Integration of Pumping Profile Design and Water Management Optimization for Shale Gas Production Systems

Unconventional shale gas production in the United States has been largely improved due to the development of hydraulic fracturing technology. However, the shale gas production system is generally complex; further, such enhanced levels of production have generated great concerns on its accompanying environmental implications, especially regarding shale gas water management. To handle the complexity associated with shale gas production system and identify the sustainable water management strategy, many optimization-based approaches have been developed. However, few of them considered the hydraulic fracturing operation as a dynamic process, where the pumping profile directly determines the volume of freshwater consumed and affects the production rates of both shale gas and wastewater. Considering the significant spatiotemporal variation in water footprint of hydraulic fracturing, those obtained planning and operational decisions of shale gas production system could be suboptimal and thus need to be updated when well development strategy changes. From another perspective, one problem could be that the pumping profile is generally designed to only maximize well productivity, without considering the impact of water management. To handle these challenges, the overall objective of this research is to develop a framework for the integration of pumping profile design and water management optimization to achieve the economically viable and environmentally sustainable water management strategy along with maximizing shale gas production. To this end, we initially focus on the development of a novel controller design framework for hydraulic fracturing while explicitly taking into account the associated post-fracturing water management. In particular, a dynamic input-output model is developed to estimate the characteristics of shale gas wastewater produced; and, a mapping-based technique is proposed to estimate the total annual cost of wastewater management and total revenue from shale gas. This framework is demonstrated to be capable to balance the trade-offs between hydraulic fracturing and water management by manipulating the pumping profile. Subsequently, we further extend this study by considering the following practical considerations. First, to better understand the significant spatiotemporal variation in water footprint associated with shale gas well development, the real water-use and flowback and produced (FP) water production data for individual shale gas wells drilled in the Eagle Ford and Marcellus shale regions are collected and analyzed. Herein, a typical model of shale gas production system is utilized to demonstrate how the variation in water recovery ratio can affect the optimal design and operation decisions. Second, to better describe the complex shale gas production system, an optimization model for shale gas supply chain network (SGSCN) incorporating of hydraulic fracturing water cycle is developed. Herein, capacity planning for both large-scale conventional facility and small-scale modular device is considered to achieve a flexible and efficient water management strategy. Third, to better integrate the optimization of shale gas production system and control of hydraulic fracturing, an online integrated scheduling and control framework with two feedback loops is proposed. Herein, the offset-free model predictive control (MPC) scheme is designed to compensate for plant-model mismatch

