Christopher W. Karvetski

Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation.

Integration of Decision Analysis and Scenario Planning for Coastal Engineering and Climate Change

This paper develops a methodology for eliciting shifts in preference across future scenarios in the performance assessment of infrastructure policies and investments. The methodology quantifies the robustness of alternative portfolios across a variety of scenarios and identifies the scenarios that greatly affect the assessments. An innovation of the methodology is to elicit, for each scenario, only a few relative increases or decreases in importance of selected terms of the value function, which is more efficient than a full elicitation of the value function for each scenario. The identification of critical scenarios via our methodology can be used to focus resource-intensive and potentially costly modeling activities. The methodology integrates preference orders, centroid weights, and the Borda method. In a demonstration, the methodology assesses the relative sea level and other climate-change scenarios that could affect the performance of coastal protections.

Evaluating deep uncertainties in strategic priority-setting with an application to facility energy investments

A recent paper in this journal described the identification and integration of sources of risk in a systems engineering process model [Lambert, Jennings, and Joshi, Syst Eng 9(3) (2006), 187–198]. The earlier effort falls short in addressing sources of deep, nonprobabilistic uncertainty that should enter to strategic systems design and reengineering. Our new paper incorporates the earlier effort to a framework for evaluating which are the deep uncertainties that most influence a priority-setting among investments in large-scale systems with multiple stakeholders, and therefore warrant more investigation. The framework addresses that deep uncertainties are continuously discovered and reflective of diverse and unique stakeholder experiences, knowledge bases, and advocacy positions. Deep uncertainties are epistemic viewpoints across which the strategic priorities for investments will differ. The framework modifies existing tools of scenario analysis and multicriteria analysis to process and filter the deep uncertainties. The framework is demonstrated in an application to reengineering of an energy system for a defense installation where frequent outages are disruptive to scientific and other missions. The sources of deep uncertainty in the demonstration include regulatory, economic, environment, cyber-threat, and others. The investments include innovative microturbine and microgrid technologies. An example of a result is that international economic disruption is relatively more influential than cyber-threats to strategic priority-setting for investing in a microgrid at the particular installation. ©2012 Wiley Periodicals, Inc. Syst Eng 15

Prioritizing Infrastructure Investments in Afghanistan with Multiagency Stakeholders and Deep Uncertainty of Emergent Conditions

The Afghanistan National Development Strategy identified billions of dollars of needs for transportation, water, energy, telecommunications, and other necessary infrastructure development for the rebuilding of Afghanistan. With economic sustainability as a primary aim, the coordination and prioritization of investments has been a challenge in part because of Afghanistan’s volatile security situation along with the intricacies of the negotiating and coordinating efforts of numerous stakeholders. An understanding of the contributions of infrastructure systems and associated projects to the national development strategy is needed. This paper formulates a scenario-informed multicriteria approach to prioritize major project investments for infrastructure development subject to deep, nonprobabilistic uncertainties. The methods are inclusive of stakeholder values and accounts for deep uncertainties in governance, security, economy, environment, workforce, and other topics. The methods are applied in Afghanistan’s Nangarhar province to assist in the selection among twenty-seven candidate infrastructure projects that are vulnerable to potential refugee immigration among other emergent conditions. The paper describes the relationships of selected projects to strategic goals while facilitating collaboration among government and nongovernment investors, donors, technologists, and other stakeholders.

Climate change scenarios: risk and impact analysis for Alaska coastal infrastructure

Climate change has the potential to impose severe stress on coastal environments. Alaskan coastlines are especially vulnerable to erosion and other changes that have led to significant damage and threats to infrastructure, human health and safety, and economic prosperity. This paper describes an integration of scenario analysis with multi-criteria decision analysis to prioritise the vulnerability of communities for the development of infrastructure protection and other actions. The approach allows stakeholders to account for uncertainty in the prioritisation and also includes value judgements of the multiple relevant stakeholders. We present a case study that evaluates several climate change scenarios and formulates metrics for finding scenarios that most impact priorities. Scenarios including sea-level rise, increased frequency of forest fires, permafrost melting, and others are used. We find the increased frequency of forest fires to be the most upsetting scenario along with four communities that are identified as highly vulnerable and not sensitive to the scenarios.

