Techno-Economic Assessment of LNG and Diesel Production and Global Trading Based on Hybrid PV-Wind Power Plants and PtG, GtL and PtL Technologies

With growing demand for liquefied natural gas (LNG) and liquid transportation fuels, and concerns about climate change and causes of greenhouse gas emissions, this master’s thesis introduces a new value chain design for LNG and transportation fuels and respective fundamental business cases based on hybrid PV-Wind power plants. The value chains are composed of renewable electricity (RE) converted by power-to-gas (PtG), gas-to-liquids (GtL) or power-to-liquids (PtL) facilities into SNG (which is finally liquefied into LNG) or synthetic liquid fuels, mainly diesel, respectively. The RE-LNG or RE-diesel are drop-in fuels to the current energy system and can be traded everywhere in the world. The calculations for the hybrid PV-Wind power plants, electrolysis, methanation (H2tSNG), hydrogen-to-liquids (H2tL), GtL and LNG value chain are performed based on both annual full load hours (FLh) and hourly analysis. Results show that the proposed RE-LNG produced in Patagonia, as the study case, is competitive with conventional LNG in Japan for crude oil prices within a minimum price range of about 87 - 145 USD/barrel (20 – 26 USD/MBtu of LNG production cost) and the proposed RE-diesel is competitive with conventional diesel in the European Union (EU) for crude oil prices within a minimum price range of about 79 - 135 USD/barrel (0.44 – 0.75 €/l of diesel production cost), depending on the chosen specific value chain and assumptions for cost of capital, available oxygen sales and CO2 emission costs. RE-LNG or RE-diesel could become competitive with conventional fuels from an economic perspective, while removing environmental concerns. The RE-PtX value chain needs to be located at the best complementing solar and wind sites in the world combined with a de-risking strategy. This could be an opportunity for many countries to satisfy their fuel demand locally. It is also a specific business case for countries with excellent solar and wind resources to export carbon-neutral hydrocarbons, when the decrease in production cost is considerably more than the shipping cost. This is a unique opportunity to export carbon-neutral hydrocarbons around the world where the environmental limitations on conventional hydrocarbons are getting tighter.

A review on the recent history of wind power ramp forecasting.

Forecasting large and fast variations of wind power (the so called ramps) helps achieve the integration of large amounts of wind energy. This paper presents a survey on wind power ramp forecasting, reflecting the increasing interest on this topic observed since 2007. Three main aspects were identified from the literature: wind power ramp definition, ramp underlying meteorological causes and experi-ences in predicting ramps. In this framework, we additionally outline a number of recommendations and potential lines of research.

Identifying wind power ramp causes from multivariate datasets: a methodological proposal and its application to reanalysis data.

Forecasting abrupt variations in wind power generation (the so-called ramps) helps achieve large scale wind power integration. One of the main issues to be confronted when addressing wind power ramp forecasting is the way in which relevant information is identified from large datasets to optimally feed forecasting models. To this end, an innovative methodology oriented to systematically relate multivariate datasets to ramp events is presented. The methodology comprises two stages: the identification of relevant features in the data and the assessment of the dependence between these features and ramp occurrence. As a test case, the proposed methodology was employed to explore the relationships between atmospheric dynamics at the global/synoptic scales and ramp events experienced in two wind farms located in Spain. The achieved results suggested different connection degrees between these atmospheric scales and ramp occurrence. For one of the wind farms, it was found that ramp events could be partly explained from regional circulations and zonal pressure gradients. To perform a comprehensive analysis of ramp underlying causes, the proposed methodology could be applied to datasets related to other stages of the wind-topower conversion chain.

Incorporating wind power forecast uncertainties into stochastic unit commitment using neural network-based prediction intervals

Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

A time series ensemble method to predict wind power

Wind power prediction refers to an approximation of the probable production of wind turbines in the near future. We present a time series ensemble framework to predict wind power. Time series wind data is transformed using a number of complementary methods. Wind power is predicted on each transformed feature space. Predictions are aggregated using a neural network at a second stage. The proposed framework is validated on wind data obtained from ten different locations across Australia. Experimental results demonstrate that the ensemble predictor performs better than the base predictors.

