Advanced control of renewable energy microgrids with hybrid energy storage system

Renewable energy will play an important role in the transition to a new energetic model which, along with other developments of the digital age, will probably bring about the Third Industrial Revolution. However, the change to this new energetic model is subject to overcoming technological barriers, namely the sporadic nature of renewable sources. Which in turn affects both, power quality and economic competitiveness. The imbalance of active and reactive power that renewable energies introduce in the grid causes variation in the voltage supply, grid frequency, harmonics, as well as producing other power quality issues. Energy storage systems appear to be a key factor in compensating generation and demand. The lack of controllability and the penalty for deviations in the regulation market hinder the economic competitiveness of renewable energy. Energy storage systems will be the technological solution enabling controllability in renewable energies, allowing their introduction in the spot energy market. Redesigning the grid into smaller, more manageable units based on microgrids appears as a solution to the outlined problems. In these microgrids, stored energy compensates both the intermittent nature of renewable generation and the randomness of the consumer's behaviour. Traditionally, energy storage has been developed by large hydropower-regulation plants, however, these kinds of plants are subject to natural emplacements and their implementation is subject to environmental impact grades. The high energy density of hydrogen as an energy carrier will play an important role in this new energetic paradigm. However, robust performance and the transient response are the main barriers for its technological implantation and, usually, hydrogen-based systems have a useful life that is sometimes too limited to buffer the associated cost. Batteries and supercapacitors have a better transient response, however, their low energy density does not provide enough autonomy to the system. The design of a hybrid energy storage system, having advanced control systems in charge of taking advantage of each storage system and avoiding the causes of degradation and/or limitations of them, emerges as a technological solution to the problems commented. The high number of constraints and variables to be optimized increases the complexity of the associated control problem, making it necessary to deploy advanced control algorithms. In this thesis, the development of optimal controllers for renewable energy microgrids with hybrid energy storage systems is explored using Model Predictive Control (MPC). The control system is introduction on different time scales resulting in an optimal control solution for the economic dispatch and the power quality of the microgrid. Meanwhile, degradation issues of energy storage systems are analyzed and minimized, improving the longevity of the whole energy storage system

Development of technical economic analysis for optimal sizing of a hybrid power system: a case study of an industrial site in Tlemcen Algeria

The current study aimed to develop an optimal sizing simulation model for an off-grid photovoltaic-wind hybrid power system of an industrial site in Algeria. The loss of power supply probability algorithm was used for sizing our hybrid system. The technical and economic evaluation for the case study showed that the storage system occupied the most critical part of the total investment cost of the hybrid system. The investment cost analysis indicated a unique optimal configuration for each size of the batteries bank. For one day's autonomy, the best size of the hybrid system corresponded to 61 PV panels and 9 wind turbines. Based on a levelized cost of energy analysis, the cost of the batteries represented for this combination is 52% of the total investment cost. The wind turbines accounted for 42% and the PV panels for only 3%. This combination of the hybrid system resulted in an energy cost that was very competitive with most European countries. However, the public energy grid cost in the case study region was still six times lower due to government subsidies. The findings are very encouraging and can help decision-makers adopt alternative and more sustainable solutions in energy policy. These results will aid in determining future research directions in Algeria's hybrid renewable energy systems.National funds funded Luís Frölén Ribeiro through FCT - Fundação para a Ciência e Tecnologia, through project UIDB/50022/2020 – LAETAinfo:eu-repo/semantics/publishedVersio

THE STABILITY ANALYSIS FOR WIND TURBINES WITH DOUBLY FED INDUCTION GENERATORS

The quickly increasing, widespread use of wind generation around the world reduces carbon emissions, decreases the effects of global warming, and lowers dependence on fossil fuels. However, the growing penetration of wind power requires more effort to maintain power systems stability. This dissertation focuses on developing a novel algorithm which dynamically optimizes the proportional-integral (PI) controllers of a doubly fed induction generator (DFIG) driven by a wind turbine to increase the transient performance based on small signal stability analysis. Firstly, the impact of wind generation is introduced. The stability of power systems with wind generation is described, including the different wind generator technologies, and the challenges in high wind penetration conditions. Secondly, the small signal stability analysis model of wind turbines with DFIG is developed, including detailed rotor/grid side converter models, and the interface with the power grid. Thirdly, Particle swarm optimization (PSO) is selected to off-line calculate the optimal parameters of DFIG PI gains to maximize the damping ratios of system eigenvalues in different wind speeds. Based on the historical data, the artificial neural networks (ANNs) are designed, trained, and have the ability to quickly forecast the optimal parameters. The ANN controllers are designed to dynamically adjust PI gains online. Finally, system studies have been provided for a single machine connected to an infinite bus system (SMIB), a single machine connected to a weak grid (SMWG), and a multi machine system (MMS), respectively. A detailed analysis for MMS with different wind penetration levels has been shown according to grid code. Moreover, voltage stability improvement and grid loss reduction in IEEE 34-bus distribution system, including WT-DFIG under unbalanced heavy loading conditions, are investigated. The simulation results show the algorithm can greatly reduce low frequency oscillations and improve transient performance of DFIGs system. It realizes off-line optimization of MMS, online forecasts the optimal PI gains, and adaptively adjusts PI gains. The results also provide some useful conclusions and explorations for wind generation design, operations, and connection to the power grid. Advisors: Sohrab Asgarpoor and Wei Qia

