Exploring a Direct Policy Search Framework for Multiobjective Optimization of a Microgrid Energy Management System

With an increasing focus on integration of distributed energy resources, it is likely that microgrids will proliferate globally. Microgrid systems will be expected to achieve multiple stakeholder objectives, motivating the study of microgrid operations using a multiobjective framework. A multiobjective perspective has the potential balance the trade-offs implicit to efficient use of available resources. To address this challenge, this paper proposes a simulation based parametric approach for multiobjective optimization for microgrid energy management. The methodology generates a Pareto-approximate set of control policies, to provide a microgrid controller with diverse alternative strategies for utilizing resources to balance competing objectives. The policies also help to illustrate the complex relationships between the objectives, and the consequences of compromises across performance. The methodology is implemented on a test microgrid and the potential benefits are demonstrated with a set of illustrative case studies

Operational Research in Education

Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions

Updating, Upgrading, Refining, Calibration and Implementation of Trade-Off Analysis Methodology Developed for INDOT

As part of the ongoing evolution towards integrated highway asset management, the Indiana Department of Transportation (INDOT), through SPR studies in 2004 and 2010, sponsored research that developed an overall framework for asset management. This was intended to foster decision support for alternative investments across the program areas on the basis of a broad range of performance measures and against the background of the various alternative actions or spending amounts that could be applied to the several different asset types in the different program areas. The 2010 study also developed theoretical constructs for scaling and amalgamating the different performance measures, and for analyzing the different kinds of trade-offs. The research products from the present study include this technical report which shows how theoretical underpinnings of the methodology developed for INDOT in 2010 have been updated, upgraded, and refined. The report also includes a case study that shows how the trade-off analysis framework has been calibrated using available data. Supplemental to the report is Trade-IN Version 1.0, a set of flexible and easy-to-use spreadsheets that implement the tradeoff framework. With this framework and using data at the current time or in the future, INDOT’s asset managers are placed in a better position to quantify and comprehend the relationships between budget levels and system-wide performance, the relationships between different pairs of conflicting or non-conflicting performance measures under a given budget limit, and the consequences, in terms of system-wide performance, of funding shifts across the management systems or program areas

A review of asset management literature on multi-asset systems

This article gives an overview of the literature on asset management for multi-unit systems with an emphasis on two multi-asset categories: fleet (a system of homogeneous assets) and portfolio (a system of heterogeneous assets). As asset systems become more complicated, researchers have employed different terms to refer to their specific problems. With an objective to facilitate readers in searching conducive studies to their interests, this paper establishes a novel classification scheme for multi-unit systems in accordance with essential features such as diversity of assets and intervention options. Moreover, discerning differences in characteristics between cross-component and cross-asset interactions, we select three types of potential multi-component dependencies (performance, stochastic, and resource) and extend their notions to be applicable to multi-asset systems. The investigation into these dependencies enables the identification of problems that could exist in real industrial settings but are yet to be determined in academia. Ultimately, we delve into modelling approaches adopted by previous researchers. This comprehensive information allows us to offer the insights into the current trends in multi-asset maintenance. We expect that the output of this review paper will not only stress research gaps on multi-asset systems, but more importantly help systematise future studies on this aspect

Housing and Community Development

Researchers in housing and community development design and evaluate policies regarding access to attractive, affordable and sustainable housing and improving the social, physical and economic infrastructure of communities, especially those in the urban core. Practitioners in this field confront political considerations, administrative guidelines and limited funding. Decision science can increase the efficiency and effectiveness of market-rate housing development and provide support for policy responses to issues such as affordable housing, race and class segregation, ineffective and/or inequitable economic development, and sustainable development. This research spans many disciplines, including systems modeling, urban economics, multi-criteria decision modeling, stochastic models and decision support systems, and is often interdisciplinary and applied in nature. A common thread in this work is the need to explicitly address the needs of multiple stakeholders, to capture the public and private nature of housing, and to incorporate best-available evidence regarding markets, policies and impacts of housing and community development. We describe the policy context for this work, review previous research through the lens of descriptive, prescriptive and decision support models, and identify important limitations to work in this area to date. We then describe diverse opportunities for research in this area that can address current policy concerns such as sustainable development, post-disaster reconstruction and individual and group decision support

