Optimal Pretreatment System of Flowback Water from Shale Gas Production

Shale gas has emerged as a potential resource to transform the global energy market. Nevertheless, gas extraction from tight shale formations is only possible after horizontal drilling and hydraulic fracturing, which generally demand large amounts of water. Part of the ejected fracturing fluid returns to the surface as flowback water, containing a variety of pollutants. For this reason, water reuse and water recycling technologies have received further interest for enhancing overall shale gas process efficiency and sustainability. Water pretreatment systems (WPSs) can play an important role for achieving this goal. This paper introduces a new optimization model for WPS simultaneous synthesis, especially developed for flowback water from shale gas production. A multistage superstructure is proposed for the optimal WPS design, including several water pretreatment alternatives. The mathematical model is formulated via generalized disjunctive programming (GDP) and solved by re-formulation as a mixed-integer nonlinear programming (MINLP) problem, to minimize the total annualized cost. Hence, the superstructure allows identifying the optimal pretreatment sequence with minimum cost, according to inlet water composition and wastewater-desired destination (i.e., water reuse as fracking fluid or recycling). Three case studies are performed to illustrate the applicability of the proposed approach under specific composition constraints. Thus, four distinct flowback water compositions are evaluated for the different target conditions. The results highlight the ability of the developed model for the cost-effective WPS synthesis, by reaching the required water compositions for each specified destination

Social cooperation and resource management dynamics among late hunter-fisher-gatherer societies in Tierra del Fuego (South America)

This paper presents the theoretical basis and first results of an agent-based model (ABM) computer simulation that is being developed to explore cooperation in hunter–gatherer societies. Specifically, we focus here on Yamana, a hunter-fisher-gatherer society that inhabited the islands of the southernmost part of Tierra del Fuego (Argentina–Chile). Ethnographical and archaeological evidence suggests the existence of sporadic aggregation events, triggered by a public call through smoke signals of an extraordinary confluence of resources under unforeseeable circumstances in time and space (a beached whale or an exceptional accumulation of fish after a low tide, for example). During these aggregation events, the different social units involved used to develop and improve production, distribution and consumption processes in a collective way. This paper attempts to analyse the social dynamics that explain cooperative behaviour and resource-sharing during aggregation events using an agent-based model of indirect reciprocity. In brief, agents make their decisions based on the success of the public strategies of other agents. Fitness depends on the resource captured and the social capital exchanged in aggregation events, modified by the agent’s reputation. Our computational results identify the relative importance of resources with respect to social benefits and the ease in detecting—and hence punishing—a defector as key factors to promote and sustain cooperative behaviour among populationSpanish Ministerio de Ciencia e Innovación (projects CONSOLIDER-INGENIO 2010 SimulPast-CSD2010-00034 and HAR2009-06996) as well as from the Argentine Consejo Nacional de Investigaciones Científicas y Técnicas (project PIP-0706) and the Wenner-Gren Foundation for Anthropological Research (project GR7846)

Evaluation Framework and Tools for Distributed Energy Resources

The Energy Information Administration's (EIA) 2002 Annual Energy Outlook (AEO) forecast anticipates the need for 375 MW of new generating capacity (or about one new power plant) per week for the next 20 years, most of which is forecast to be fueled by natural gas. The Distributed Energy and Electric Reliability Program (DEER) of the Department of Energy (DOE), has set a national goal for DER to capture 20 percent of new electric generation capacity additions by 2020 (Office of Energy Efficiency and Renewable Energy 2000). Cumulatively, this amounts to about 40 GW of DER capacity additions from 2000-2020. Figure ES-1 below compares the EIA forecast and DEER's assumed goal for new DER by 2020 while applying the same definition of DER to both. This figure illustrates that the EIA forecast is consistent with the overall DEER DER goal. For the purposes of this study, Berkeley Lab needed a target level of small-scale DER penetration upon which to hinge consideration of benefits and costs. Because the AEO2002 forecasted only 3.1 GW of cumulative additions from small-scale DER in the residential and commercial sectors, another approach was needed to estimate the small-scale DER target. The focus here is on small-scale DER technologies under 500 kW. The technology size limit is somewhat arbitrary, but the key results of interest are marginal additional costs and benefits around an assumed level of penetration that existing programs might achieve. Berkeley Lab assumes that small-scale DER has the same growth potential as large scale DER in AEO2002, about 38 GW. This assumption makes the small-scale goal equivalent to 380,000 DER units of average size 100 kW. This report lays out a framework whereby the consequences of meeting this goal might be estimated and tallied up. The framework is built around a list of major benefits and a set of tools that might be applied to estimate them. This study lists some of the major effects of an emerging paradigm shift away from central station power and towards a more dispersed and heterogeneous power system. Seventeen societal effects of small-scale DER are briefly summarized. Each effect is rated as high, medium or low, on three different scales that will help determine the optimal social investment. The three scales are: the magnitude of the economic benefit; the likelihood that the benefit can be monetized in efficient markets, i.e. internalized; and how tractable it might be to quantify each benefit analytically. Some of the modeling tools that may be used to estimate these effects are described in the Appendix

