An Off-design Thermoeconomic Input-Output Analysis of a Natural Gas Combined Cycle Power Plant

In the current and forecasted energy scenario, Natural Gas Combined Cycle (NGCC) power plants are requested increasingly flexible operation. The continuous changes in the capacity factor of the power plants and the increasing number and steepness of ramp-ups could largely affect the thermodynamic and economic performance of the plants and undermine their competitiveness. In order for industrial operators to adopt competitive strategies to increase the flexibility of the power plants, the effect that off-design operation has on the cost structure of plant products needs to be addressed. Thermoeconomics provides tools and models to meet such objective. The study presents an application of Thermoeconomic Input-Output Analysis (TIOA) to a NGCC power plant subject to flexible operation in Italy. The on- and off-design performance of the plant is assessed, considering two load control mechanisms for off-design operation: Inlet Guide Vanes (IGVs) with constant Turbine Outlet Temperature (TOT) or constant Turbine Inlet Temperature (TIT). The Input-Output model is derived from a detailed off-design Thermodynamic model designed in Thermoflow Thermoflex™, and it is stand-alone: it computes the cost structure of the plant products and the Thermoeconomic performance indicators as continuous functions of the gas turbine load, independently from the Thermodynamic model. In the first place, the on- and off-design models of the plant are set up. Secondly, the detailed economic cost analysis is performed. Eventually, the stand-alone Input -Output model is derived: the Technical Coefficients and the Input Coefficients are computed from the fuels and products in the Thermodynamic model at different loads; by regression of the obtained values, continuous functions of the load are derived for each coefficient; finally, the stand-alone model is designed, including these functions in the Leontief Inverse matrix. The results provide an evaluation of the off-design performance of the power plant for the two control strategies, and a tool for the choice of the most efficient one. After specialised analysts set up and run the off-design Thermodynamic model, the power plant operators may perform production scenarios and predictions through the stand-alone Input-Output model independently. This may help abate barriers for industrial practitioners, given by the complexity, computational effort and difficult interpretation of off-design thermodynamic and cost models

PRACTICAL APPROACHES FOR THE APPLICATION OF EXERGY COST THEORY TO ENERGY CONVERSION SYSTEMS

The Exergy Cost Theory (ECT) was proposed as a complete and formalized method to account for the exergy cost of system products, defining criteria for optimization and diagnosis purposes. In this paper, different practical approaches for the application of the Exergy Cost Analysis are presented and comparatively applied to the CGAM problem. An emphasis has been specially put on the possible approaches to define and to solve the system of exergy cost balances, including the definition of auxiliary relations and the reallocation of the exergy cost of residues. It is found that the definition of the functional diagram and the numerical solution of the system through Input-Output analysis seems to be preferable with respect to other approaches

Off-Design Modeling of Natural Gas Combined Cycle Power Plants: An Order Reduction by Means of Thermoeconomic Input–Output Analysis

In a European context characterized by growing need for operational flexibility across the electricity sector, the combined cycle power plants are increasingly subjected to cyclic operation. These new operation profiles cause an increase of production costs and decrease of revenues, which undermines the competitiveness of the combined cycles. Power plant operators need tools to predict the effect of off-design operation and control mechanisms on the performance of the power plant. Traditional Thermodynamic or Thermoeconomic models may be unpractical for the operators, due to their complexity and the computational effort they require. This study proposes a Thermoeconomic Input–Output Analysis model for the on- and off-design performance prediction of energy systems, and applies it to La Casella Natural Gas Combined Cycle (NGCC) power plant, in Italy. It represents a stand-alone, reduced order model, where the cost structure of the plant products and the Thermoeconomic performance indicators are derived for on- and off-design conditions as functions of the load and of different control mechanisms, independently from the Thermodynamic model. The results of the application show that the Thermoeconomic Input–Output Analysis model is a suitable tool for power plant operators, able to derive the same information coming from traditional Thermoeconomic Analysis with reduced complexity and computational effort

