. In this paper, this methodological gap is addressed by presenting a decision aid framework, based on mixed integer programming, for supporting long-term decision-making when planning (the expansion of existing) energy systems. The proposed framework relies on heuristically solving an optimization problem coined as the Generation, transmission and storage location and sizing of operation-aware sustainable power system design problem, which encodes two nested problems: a novel strategic renewable power system expansion problem, and a Unit Commitment problem. Using a case study from the Chilean power system, it is shown that the proposed tool ensures a more realistic and accurate economic evaluation, as it takes into account the influence of the evaluated project on the grid where it will be installed. In the considered case study, the devised framework designs a sustainable power system expansion investment strategy ensuring an investment rate of return of at least 7% and an annualized profit of more than 277 MM USD considering a 30 years evaluation horizon; furthermore, this is accomplished along with an equalization of the spot price resulting in a 13% reduction with respect to the current spot price of the system. This shows the impact of renewable sources and energy storage systems on the market operation. Furthermore, the proposed approach is used to investigate how high (public) subsidies on renewable technologies should be in order to increase the penetration of these technologies.

Economic and emission impacts of energy storage systems on power-system long-term expansion planning when considering multi-stage decision processes

Energy storage systems (ESS) are becoming a key component for power systems due to their capability to store energy generation surpluses and supply them whenever needed. However, adding ESS might eventually have unexpected long-term consequences and may not necessarily help in reducing CO2 emissions; mainly because they can store energy from any source and add some inefficiencies. Thus, it is important to accurately assess the impact they could have on the long-term prospects of the overall power system.In this work, those effects are assessed using a new adaptive two-stage generation, storage, and transmission expansion planning model, which includes constraints related to the system's flexibility, commonly disregarded in long-term expansion analysis. The effects of including an adaptive step in the proposed planning model, where investments can be adjusted to long-term demand trends, and those of including or ignoring ramp and reserve constraints are analyzed.The methodology is illustrated using a 45-bus representation of the Chilean power system. We use this case study to illustrate a counterexample where ESS can help reducing total system costs, but increasing CO2 emissions. We do not argue this would be mostly the case, but this counterexample helps to illustrate that this situation is possible. Likewise, we show that including the adaptive (two-step) approach significantly changes the generation and transmission expansion mix, as well as the emission levels. Finally, disregarding ramps does reduce total costs and slightly increases emissions in the Chilean case, but dismissing power reserves does not significantly affect the results.

Firewood heat electrification impacts in the Chilean power system

Chile presents an extended use of low-quality firewood for residential heating. This raises serious concerns, mainly related to health problems due to particulate emissions from firewood combustion. Several initiatives have been considered by the Chilean government to address this, including heat electrification goals. In addition, the Chilean power system is undergoing a decarbonization process. This paper analyzes the impacts of firewood heat electrification over the Chilean power system’s decarbonization process until 2044, based on a capacity expansion planning model and an estimation of firewood heat demand, to account for major changes in load shape and spatial distribution. The results show that there is a large increase in the power system total cost (ranging from 5.6% to 19.4%), with flexibility requirements becoming larger in the south. Technologies that strongly depend on local resource availability, such as wind and concentrated solar power, present changes in their systemic value, altering the need for storage and flexibility. Also, aspects such as household insulation, electrification efficiency, and smart heating technologies would significantly impact the process in terms of cost reduction and optimal generation mix. The policy implications for the Chilean power system are presented, within the broader discussion of the overall firewood problem.

Valuing flexibility in transmission expansion planning from the perspective of a social planner: A methodology and an application to the Chilean power system

We study the value of adding flexibility to Transmission Expansion Planning (TEP) projects from the perspective of a social planner using real options. Due to the deregulation of electricity markets, TEP projects currently face multiple uncertainties. These uncertainties often cause traditional project valuation methods to recommend sub-optimal investment decisions. Additionally, to incorporate the effects of uncertainties on the valuation of TEP projects, current literature rely on some critical simplifications that do not fit well with the real operations of a power market. This paper models the power market in a realistic way by combining an equilibrium model, to assess the power market equilibrium that the TEP project will generate, with a valuation model based on real options, to incorporate the value of flexibility. The methodology is applied to determine the value of adding capacity expansion flexibility to a portion of the rigid TEP project that connects the main two interconnected systems in Chile since 2018. Our results show that, in this case, adding flexibility increases the net expected social welfare by $14.03 million. Several sensitivity analyses confirm that this flexibility has more value when uncertainty is higher and/or investment costs are lower.