Development of a techno-economic energy model for low carbon business parks

To mitigate climate destabilisation, global emissions of human-induced greenhouse gases urgently need to be reduced, to be nearly zeroed at the end of the century. Clear targets are set at European level for the reduction of greenhouse gas emissions and primary energy consumption and for the integration of renewable energy. Carbon dioxide emissions from fossil fuel combustion in the industry and energy sectors account for a major share of greenhouse gas emissions. Hence, a low carbon shift in industrial and business park energy systems is called for. Low carbon business parks minimise energy-related carbon dioxide emissions by enhanced energy efficiency, heat recovery in and between companies, maximal exploitation of local renewable energy production, and energy storage, combined in a collective energy system. Moreover, companies with complementary energy profiles are clustered to exploit energy synergies. The design of low carbon energy systems is facilitated using the holistic approach of techno-economic energy models. These models take into account the complex interactions between the components of an energy system and assist in determining an optimal trade-off between energetic, economic and environmental performances. In this work, existing energy model classifications are scanned for adequate model characteristics and accordingly, a confined number of energy models are selected and described. Subsequently, a practical categorisation is proposed, existing of energy system evolution, optimisation, simulation, accounting and integration models, while key model features are compared. Next, essential features for modelling energy systems at business park scale are identified: As a first key feature, a superstructure-based optimisation approach avoids the need for a priori decisions on the system’s configuration, since a mathematical algorithm automatically identifies the optimal configuration in a superstructure that embeds all feasible configurations. Secondly, the representation of time needs to incorporate sufficient temporal detail to capture important characteristics and peaks in time-varying energy demands, energy prices and operation conditions of energy conversion technologies. Thirdly, energy technologies need to be accurately represented at equipment unit level by incorporating part-load operation and investment cost subject to economy of scale in the model formulation. In addition, the benefits of installing multiple units per technology must be considered. A generic model formulation of technology models facilitates the introduction of new technology types. As a fourth important feature, the potential of thermodynamically feasible heat exchange between thermal processes needs to be exploited, while optimally integrating energy technologies to fulfil remaining thermal demands. For this purpose, thermal streams need to be represented by heat –temperature profiles. Moreover, restrictions to direct heat exchange between process streams need to be taken into account. Finally, the possibility for energy storage needs to be included to enhance the integration of non-dispatchable renewable energy technologies and to bridge any asynchrony between cooling and heating demands. Starting from these essential features, a techno-economic optimisation model (Syn-E-Sys), is developed customised for the design of low carbon energy systems on business park scale. The model comprises two sequential stages. In the first stage, heat recovery within the system is maximised, while energy supply and energy storage technologies are optimally integrated and designed to fulfil remaining energy requirements at minimum total annualised costs. Predefined variations in thermal and electrical energy demand and supply are taken into account, next to a carbon emission cap. At the same time, heat networks can be deployed to transfer heat between separate parts of the system. In the second stage, the model generates an optimal multi-period heat exchanger network enabling all required heat exchanges. Syn-E-Sys builds upon a multi-period energy integration model that can deal with restrictions in heat exchange. It is combined with a generic technology model, that features part-load operation as well as investment cost subject to economy of scale, and a generic energy storage model. The technology model can be manipulated to represent various thermal or electrical energy conversion technology units, and serves as a building block to model more complex technologies. The storage model covers electrical as well as thermal energy storage, taking into account the effect of hourly energy losses on the storage level, without increasing the number of time steps to be analysed. For this purpose, time sequence is introduced by dividing the year into a set of time slices and assigning them to a hierarchical time structure. In addition, a more complex model for storage of sensible heat is integrated, consisting of a stack of interconnected virtual tanks. To enable the optimisation of the number of units per technology in the energy system configuration, an automated superstructure expansion procedure is incorporated. Heat transfer unit envelope curves are calculated to facilitate the choice of appropriate temperature levels for heat networks. Heat networks that are embedded within this envelope, completely avoid the increase in energy requirements that would result from the heat exchange restrictions between separated parts of the energy system. Finally, the heat exchanger network is automatically generated using a multi-period stage-wise superstructure. Two problems inherent to the heat cascade formulation are encountered during model development. As a first issue, heat networks can form self-sustaining energy loops if their hot and cold streams are not completely embedded within the envelope. This phenomenon is referred to in this work as phantom heat. As a second issue, the heat cascade formulation does not prevent that a thermal storage releases its heat to a cooling technology. To demonstrate the specific features of Syn-E-Sys and its holistic approach towards the synthesis of low carbon energy systems, the model is applied to a generic case study and to a case study from literature. The generic case study is set up to demonstrate the design of an energy system including non-dispatchable renewable energy and energy storage, subject to a carbon emission cap. For this purpose, the year is subdivided into a set of empirically defined time slices that are connected to a hierarchical time structure composed of seasons, daytypes and intra-daily time segments. The results obtained by Syn-E-Sys show a complex interaction between energy supply, energy storage and energy import/export to fulfil energy demands, while keeping carbon emissions below the predefined cap. The model enables optimisation of the intra-annual charge pattern and the capacity of thermal and electrical storage. Moreover, an optimal heat exchanger network is automatically generated. In the second case study, heat recovery is optimised for a drying process in the paper industry. To avoid the energy penalty due to heat exchange restrictions between two separated process parts, heat transfer units need to be optimally integrated. Firstly, a simplified version of the original problem is set up in Syn-E-Sys and the obtained results correspond well to literature. Subsequently, the original problem is extended to demonstrate the optimal integration of heat transfer units in a multi-period situation. In conclusion, Syn-E-Sys facilitates optimal design of low carbon energy systems on business park scale, taking into account the complex time-varying interactions between thermal and electrical energy demand, supply and storage, while the potential for heat recovery is fully exploited