Physiologically informed dynamic causal modeling of fMRI data

AbstractThe functional MRI (fMRI) signal is an indirect measure of neuronal activity. In order to deconvolve the neuronal activity from the experimental fMRI data, biophysical generative models have been proposed describing the link between neuronal activity and the cerebral blood flow (the neurovascular coupling), and further the hemodynamic response and the BOLD signal equation. These generative models have been employed both for single brain area deconvolution and to infer effective connectivity in networks of multiple brain areas. In the current paper, we introduce a new fMRI model inspired by experimental observations about the physiological underpinnings of the BOLD signal and compare it with the generative models currently used in dynamic causal modeling (DCM), a widely used framework to study effective connectivity in the brain. We consider three fundamental aspects of such generative models for fMRI: (i) an adaptive two-state neuronal model that accounts for a wide repertoire of neuronal responses during and after stimulation; (ii) feedforward neurovascular coupling that links neuronal activity to blood flow; and (iii) a balloon model that can account for vascular uncoupling between the blood flow and the blood volume. Finally, we adjust the parameterization of the BOLD signal equation for different magnetic field strengths. This paper focuses on the form, motivation and phenomenology of DCMs for fMRI and the characteristics of the various models are demonstrated using simulations. These simulations emphasize a more accurate modeling of the transient BOLD responses — such as adaptive decreases to sustained inputs during stimulation and the post-stimulus undershoot. In addition, we demonstrate using experimental data that it is necessary to take into account both neuronal and vascular transients to accurately model the signal dynamics of fMRI data. By refining the models of the transient responses, we provide a more informed perspective on the underlying neuronal process and offer new ways of inferring changes in local neuronal activity and effective connectivity from fMRI

Long-term energy planning and demand forecast in remote areas of developing countries: Classification of case studies and insights from a modelling perspective

More than half a billion people will still lack reliable and affordable electricity in 2040 and around 1.8 billion may remain reliant on traditional solid biomass for cooking. Long-term energy planning could help to achieve the energy access targets in developing countries, especially in remote rural areas. Different studies exist on long-term rural electricity and thermal energy planning, but the different foci, terminology and methodologies make it difficult to track their similarities, weaknesses and strengths. With this work, we aim at providing a critical analysis of peer-reviewed studies on long-term rural energy planning, to help researchers in the field move across the diverse know-how developed in the last decades. The work resulted in the analysis of 130 studies and categorisation of 85 of them that focus on electricity, thermal energy, and oil supply in rural areas, under a number of rules clearly defined in the first part of the paper. We classify the studies in two consecutive steps, first according to their type and afterwards according to the methodology they employ to forecast the energy demand, which is one the most critical aspects when dealing with long-term rural energy planning. The work also provides specific insights, useful to researchers interested in rural energy modelling. Few studies assume a dynamic demand over the years and most of them do not consider any evolution of the future energy load, or forecast its growth through arbitrary trends and scenarios. This however undermines the relevance of the results for the purpose of long-term planning and highlights the necessity of further developing the forecasting methodologies. We conclude that bottom-up approaches, system-dynamics and agent-based models seem appropriate approaches to forecast the evolution of the demand for energy in the long-term; we analyse their potential capability to tackle the context-specific complexities of rural areas and the nexus causalities among energy and socio-economic dynamics

Tonotopic maps in human auditory cortex using arterial spin labeling

A tonotopic organization of the human auditory cortex (AC) has been reliably found by neuroimaging studies. However, a full characterization and parcellation of the AC is still lacking. In this study, we employed pseudo-continuous arterial spin labeling (pCASL) to map tonotopy and voice selective regions using, for the first time, cerebral blood flow (CBF). We demonstrated the feasibility of CBF-based tonotopy and found a good agreement with BOLD signal-based tonotopy, despite the lower contrast-to-noise ratio of CBF. Quantitative perfusion mapping of baseline CBF showed a region of high perfusion centered on Heschl's gyrus and corresponding to the main high-low-high frequency gradients, co-located to the presumed primary auditory core and suggesting baseline CBF as a novel marker for AC parcellation. Furthermore, susceptibility weighted imaging was employed to investigate the tissue specificity of CBF and BOLD signal and the possible venous bias of BOLD-based tonotopy. For BOLD only active voxels, we found a higher percentage of vein contamination than for CBF only active voxels. Taken together, we demonstrated that both baseline and stimulus-induced CBF is an alternative fMRI approach to the standard BOLD signal to study auditory processing and delineate the functional organization of the auditory cortex. Hum Brain Mapp, 2016. © 2016 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc

The role of Energy-Water nexus to motivate transboundary cooperation:: An indicative analysis of the Drina River Basin

