Optimizing Dispatch Strategies for CSP Plants: A Monte Carlo Simulation Approach to Maximize Annual Revenue in Chile's Renewable Energy Sector
Year: 2026
Type: dissertation
Abstract: Chile’s abundant solar resources, particularly in the Atacama Desert, present an unparalleled opportunity for large-scale renewable power generation. Among the various solar technologies available, Concentrated Solar Power (CSP) offers distinct advantages by coupling high-efficiency solar collection with thermal energy storage (TES), enabling the dispatch of electricity when demand and market prices are most favorable. This doctoral research focuses exclusively on optimizing CSP plant dispatch strategies through a rigorous Monte Carlo simulation framework, aiming to maximize annual revenues while reinforcing grid stability and mitigating curtailment risks. The study is grounded in Chile’s broader goals under Energy Policy 2050, which seeks a significant penetration of renewables in the national energy mix. By centering on CSP, this work addresses crucial barriers to widespread solar adoption—namely, intermittency, limited dispatch flexibility, and potential financial uncertainty for plant operators. At the heart of this investigation is a 100 MW CSP facility strategically located in the Atacama Desert to harness consistently high solar irradiance. The methodology integrates real-world market data, solar resource profiles, and detailed power system constraints into a stochastic Monte Carlo model. This approach captures the inherent variability of both solar input and electricity prices, allowing for a comprehensive exploration of diverse dispatch scenarios. By systematically varying storage charge–discharge schedules, ramp rates, and operational constraints, the model identifies revenue-maximizing configurations, revealing how storage can be leveraged to shift power production to peak-price intervals. Such flexibility is especially critical in Chile’s evolving electricity market, where occasional oversupply from other renewable sources can lead to sharp price drops and heightened curtailment risk. Central to the simulation’s design is the concept of iterative dispatch optimization. Each Monte Carlo run incorporates potential fluctuations in market prices, seasonal solar irradiation, and policy-driven remuneration mechanisms (e.g., capacity payments or ancillary services). Over numerous iterations, the model converges on a probability distribution of possible revenue outcomes, highlighting the significance of adaptive strategies that account for uncertainty. The results conclusively demonstrate that advanced dispatch algorithms can substantially enhance profitability—by over 100% compared to less sophisticated, fixed-schedule approaches—while simultaneously supporting grid balance. These optimized strategies mitigate the need for forced curtailments by aligning CSP output with demand peaks, illustrating that CSP operators can be valuable partners for system operators seeking flexibility and stability. Beyond the quantitative findings, this research offers actionable policy recommendations. It underscores the value of granting CSP producers greater dispatch autonomy and incorporating real-time market signals into power purchase agreements. Such measures incentivize investment in thermal storage, as plant operators can better capture high-value intervals and avoid selling electricity into low-price or negatively priced periods. The thesis further argues that this economic rationale enhances the bankability of CSP projects, attracting investors who might otherwise favor more established renewable technologies. By improving the financial appeal of CSP, Chile can accelerate its transition toward a cleaner, more resilient energy portfolio—an imperative given the dual challenges of rising demand and the global push for carbon-neutral power. In conclusion, this doctoral work provides a robust, data-driven roadmap for maximizing CSP plant revenues within Chile’s dynamic market conditions. Through Monte Carlo-based dispatch optimization, it not only validates the viability of CSP technology as a key player in the nation’s energy future but also advances broader discussions on how to integrate high-penetration renewables while safeguarding economic returns and grid reliability.
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7160365254
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