GivEn -- Shape Optimization for Gas Turbines in Volatile Energy Networks

This paper describes the project GivEn that develops a novel multicriteria optimization process for gas turbine blades and vanes using modern "adjoint" shape optimization algorithms. Given the many start and shut-down processes of gas power plants in volatile energy grids, besides optimizing gas turbine geometries for efficiency, the durability understood as minimization of the probability of failure is a design objective of increasing importance. We also describe the underlying coupling structure of the multiphysical simulations and use modern, gradient based multicriteria optimization procedures to enhance the exploration of Pareto-optimal solutions

Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: A review

With the privatization and intense competition that characterize the volatile energy sector, the gas turbine industry currently faces new challenges of increasing operational flexibility, reducing operating costs, improving reliability and availability while mitigating the environmental impact. In this complex, changing sector, the gas turbine community could address a set of these challenges by further development of high fidelity, more accurate and computationally efficient engine health assessment, diagnostic and prognostic systems. Recent studies have shown that engine gas-path performance monitoring still remains the cornerstone for making informed decisions in operation and maintenance of gas turbines. This paper offers a systematic review of recently developed engine performance monitoring, diagnostic and prognostic techniques. The inception of performance monitoring and its evolution over time, techniques used to establish a high-quality dataset using engine model performance adaptation, and effects of computationally intelligent techniques on promoting the implementation of engine fault diagnosis are reviewed. Moreover, recent developments in prognostics techniques designed to enhance the maintenance decision-making scheme and main causes of gas turbine performance deterioration are discussed to facilitate the fault identification module. The article aims to organize, evaluate and identify patterns and trends in the literature as well as recognize research gaps and recommend new research areas in the field of gas turbine performance-based monitoring. The presented insightful concepts provide experts, students or novice researchers and decision-makers working in the area of gas turbine engines with the state of the art for performance-based condition monitoring

Combined heat and power plant flexibility - Technical and economic potential and system interaction

The share of variable renewable energy sources in electricity generation systems is expected to increase, leading to increased variability in the load that must be provided by conventional power plants or other flexibility measures. Thus, thermal power plants need to consider implementation of technical measures that enhance flexibility; to maintain profitability of operation with increased electricity price fluctuation, and to support electricity system stability. This thesis investigates the technical and economic potential for flexible operation of combined heat and power plants that deliver heat to district heating networks; in current and future Swedish energy system scenarios with varying levels of electricity price volatility. A modeling framework is developed to analyze static, dynamic, technical and economic aspects of flexible combined heat and power operation; comprising steady-state and dynamic process simulation models that are validated with reference plant measurements; and dispatch optimization models. Based on the designs of a waste-fired and a gas turbine combined cycle reference plant, two options to enhance the plant operational flexibility are analyzed: 1) product flexibility; i.e. operating the steam cycle with varying product ratios of electricity, heat and frequency response; 2) thermal flexibility, allowing the heat production to be shifted in time.The results show that flexible operation, for variable electricity generation, is technically feasible in both plant types. Operation with product and/or thermal flexibility can increase the annual plant revenue with up to 90 k€/MW by reduced fuel consumption or increased full load hours. The economic impact of increased ramp rate (operational flexibility) is marginal (<6 k€/MW). The value, and utilization, of flexibility enhancing measures increase with electricity price volatility, that benefits plants with a wide load span for electricity generation and motivates a shift in operating strategy from the traditional heat-following production planning to electricity-following operation

Electricity price forecasting utilizing machine learning in MIBEL

Short term electricity price forecasts have become increasingly important in the last few decades due to the rise of more competitive electricity markets throughout the globe. Accurate forecasts are now essential for market players to maximize their profits and hedge against risk, hence various forecasting methodologies have been applied to electricity price forecasting in the last few decades. This dissertation explores the main methodologies and how accurately can three popular machine learning models, SVR LSTM and XGBoost, predict prices in the Iberian market of electricity. Additionally, a study on input variables and their relationship with the final price is made

Modelling of national and local interactions between heat and electricity networks in low-carbon energy systems

Decarbonisation of the heating and cooling sector is critical for achieving long-term energy and climate change objectives. Closer integration between heating/cooling and electricity systems can provide additional flexibility required to support the integration of variable renewables and other low-carbon energy sources. This paper proposes a framework for identifying cost-efficient solutions for supplying district heating systems within both operation and investment timescales, while considering local and national-level interactions between heat and electricity infrastructures. The proposed optimisation model minimises the levelised cost of a portfolio of heating technologies, and in particular Combined Heat and Power (CHP) and polygeneration systems, centralised heat pumps (HPs), centralised boilers and thermal energy storage (TES). A number of illustrative case studies are presented, quantifying the impact of renewable penetration, electricity price volatility, local grid constraints and local emission targets on optimal planning and operation of heat production assets. The sensitivity analysis demonstrates that the cost-optimal TES capacity could increase by 41–134% in order to manage a constraint in the local electricity grid, while in systems with higher RES penetration reflected in higher electricity price volatility it may be optimal to increase the TES capacity by 50–66% compared to constant prices, allowing centralised electric HP technologies to divert excess electricity produced by intermittent renewable generators to the heating sector. This confirms the importance of reflecting the whole-system value of heating technologies in the underlying cost-benefit analysis of heat networks