Hydropower is a key energy source for achieving Sustainable Development Goal 7. Meanwhile, the effects of hydropower development and operation are complex, and potentially a source of tension on transboundary rivers. This paper aims at exploring solutions that consider both energy and water to motivate transboundary cooperation in the operation of hydropower plants (HPPs) in the Drina River Basin (DRB), where the level of cooperation among the riparian countries is low. OSeMOSYS was used to develop a multi-country model with a simplified hydrological system to represent the cascade of HPPs in the DRB. Results show that improved cooperation can increase electricity generation in the HPPs downstream without compromising generation upstream. It also demonstrates the role of inexpensive hydropower in enhancing electricity trade in the region. Implementing energy efficiency measures would reduce the stress on coal power plants, which will mitigate CO2 emissions by about 21% compared to the 2015 level

Energy projections for African countries

This report provides insights on energy supply and demand, power generation, investments and total system costs, water consumption and withdrawal by the energy sector as well as carbon dioxide emissions for the African continent. The energy supply systems of forty-seven African countries are modelled individually and connected via gas and electricity trade links to identify the cost-optimal solution to satisfy each country's total final energy demand for the period 2015-2065. In this analysis, The Electricity Model Base for Africa (TEMBA) was extended to include a simple representation of the full energy system. It was also updated to include new data. Simulations were run using the medium- to long-term Open Source Energy Modelling System tool (OSeMOSYS). The TEMBA model produces aggregate results for the whole continental energy system and more detailed ones for the power system of each African country. The scenarios examined in this study consider different emission trajectories and technology availability. The Reference scenario considers the national energy policies that were in place until 2017, whereas the 2.0°C and 1.5°C scenarios examine emission levels aligned with the climate targets agreed under the United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement. The scenarios have been aligned with the "Global Energy and Climate Outlook 2018: Greenhouse gas emissions and energy balances" report of the Joint Research Centre (Keramidas et al., 2018). The results demonstrate that power generation capacity will need to increase 10-fold from 2015 to 2065 to meet projected electricity demands. A significant proportion of this capacity will likely consist of renewable energy sources, particularly under the 2.0°C and 1.5°C scenarios, as technology costs fall. On the contrary, there will only be little investment for new coal generation. In addition, a number of African countries will invest in nuclear power plants and CCS technologies (biomass, coal, gas) in the future in order to achieve the emission targets set in the 2.0°C and 1.5°C scenarios. The results also indicate how water demand from the energy sector could evolve. Under the Reference scenario, it is estimated that by 2065 the African energy system will contribute to a water withdrawal of approximately 4% of the total renewable water resources (TRWR) in Africa (3,950 bcm) (FAO - Food and Agriculture Organization of the United Nations, n.d.). On the one hand, this share appears meagre, but in reality, this number must be analysed in the perspective of the nexus between water for food, energy, household and productive uses. Most of the thermal power infrastructure is not located in remote places and is rather near to population centres. This creates an added complexity to future infrastructure planning. On the other hand, water withdrawals are expected to decrease to 1.2% and 1.6% of TRWR in the 2.0°C and 1.5°C scenarios respectively by 2065 owing to deep decarbonisation of the energy sector.JRC.C.7-Knowledge for the Energy Unio

Climate, Land, Energy and Water systems interactions – From key concepts to model implementation with OSeMOSYS

The Climate, Land, Energy and Water systems (CLEWs) approach guides the development of integrated assessments. The approach includes an analytical component that can be performed using simple accounting methods, soft-linking tools, incorporating cross-systems considerations in sectoral models, or using one modelling tool to represent CLEW systems. This paper describes how a CLEWs quantitative analysis can be performed using one single modelling tool, the Open Source Energy Modelling System (OSeMOSYS). Although OSeMOSYS was primarily developed for energy systems analysis, the tool’s functionality and flexibility allow for its application to CLEWs. A step-by-step explanation of how climate, land, energy, and water systems can be represented with OSeMOSYS, complemented with the interpretation of sets, parameters, and variables in the OSeMOSYS code, is provided. A hypothetical case serves as the basis for developing a modelling exercise that exemplifies the building of a CLEWs model in OSeMOSYS. System-centred scenario analysis is performed with the integrated model example to illustrate its application. The analysis of results shows how integrated insights can be derived from the quantitative exercise in the form of conflicts, trade-offs, opportunities, and synergies. In addition to the modelling exercise, using the OSeMOSYS-CLEWs example in teaching, training and open science is explored to support knowledge transfer and advancement in the field