THE STABILITY ANALYSIS FOR WIND TURBINES WITH DOUBLY FED INDUCTION GENERATORS

The quickly increasing, widespread use of wind generation around the world reduces carbon emissions, decreases the effects of global warming, and lowers dependence on fossil fuels. However, the growing penetration of wind power requires more effort to maintain power systems stability. This dissertation focuses on developing a novel algorithm which dynamically optimizes the proportional-integral (PI) controllers of a doubly fed induction generator (DFIG) driven by a wind turbine to increase the transient performance based on small signal stability analysis. Firstly, the impact of wind generation is introduced. The stability of power systems with wind generation is described, including the different wind generator technologies, and the challenges in high wind penetration conditions. Secondly, the small signal stability analysis model of wind turbines with DFIG is developed, including detailed rotor/grid side converter models, and the interface with the power grid. Thirdly, Particle swarm optimization (PSO) is selected to off-line calculate the optimal parameters of DFIG PI gains to maximize the damping ratios of system eigenvalues in different wind speeds. Based on the historical data, the artificial neural networks (ANNs) are designed, trained, and have the ability to quickly forecast the optimal parameters. The ANN controllers are designed to dynamically adjust PI gains online. Finally, system studies have been provided for a single machine connected to an infinite bus system (SMIB), a single machine connected to a weak grid (SMWG), and a multi machine system (MMS), respectively. A detailed analysis for MMS with different wind penetration levels has been shown according to grid code. Moreover, voltage stability improvement and grid loss reduction in IEEE 34-bus distribution system, including WT-DFIG under unbalanced heavy loading conditions, are investigated. The simulation results show the algorithm can greatly reduce low frequency oscillations and improve transient performance of DFIGs system. It realizes off-line optimization of MMS, online forecasts the optimal PI gains, and adaptively adjusts PI gains. The results also provide some useful conclusions and explorations for wind generation design, operations, and connection to the power grid. Advisors: Sohrab Asgarpoor and Wei Qia

OPTIMIZING THE USE OF ENERGY STORAGE AS A DEMAND RESPONSE TOOL

The renewable energies expansion over last years, due to the need to bring electricity production towards ever higher levels of green production and the increase of the demand, have brought further stability problems to the main grid. The handling of the integration of these alternative sources and the optimization of the electricity grid have given high attention on the role of demand response program as a key part for the target. The combination of battery storage units with real-time prices is part of the research effort that aims to reduce the instability of the grid and the energy costs of the users. Literature shows good potential for the control strategies as the relative wide range of technologies developed recently for the scope, even if for the residential customers usually the potential is constrained by the limited controllable loads and their significant share of consumption. However, the aspect of user comfort is not always fully considered leading to less realistic conclusions. The objective of the work described in the dissertation was then to obtain a reduction in residential energy costs through the optimal scheduling of user appliances supported by the use of battery storage, under a real-time price scheme, while limiting the discomfort for the customer. Although the first results of applying a real time pricing scheme based on the current variations in price observed in the Iberian wholesale market led only to small profits when not considering additional self-generation, they increased significantly if a small photovoltaic based production is considered, and reached significant cost savings (circa 70%) in periods of high solar generation. But, when applying a real time price following the fluctuations of the renewable energy supply, which produced much higher variations in price, the results improved considerably, reaching cost savings as high as 85%. The implemented model shows the true relevance of Demand Response and Energy Storage, producing meaningful savings if the supply costs change with the availability of renewable energy supply. With self-generation, the obtained value is even higher in the perspective of the individual customer, maximizing the cost-effectiveness of such investment

Development of a control framework for hybrid renewable energy system in microgrid