Relação entre stakeholders, recursos estratégicos e sustentabilidade em uma organização atuante na cadeia de valor da indústria brasileira de energia eólica

This paper approaches the strategy in business management and aimed at identifying and outlining the interests and commitment of stakeholders in strategic resources management concerning production and implementation of wind turbine equipment of a Brazilian wind power company and also verifying if internal and external results deriving from such activities were sustainable, taking as main reference seminal publications and periodicals relevant to the research point that discuss the Resource Theory, Stakeholders and Sustainability. An analysis was carried out to assess how stakeholders, beyond the temporal context, intermediated the composition, development and management of the organization´s resources, as well as the social, environmental and economic results obtained from resources management in the production and supply of wind turbines to a Wind Power Plant located in the State of Ceara, in order to portray that Brazil sustainability can be an important competitive advantage source that creates value for shareholders and the community (Hart & Milstein, 2003). The strategy herein applied was the qualitative investigation using a single study case, which allowed for the thorough examination of an active organization operating in the Brazilian industry of wind power and also the resources used in the production and implementation of wind turbines supplied to the a Wind Power Plant in Ceara. Considering the content analysis and the triangulation principle, three qualitative data collection methods were applied to identify and characterize stakeholders’ interest and commitment in resource management of the organization operating in the Brazilian wind power industry, as follows, semistructured deep interview with managers of tactic-strategic level and analysts of organization´s value chain nine activities, analysis of public internal and external documents; and analysis of audio-visual material. Nonetheless, to identify the internal and external economic, social and environmental results of implementation and supply of wind turbines to the Wind Power Plant in Ceara, semistructured interviews were also carried out with the residents of the region. Results showed the BNDES (Brazilian Development Bank) and the organization head office were the stakeholders who exerted the strongest influence on resources related to production and implementation of the aerogenerator product at Trairi Wind Plant in Ceara. Concerning the organization resources, at the current stage of the Brazilian Wind Industry ,although the brand, reliability and reputation of the organization under study were valuable esources, rare, hard to imitate and exploited by the organization, it was noticed that opposed to RBV, they did not actually represent a source of competitive advantage . For the local community the social, economic and environmental results related to the wind turbines implementation were more positive than negative, despite the fact that the productive process caused negative environmental impacts such as the high emission of CO2 to transport wind turbines components to Trairi Wind Power Plant.

Investigation of the effects of various types of wind turbine generators on power-system stability

It has become more and more demanding to investigate the impacts of wind farms on power system operation as ever-increasing penetration levels of wind power have the potential to bring about a series of dynamic stability problems for power systems. This paper undertakes such an investigation through investigating the small signal and transient stabilities of power systems that are separately integrated with three types of wind turbine generators (WTGs), namely the squirrel cage induction generator (SCIG), the doubly fed induction generator (DFIG), and the permanent magnet generator (PMG). To examine the effects of these WTGs on a power system with regard to its stability under different operating conditions, a selected synchronous generator (SG) of the well-known Western Electricity Coordinating Council (WECC three-unit nine-bus system and an eight-unit 24-bus system is replaced in turn by each type of WTG with the same capacity. The performances of the power system in response to the disturbances are then systematically compared. Specifically, the following comparisons are undertaken: (1) performances of the power system before and after the integration of the WTGs; and (2) performances of the power system and the associated consequences when the SCIG, DFIG, or PMG are separately connected to the system. These stability case studies utilize both eigenvalue analysis and dynamic time-domain simulation methods.

A dual inverter-based supercapacitor direct integration scheme for wind energy conversion systems

Interfacing converters used in connecting energy storage systems like supercapacitors and battery banks to wind power systems introduce additional cost and power losses. This paper therefore presents a direct integration scheme for supercapacitors used in mitigating short-term power fluctuations in wind power systems. This scheme uses a dual inverter topology for both grid connection and interfacing a supercapacitor bank. The main inverter of the dual inverter system is powered by the rectified output of a wind turbine-coupled permanent-magnet synchronous generator. The auxiliary inverter is directly connected to the supercapacitor bank. With this approach, an interfacing converter is not required, and there are no associated costs and power losses incurred. The operation of the proposed system is discussed in detail. Simulation and experimental results are presented to verify the efficacy of the proposed system in suppressing short-term wind power fluctuations.