Evaluation Framework and Tools for Distributed Energy Resources

The Energy Information Administration's (EIA) 2002 Annual Energy Outlook (AEO) forecast anticipates the need for 375 MW of new generating capacity (or about one new power plant) per week for the next 20 years, most of which is forecast to be fueled by natural gas. The Distributed Energy and Electric Reliability Program (DEER) of the Department of Energy (DOE), has set a national goal for DER to capture 20 percent of new electric generation capacity additions by 2020 (Office of Energy Efficiency and Renewable Energy 2000). Cumulatively, this amounts to about 40 GW of DER capacity additions from 2000-2020. Figure ES-1 below compares the EIA forecast and DEER's assumed goal for new DER by 2020 while applying the same definition of DER to both. This figure illustrates that the EIA forecast is consistent with the overall DEER DER goal. For the purposes of this study, Berkeley Lab needed a target level of small-scale DER penetration upon which to hinge consideration of benefits and costs. Because the AEO2002 forecasted only 3.1 GW of cumulative additions from small-scale DER in the residential and commercial sectors, another approach was needed to estimate the small-scale DER target. The focus here is on small-scale DER technologies under 500 kW. The technology size limit is somewhat arbitrary, but the key results of interest are marginal additional costs and benefits around an assumed level of penetration that existing programs might achieve. Berkeley Lab assumes that small-scale DER has the same growth potential as large scale DER in AEO2002, about 38 GW. This assumption makes the small-scale goal equivalent to 380,000 DER units of average size 100 kW. This report lays out a framework whereby the consequences of meeting this goal might be estimated and tallied up. The framework is built around a list of major benefits and a set of tools that might be applied to estimate them. This study lists some of the major effects of an emerging paradigm shift away from central station power and towards a more dispersed and heterogeneous power system. Seventeen societal effects of small-scale DER are briefly summarized. Each effect is rated as high, medium or low, on three different scales that will help determine the optimal social investment. The three scales are: the magnitude of the economic benefit; the likelihood that the benefit can be monetized in efficient markets, i.e. internalized; and how tractable it might be to quantify each benefit analytically. Some of the modeling tools that may be used to estimate these effects are described in the Appendix

Evaluation Framework and Tools for Distributed Energy Resources

The Energy Information Administration's (EIA) 2002 Annual Energy Outlook (AEO) forecast anticipates the need for 375 MW of new generating capacity (or about one new power plant) per week for the next 20 years, most of which is forecast to be fueled by natural gas. The Distributed Energy and Electric Reliability Program (DEER) of the Department of Energy (DOE), has set a national goal for DER to capture 20 percent of new electric generation capacity additions by 2020 (Office of Energy Efficiency and Renewable Energy 2000). Cumulatively, this amounts to about 40 GW of DER capacity additions from 2000-2020. Figure ES-1 below compares the EIA forecast and DEER's assumed goal for new DER by 2020 while applying the same definition of DER to both. This figure illustrates that the EIA forecast is consistent with the overall DEER DER goal. For the purposes of this study, Berkeley Lab needed a target level of small-scale DER penetration upon which to hinge consideration of benefits and costs. Because the AEO2002 forecasted only 3.1 GW of cumulative additions from small-scale DER in the residential and commercial sectors, another approach was needed to estimate the small-scale DER target. The focus here is on small-scale DER technologies under 500 kW. The technology size limit is somewhat arbitrary, but the key results of interest are marginal additional costs and benefits around an assumed level of penetration that existing programs might achieve. Berkeley Lab assumes that small-scale DER has the same growth potential as large scale DER in AEO2002, about 38 GW. This assumption makes the small-scale goal equivalent to 380,000 DER units of average size 100 kW. This report lays out a framework whereby the consequences of meeting this goal might be estimated and tallied up. The framework is built around a list of major benefits and a set of tools that might be applied to estimate them. This study lists some of the major effects of an emerging paradigm shift away from central station power and towards a more dispersed and heterogeneous power system. Seventeen societal effects of small-scale DER are briefly summarized. Each effect is rated as high, medium or low, on three different scales that will help determine the optimal social investment. The three scales are: the magnitude of the economic benefit; the likelihood that the benefit can be monetized in efficient markets, i.e. internalized; and how tractable it might be to quantify each benefit analytically. Some of the modeling tools that may be used to estimate these effects are described in the Appendix