Scenario-informed multiple criteria analysis for prioritizing investments in electricity capacity expansion

Planning the expansion and energy security of electricity capacity for a national electricity utility is a complex task in almost any economy. Planning is usually an iterative activity and can involve the use of large scale planning optimization systems accompanied by assessment of uncertain scenarios emerging from economic, technological, environmental, and regulatory developments. This paper applies a multiple criteria decision analysis to prioritize investment portfolios in capacity expansion and energy security while principally studying the robustness of the prioritization to multiple uncertain and emergent scenarios. The scenarios are identified through interaction with decision makers and stakeholders. The approach finds which scenarios most affect the prioritization of the portfolios and which portfolios have the greatest upside and downside potential across scenarios. The approach fosters innovation in the use of robust and efficient technologies, renewable energy sources, and cleaner energy fuels. A demonstration is provided for assessing the performance of technology portfolios constructed from investments in nine electricity generation technologies in Mexico.

Case studies of scenario analysis for adaptive management of natural resource and infrastructure systems

Management of natural resources and infrastructure systems for sustainability is complicated by uncertainties in the human and natural environment. Moreover, decisions are further complicated by contradictory views, values, and concerns that are rarely made explicit. Scenario analysis can play a major role in addressing the challenges of sustainability management, especially the core question of how to scan the future in a structured, integrated, participatory, and policy-relevant manner. In a context of systems engineering, scenario analysis can provide an integrated and timely understanding of emergent conditions and help to avoid regret and belated action. The purpose of this paper is to present several case studies in natural resources and infrastructure systems management where scenario analysis has been used to aide decision making under uncertainty. The case studies include several resource and infrastructure systems: (1) water resources (2) land-use corridors (3) energy infrastructure, and (4) coastal climate change adaptation. The case studies emphasize a participatory approach, where scenario analysis becomes a means of incorporating diverse stakeholder concerns and experience. This approach to scenario analysis provides insight into both high-performing and robust initiatives/policies, and, perhaps more importantly, influential scenarios. Identifying the scenarios that are most influential to policy making helps to direct further investigative analysis, modeling, and data-collection efforts to support the learning process that is emphasized in adaptive management.

Flood protection diversification to reduce probabilities of extreme losses.

Recent catastrophic losses because of floods require developing resilient approaches to flood risk protection. This article assesses how diversification of a system of coastal protections might decrease the probabilities of extreme flood losses. The study compares the performance of portfolios each consisting of four types of flood protection assets in a large region of dike rings. A parametric analysis suggests conditions in which diversifications of the types of included flood protection assets decrease extreme flood losses. Increased return periods of extreme losses are associated with portfolios where the asset types have low correlations of economic risk. The effort highlights the importance of understanding correlations across asset types in planning for large-scale flood protection. It allows explicit integration of climate change scenarios in developing flood mitigation strategy.

Probabilistic Coherence Weighting for Optimizing Expert Forecasts

Methods for eliciting and aggregating expert judgment are necessary when decision-relevant data are scarce. Such methods have been used for aggregating the judgments of a large, heterogeneous group of forecasters, as well as the multiple judgments produced from an individual forecaster. This paper addresses how multiple related individual forecasts can be used to improve aggregation of probabilities for a binary event across a set of forecasters. We extend previous efforts that use probabilistic incoherence of an individual forecasters subjective probability judgments to weight and aggregate the judgments of multiple forecasters for the goal of increasing the accuracy of forecasts. With data from two studies, we describe an approach for eliciting extra probability judgments to (i) adjust the judgments of each individual forecaster, and (ii) assign weights to the judgments to aggregate over the entire set of forecasters. We show improvement of up to 30% over the established benchmark of a simple equal-weighted averaging of forecasts. We also describe how this method can be used to remedy the “fifty--fifty blip” that occurs when forecasters use the probability value of 0.5 to represent epistemic uncertainty.

Energy Security for Industrial and Military Installations: Emergent Conditions that Influence the Strategic Selection of Technologies

We describe recent efforts integrating scenario analysis with multiple criteria decision analysis in support of strategic planning for the energy security of industrial and military installations. Energy security is an increasingly important issue for industrial and military installations. Disruptions of the grid and other outages for key buildings, facilities, and entire installations jeopardize critical activities and missions. Cost and supply volatilities of traditional energy sources and backup technologies increase the need for innovation in meeting energy demands. Part of such demands should be met with renewable energy sources. Each of the hundreds of installations of a large industrial or military organization presents a unique challenge in the attainment of energy security goals. This Chapter describes a framework to highlight what science, engineering, and other conditions most influence the planning of strategic investments in innovation for energy security. The framework aims to avoid surprises that could result from a failure to account systematically for the emergent conditions that affect industrial and military installations, including emergent conditions of regulation, technologies, economics, geopolitics, environment, and other topics. Science, engineering, and other investigative resources can be focused on the future conditions that most matter to the selection of technologies and their operations plans.