An Adaptive Robust Optimization Model for Power Systems Planning With Operational Uncertainty

There is an increasing necessity for new long-term planning models to adequately assess the flexibility requirements of significant levels of short-term operational uncertainty in power systems with large shares of variable renewable energy. In this context, this paper proposes an adaptive robust optimization model for the generation and transmission expansion planning problem. The proposed model has a two-stage structure that separates investment and operational decisions, over a given planning horizon. The key attribute of this model is the representation of daily operational uncertainty through the concept of representative days and the design of uncertainty sets that determine load and renewable power over such days. This setup allows an effective representation of the flexibility requirements of a system with large shares of variable renewable energy, and the consideration of a broad range of operational conditions. To efficiently solve the problem, the column and constraint generation method is employed. Extensive computational experiments on a 20-bus and a 149-bus representation of the Chilean power system over a 20-year horizon show the computational efficiency of the proposed approach, and the advantages as compared to a deterministic model with representative days, due to an effective spatial placement of both variable resources and flexible resources.

Power system expansion planning under global and local emission mitigation policies

This work analyzes the impacts on the power system expansion planning of implementing CO2 and local pollutant emission taxes under five different policy-relevant scenarios. To do this, we have formulated and implemented an optimization model based on a mixed-integer linear program, which determines the optimal expansion plan considering the installation of both large-scale power plants and renewable-based distributed generation. An important characteristic of the proposed model is that it includes a detailed formulation of the power system. Moreover, differently than existing literature, special attention is given to the analysis of the spatial-temporal distributive effects of pollutant taxes, considering both global and local pollutant emissions. The method is applied to the main Chilean power system. Our results indicate that global and local pollutant taxes significantly impact both planning and operational decisions in the power system. In particular, pollutant taxes may have significant spatial distributive effects, as shown in the analysis of 13 regions of Chile, leading to damages in some specific regions while relatively benefiting others. Our results also show that the availability of renewable energy capacity may improve the effectiveness of pollutant taxes. Particularly, adding 1.5 GW of hydro capacity to the Chilean system allows avoiding around 32 GWh of fossil fuel generation per year, saving more than 1.5 billion US$ in the 10-year horizon considered. The proposed method and qualitative results are sufficiently generic to apply to any other jurisdiction.

Effect of Climate Change on wind speed and its impact on optimal power system expansion planning: The case of Chile

This work assesses the changes in power capacity expansion decisions regarding power generation and transmission that occur when the effects of Climate Change on wind speed are captured in the decision model. Considering an 85-year period (2016–2101), we use a Mixed-Integer Linear Program (MILP) model to analyze the optimal power capacity expansion in diverse types of power generation technologies, throughout the years and geographical locations. The optimization model minimizes the total (investment and operational) costs of the power system subject to several technical and economic constraints. We implement our model using the main Chilean power system. We compare two scenarios: one assuming that Climate Change affects wind speeds and hence wind farm capacity factors and the other assuming it does not. Our results reveal that, when taking into account the impact of Climate Change on wind speed, the optimal power generation and transmission expansion plan is different than when ignoring this effect. The variation of wind speed affects not only wind power capacity installed, but also other-technology power capacity installed. In particular, power capacity installed in wind and solar generation plants is higher (measured in MW installed) than the power capacity installed when we ignore the effects of Climate Change; and power capacity installed in diesel and natural gas technologies are lower. We perform sensitivity analyses, changing power capacity expansion limits and the discount rate, to check for the robustness of our results.