Flying supercapacitors as power smoothing elements in wind generation

This paper presents a capacitor-clamped three-level inverter-based supercapacitor direct integration scheme for wind energy conversion systems. The idea is to increase the capacitance of clamping capacitors with the use of supercapacitors and allow their voltage to vary within a defined range. Even though this unique approach eliminates the need of interfacing dc-dc converters for supercapacitors, the variable voltage operation brings about several challenges. The uneven distribution of space vectors is the major modulation challenge. A space vector modulation method is proposed in this paper to address this issue and to generate undistorted currents even in the presence of dynamic changes in supercapacitor voltages. A supercapacitor voltage equalization algorithm is also presented. Moreover, control strategies of the proposed system are discussed in detail. Simulation and experimental results are presented to verify the efficacy of the proposed system in suppressing short-term wind power fluctuations.

Doubly Fed Induction Generator for wind energy generation using nine-switch power converter

A Three-Phase Nine-Switch Converter (NSC) topology for Doubly Fed Induction Generator in wind energy generation is proposed in this paper. This converter topology was used in various applications such as Hybrid Electric Vehicles and Uninterruptable Power Supplies. In this paper, Nine-Switch Converter is introduced in Doubly Fed Induction Generator in renewable energy application for the first time. It replaces the conventional Back-to-Back Pulse Width Modulated voltage source converter (VSC) which composed of twelve switches in many DFIG applications. Reduction in number of switches is the most beneficial in terms of cost and power switching losses. The operation principle of Nine-Switch Converter using SPWM method is discussed. The resulting NSC performance of rotor side current control, active power and reactive control are compared with Back-to Back voltage source converter performance. DC link voltage regulation using front end converter is also presented. Finally the simulation results of DFIG performances using NSC and Back-to-Back VSC are analyzed and compared.

Design of a wind turbine - battery energy storage scheme to achieve power dispatchability

Battery energy storage system (BESS) is to be incorporated in a wind farm to achieve constant power dispatch. The design of the BESS is based on the forecasted wind speed, and the technique assumes the distribution of the error between the forecasted and actual wind speeds is Gaussian. It is then shown that although the error between the predicted and actual wind powers can be evaluated, it is non-Gaussian. With the known distribution in the error of the predicted wind power, the capacity of the BESS can be determined in terms of the confident level in meeting specified constant power dispatch commitment. Furthermore, a short-term power dispatch strategy is also developed which takes into account the state of charge (SOC) of the BESS. The proposed approach is useful in the planning of the wind farm-BESS scheme and in the operational planning of the wind power generating station.

Probabilistic power system contingency analysis considering wind

This thesis was a step forward in developing probabilistic assessment of power system response to faults subject to intermittent generation by renewable energy. It has investigated the wind power fluctuation effect on power system stability, and the developed fast estimation process has demonstrated the feasibility for real-time implementation. A better balance between power network security and efficiency can be achieved based on this research outcome.

Application of TS-Fuzzy Controller for Active Power and DC Capacitor Voltage Control in DFIG-Based Wind Energy Conversion Systems

This chapter focuses on the implementation of the TS (Tagaki-Sugino) fuzzy controller for the Doubly Fed Induction Generator (DFIG) based wind generator. The conventional PI control loops for mantaining desired active power and DC capacitor voltage is compared with the TS fuzzy controllers. DFIG system is represented by a third-order model where electromagnetic transients of the stator are neglected. The effectiveness of the TS-fuzzy controller on the rotor speed oscillations and the DC capacitor voltage variations of the DFIG damping controller on converter ratings is also investigated. The results from the time domain simulations are presented to elucidate the effectiveness of the TS-fuzzy controller over the conventional PI controller in the DFIG system. The proposed TS-fuzzy con-troller can improve the fault ride through capability of DFIG compared to the conventional PI controller.

WEPA: Wind energy potential assessment-spatial decision support system

Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.