Multi-objective design and optimization of district energy systems including polygeneration energy conversion technologies

In the present context of finding ways to decrease CO2 emissions linked with human activity, district energy systems including polygeneration energy conversion technologies are likely to play a major role. District energy systems meet the heating, hot water, cooling and electricity requirements of a district. Because they meet several types of energy requirements, and for more than one single building, district energy systems represent good opportunities to implement polygeneration energy conversion technologies. Polygeneration energy conversion technologies indeed provide different energy services simultaneously, helping to decrease the CO2 intensity compared to energy conversion technologies that meet only one energy service. Moreover, when providing energy to a whole district, polygeneration energy conversion technologies can take advantage of the various load profiles of the buildings by compensating the fluctuations and having therefore a smoother operation. A district energy system comprises essentially two parts: the plant with the polygeneration energy conversion technologies, and the distribution networks (heating and cooling). When designing the energy system for a district, one has therefore to define which type of polygeneration energy conversion technologies are best suited for the district, as well as which building are worse connecting to the system and which buildings shouldn't be connected (for instance if they are located too far away from the other buildings or if they have too small requirements to justify a connection from the plant). Moreover the operation strategy needs to be defined. In the present thesis, a method is developed that helps designing and optimizing district energy systems, from the structuring of the information available for the district (energy consumption profiles, location of the buildings, available energy sources, possible layouts for the pipes,...), over the thermo-economic modelling of the energy conversion technologies, the design of the network and the simulation of its operation strategy, and finally the evaluation of the results in terms of CO2 emissions and costs. The design and optimization of the district energy system is a multi-objective Mixed Integer Non Linear Programming problem. To solve this problem, a decomposition strategy including a master and a slave problem was developed. The master optimization problem takes care of the energy conversion technologies, whereas the slave optimization problem optimizes the network part. The two sub-problems are solved iteratively and result in the definition of a Pareto optimal curve that gives the trade-offs between the emissions and the costs for various configurations satisfying the requirements of the district. A configuration is characterized by given types and sizes of energy conversion technologies, their location in the district, the network layout, as well as the operation strategy of the technologies. Due to the time dependent energy consumption profiles and the geographical location of the buildings and plant, the method developed combines two well known types of problems, namely the multi-period optimization problems and the network problems. The method developed allows to take into account various constraints such as limited availability of energy sources, forbidden connections between buildings (for instance if a large river separates these two buildings), or else space limitations in underground technical channels. The capabilities of the method are demonstrated by means of a test case, as well as a real case in the Canton of Geneva. The results show the importance of considering all the energy services together (and not separately). Energy systems including a gas engine or a gas turbine combined cycle, together with heat pumps, indeed help decreasing both the emissions and the costs compared to the actual configurations. In the Geneva case study for instance, emissions can be decreased by up to 45%, with a simultaneous costs reduction of 24%. However, the method only deals with water networks, while in some cases space limitations and safety issues make the use of water impossible. A new type of district energy system based on CO2 as energy transfer medium (instead of water), is therefore developed in order to take such issues into account. This new system, that led to the submission of a patent, meets all the different types of energy requirements with only two pipes (instead of three or four like in conventional water based system), and uses the latent heat of CO2 as driving force, instead of the specific heat

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

Towards COP27: The Water-Food-Energy Nexus in a Changing Climate in the Middle East and North Africa

Due to its low adaptability to climate change, the MENA region has become a "hot spot". Water scarcity, extreme heat, drought, and crop failure will worsen as the region becomes more urbanized and industrialized. Both water and food scarcity are made worse by civil wars, terrorism, and political and social unrest. It is unclear how climate change will affect the MENA water–food–energy nexus. All of these concerns need to be empirically evaluated and quantified for a full climate change assessment in the region. Policymakers in the MENA region need to be aware of this interconnection between population growth, rapid urbanization, food safety, climate change, and the global goal of lowering greenhouse gas emissions (as planned in COP27). Researchers from a wide range of disciplines have come together in this SI to investigate the connections between water, food, energy, and climate in the region. By assessing the impacts of climate change on hydrological processes, natural disasters, water supply, energy production and demand, and environmental impacts in the region, this SI will aid in implementation of sustainable solutions to these challenges across multiple spatial scales