Multi-objective planning of energy storage technologies for a fully renewable system: Implications for the main stakeholders in Chile

Energy storage systems can cost-effectively balance fluctuations from renewable generation. Also, hydropower dams can provide flexibility, but often cause massive fluctuations in flow releases (hydropeaking), deteriorating the ecology of the downstream rivers. Expanding transmission infrastructure is another flexibility source but is frequently plagued by social opposition and delays. As the decision-making process transcends costs, we developed a multi-objective framework to design a fully renewable power system, such that the tradeoffs between total costs, hydropeaking, and new transmission projects can be assessed from a multi-stakeholder perspective. We planned the Chilean power system for the year 2050 and, based on the obtained trade-off curves (Pareto), we identified the following implications for the different stakeholders. Avoiding new transmission generates little costs (avoiding 30%/100% of transmission costs < 1%/ > 3%), which is positive for planners but negative for transmission companies. Severe hydropeaking can be mitigated for about 1% of additional costs if transmission is deployed. Avoiding both hydropeaking and transmission is the most extreme scenario, costing 11%. The less the transmission and hydropeaking, the more solar and storage technologies are installed. Cheap solar and storage systems enable policymakers to cost-effectively limit hydropeaking and new transmission, which makes the system greener and more socially acceptable.

Cycling Impact Assessment of Renewable Energy Generation in the Costs of Conventional Generators

This paper proposes a set of indicators to quantify the impact of conventional thermal generating unit cycling on its non-fuel variable costs (NFVC) due to generation mix changes in the system. A novel iterative cost adjustment framework is developed to evaluate the proposed indicators in order to assess the impacts of increasing installation of renewable resources on operation costs of the thermal units. The proposed framework allows private investors to estimate NFVC using a minimum level of information without a full knowledge of the system parameters. Additionally, the proposed framework is kept generic, which supports the NFVC adjustment for the conventional thermal units in a changing market environment. The impact of accelerated solar photovoltaic penetration on cycling and operational costs of existing thermal power plants in the Chilean power system is assessed using the indicators and methodology developed. The results suggest that natural gas driven peaking power plants are more susceptible to experiencing increased NFVC from solar photovoltaic growth than coal fired base load power plants.

Special Protection Systems: Challenges in the Chilean Market in the Face of the Massive Integration of Solar Energy

Special protection schemes (SPSs) are an efficient alternative to increase the flexibility in the operation of power systems. The implementation of SPSs is often motivated by technical rather than economic reasons. The aim of this paper is to propose a novel framework for the analysis and development of SPSs in a context from the Chilean experience that comprises both technical and economic incentives to enable high penetration of solar energy. With this purpose, this paper explores the new capabilities of SPSs based on maximizing the cost-effective integration of solar power into a power system, given a set of technical challenges (congestion and dynamic response in case of contingencies) that must be considered in their design. In this framework, three main drivers were identified and discussed. The discussion includes the mechanisms associated with each driver that promote the massive integration of solar power. Moreover, within the proposed technical-economic framework, a methodology for driver selection and SPS design is proposed. The methodology and the drivers identified are evaluated in the Chilean power system.

Impact of network payment schemes on transmission expansion planning with variable renewable generation

A large number of studies have dealt with the Transmission Expansion Planning (TEP) problem. However, few investigations have focused on analyzing the impacts of network payment schemes on network configuration and the benefits/losses distribution among the participants in electricity markets. In this paper, we propose a multi-annual transmission expansion planning model considering four different network payment schemes to finance the construction of new transmission lines, seeking to reduce the total system costs. Wind and solar power generation are included in the model taking into account their variability. The proposed models are reformulated as Mixed Integer Linear Programming (MILP) problems. We use seven performance metrics related with congestion, nodal prices and generator benefits, among others, to evaluate the effect of each payment scheme. A realistic case study based on the main power system in Chile is analyzed to illustrate the proposed models. It is shown that integrating line cost-recovering equations into the TEP model may result into a more realistic and less congested power network. Also, total system cost is highly related with transmission tariff discrimination. In that way, tariffs with high location dependence perform better in the case studied, the Chilean power system.