Electrical energy has an essential role in society as it ensures high quality of life and steady economic development. Demand for the electric energy has been steadily growing throughout the recent history and this demand is expected to grow further in the future. Most of electrical energy nowadays is generated by burning fossil fuels and there are serious concerns about the resulting emission. Renewable energy sources appeared as a viable alternative for environmentally hazardous sources. However, sources of renewable energy have considerably unpredictable and environmental conditions dependent power output and as such can’t be directly incorporated into existing electrical grid. These sources are usually integrated to the electrical grid as part of microgrid or hybrid energy source that consists of two or more energy sources, converters and/or storage devices. In hybrid energy sources, generation and storage elements complement each other to provide high quality and more reliable power delivery. This area of research is its infant stage and requires a lot of research and development effort to be done. Main objective of this thesis is to develop a framework for analysis and control of power electronics interfaces in microgrid connected hybrid energy source. The framework offers the generalized approach in treatment of control problem for hybrid energy sources. Development of the framework is done for the generalized hybrid source comprised of energy source(s), storage element(s), power electronic interfaces and control system. The main contributions of this thesis are, generalization of control problem for power electronics interfaces in hybrid energy source, the development of switching algorithm for three phase switching converters based on the closed loop behavior of the converters and the development of a maximum power point tracking algorithm for the renewable energy sources

Bi-Level Optimization Considering Uncertainties of Wind Power and Demand Response

Recently, world-wide power systems have been undergone a paradigm change with increasing penetration of renewable energy. The renewable energy is clean with low operation cost while subject to significant variability and uncertainty. Therefore, integration of renewables presents various challenges in power systems. Meanwhile, to offset the uncertainty from renewables, demand response (DR) has gained considerable research interests because of DR’s flexibility to mitigate the uncertainty from renewables. In this dissertation, various power system problems using bi-level optimization are investigated considering the uncertainties from wind power and demand response. In power system planning, reactive power planning (RPP) under high-penetration wind power is studied in this dissertation. To properly model wind power uncertainty, a multi-scenario framework based on alternating current optimal power flow (ACOPF) considering the voltage stability constraint under the worst wind scenario and transmission N-1 contingency is developed. The objective of RPP in this work is to minimize the VAR investment and the expected generation cost. Benders decomposition is used to solve this model with an upper level problem for VAR allocation optimization and generation cost minimization as a lower problem. Then, several problems related wind power and demand response uncertainties under power market operation are investigated. These include: an efficient and effective method to calculate the LMP intervals under wind uncertainty is proposed; the load serving entities’ strategic bidding through a coupon-based demand response (CBDR) with which a load serving entity (LSE) may participate in the electricity market as strategic bidders by offering CBDR programs to customers; the impact of financial transmission right (FTR) with CBDR programs is also studied from the perspective of LSEs; and the stragegic scheduling of energy storages owned by LSEs considering the impact of charging and discharging on the bus LMP. In these problems, a bi-level optimization framework is presented with various objective functions representing different problems as the upper level problems and the ISO’s economic dispatch (ED) as the lower level problem. The bi-level model is addressed with mathematic program with equilibrium constraints (MPEC) model and mixed-integer linear programming (MILP), which can be easily solved with the available optimization software tool

Green synthetic fuels: Renewable routes for the conversion of non-fossil feedstocks into gaseous fuels and their end uses

Innovative renewable routes are potentially able to sustain the transition to a decarbonized energy economy. Green synthetic fuels, including hydrogen and natural gas, are considered viable alternatives to fossil fuels. Indeed, they play a fundamental role in those sectors that are di cult to electrify (e.g., road mobility or high-heat industrial processes), are capable of mitigating problems related to flexibility and instantaneous balance of the electric grid, are suitable for large-size and long-term storage and can be transported through the gas network. This article is an overview of the overall supply chain, including production, transport, storage and end uses. Available fuel conversion technologies use renewable energy for the catalytic conversion of non-fossil feedstocks into hydrogen and syngas. We will show how relevant technologies involve thermochemical, electrochemical and photochemical processes. The syngas quality can be improved by catalytic CO and CO2 methanation reactions for the generation of synthetic natural gas. Finally, the produced gaseous fuels could follow several pathways for transport and lead to different final uses. Therefore, storage alternatives and gas interchangeability requirements for the safe injection of green fuels in the natural gas network and fuel cells are outlined. Nevertheless, the effects of gas quality on combustion emissions and safety are considered

Symmetry in Renewable Energy and Power Systems

This book includes original research papers related to renewable energy and power systems in which theoretical or practical issues of symmetry are considered. The book includes contributions on voltage stability analysis in DC networks, optimal dispatch of islanded microgrid systems, reactive power compensation, direct power compensation, optimal location and sizing of photovoltaic sources in DC networks, layout of parabolic trough solar collectors, topologic analysis of high-voltage transmission grids, geometric algebra and power systems, filter design for harmonic current compensation. The contributions included in this book describe the state of the art in this field and shed light on the possibilities that the study of symmetry has in power grids and renewable energy systems