IEA ECES Annex 31 Final Report - Energy Storage with Energy Efficient Buildings and Districts: Optimization and Automation

At present, the energy requirements in buildings are majorly met from non-renewable sources where the contribution of renewable sources is still in its initial stage. Meeting the peak energy demand by non-renewable energy sources is highly expensive for the utility companies and it critically influences the environment through GHG emissions. In addition, renewable energy sources are inherently intermittent in nature. Therefore, to make both renewable and nonrenewable energy sources more efficient in building/district applications, they should be integrated with energy storage systems. Nevertheless, determination of the optimal operation and integration of energy storage with buildings/districts are not straightforward. The real strength of integrating energy storage technologies with buildings/districts is stalled by the high computational demand (or even lack of) tools and optimization techniques. Annex 31 aims to resolve this gap by critically addressing the challenges in integrating energy storage systems in buildings/districts from the perspective of design, development of simplified modeling tools and optimization techniques

Energy Prediction and Optimization of the Hybrid Community District Heating System (H-CDHS)

The ever-increasing demand for energy in different sectors, such as building sector as one of the main consumers of the energy, is a result of a considerable surge in the world population, starting since the beginning of the industrial revolution in the late 18th century until the present. One of the direct consequence of this rapid growth was the overuse of fossil fuels as the world's main energy source resulting in a rapid depletion of them and thereby increasing the level of CO2 equivalent emissions at an atmospheric level known as greenhouse gasses. Increasing the concentration of these gasses at atmospheric level, exceeding the 400 PPM level for the first time in history, puts the earth at the point of no return. In order to sustain the economic growth while reducing the greenhouse gas concentration at an atmospheric level at the current stage, providing a clean sustainable solution which allows for a steady flow of energy is one of the most vital challenges facing the politician and energy planners. One of the solutions proposed by the energy planners which touches the higher level of energy management is to promote the usage of District Heating Systems (DHS). While designing an efficient DHS is highly dependant on accurate modeling of the thermal performance of the buildings, district users; yet, limited simulation tools capable of modeling the district energy systems, at a larger scale with a numerous user’s types and with an appropriated level of precision which can potentially be a very laborious and time-consuming process, have been developed. Besides many associated limitations, providing a realistic demand profile of the district energy systems is not a straightforward task due to a high number of parameters involved in predicting a detailed demand profile. To this end, this dissertation focuses on the development of the procedure for energy modeling and optimization of the Hybrid Community District Heating System (H-CDHS) with integrated centralized thermal storage, the 4th generation of district heating systems. To do so, this study describes the procedure used to develop two types of simplified models to predict the thermal load of a variety of buildings (residential, office, attached, detached, etc.). The predictions were also compared with those made by the detailed simulation models. The simplified model was then utilized to predict the energy demand of a variety of district types (residential, commercial or mix), and its prediction accuracy was compared with those made by detailed model: A good agreement was observed between the results. In next step, the proposed procedure was utilized to predict the heating demand profile of an existing community, WWH community in Glasgow. High prediction accuracy and low computational time of the proposed method illustrates the potential of the proposed method in predicting the heating demand profile of larger scale communities. In the last step, the proposed load prediction method was coupled with energy simulation tool (TRNSYS) and optimization tool (MATLAB/Simulink) in order to develop a simplified methodology for dynamic optimization of a hybrid community-district heating system (H-CDHS) integrated with a thermal energy storage system. Two existing and newly built community have been defined and the results of the optimization on the equipment size of both communities have been studied. The results for the newly build community is then compared with the one obtained from the conventional equipment sizing methods as well as static optimization methods to obtain potential reduction in equipment size using the proposed method