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use

Multi criteria decision support system for watershed management under uncertain conditions, A

2012 Summer.Includes bibliographical references.Nonpoint source (NPS) pollution is the primary cause of impaired water bodies in the United States and around the world. Elevated nutrient, sediment, and pesticide loads to waterways may negatively impact human health and aquatic ecosystems, increasing costs of pollutant mitigation and water treatment. Control of nonpoint source pollution is achievable through implementation of conservation practices, also known as Best Management Practices (BMPs). Watershed-scale NPS pollution control plans aim at minimizing the potential for water pollution and environmental degradation at minimum cost. Simulation models of the environment play a central role in successful implementation of watershed management programs by providing the means to assess the relative contribution of different sources to the impairment and water quality impact of conservation practices. While significant shifts in climatic patterns are evident worldwide, many natural processes, including precipitation and temperature, are affected. With projected changes in climatic conditions, significant changes in diffusive transport of nonpoint source pollutants, assimilative capacity of water bodies, and landscape positions of critical areas that should be targeted for implementation of conservation practices are also expected. The amount of investment on NPS pollution control programs makes it all but vital to assure the conservation benefits of practices will be sustained under the shifting climatic paradigms and challenges for adoption of the plans. Coupling of watershed models with regional climate projections can potentially provide answers to a variety of questions on the dynamic linkage between climate and ecologic health of water resources. The overarching goal of this dissertation is to develop a new analysis framework for the development of optimal NPS pollution control strategy at the regional scale under projected future climate conditions. Proposed frameworks were applied to a 24,800 ha watershed in the Eagle Creek Watershed in central Indiana. First, a computational framework was developed for incorporation of disparate information from observed hydrologic responses at multiple locations into the calibration of watershed models. This study highlighted the use of multiobjective approaches for proper calibration of watershed models that are used for pollutant source identification and watershed management. Second, an integrated simulation-optimization approach for targeted implementation of agricultural conservation practices was presented. A multiobjective genetic algorithm (NSGA-II) with mixed discrete-continuous decision variables was used to identify optimal types and locations of conservation practices for nutrient and pesticide control. This study showed that mixed discrete-continuous optimization method identifies better solutions than commonly used binary optimization methods. Third, the conclusion from application of NSGA-II optimization followed by development of a multi criteria decision analysis framework to identify near-optimal NPS pollution control plan using a priori knowledge about the system. The results suggested that the multi criteria decision analysis framework can be an effective and efficient substitute for optimization frameworks. Fourth, the hydrologic and water quality simulations driven by an extensive ensemble of climate projections were analyzed for their respective changes in basin average temperature and precipitation. The results revealed that the water yield and pollutants transport are likely to change substantially under different climatic paradigms. And finally, impact of projected climate change on performance of conservation practice and shifts in their optimal types and locations were analyzed. The results showed that performance of NPS control plans under different climatic projections will alter substantially; however, the optimal types and locations of conservation practices remained relatively unchanged

An integrated framework to support sustainable electricity planning

The changes in the electricity sector along with the need for sustainable development required traditional electricity planning to expand beyond pure financial analysis and even beyond direct environmental impact analysis. The electricity planner has now the task of designing electricity strategies for the future with the view of enhancing the financial performance of the sector while simultaneously addressing environmental and social concerns. However, the integration of the relevant dimensions of sustainable electricity planning poses important challenges to researchers. In addition, to properly deal with the increasing use of renewable energy sources of variable output, traditional optimisation models must be able to integrate the short term operational planning and dispatching process with the long range planning models. This paper proposes a new framework to sustainable electricity planning, based on optimisation models for electricity power planning combined with participatory methodologies for addressing the social dimension of the problem. The effective implementation of this framework is demonstrated for a real case study based on the Portuguese electricity system. The research started from the presentation of electricity generation scenarios for 2020 drawn from a mixed integer linear optimization model. These scenarios were then characterized under different social, economic and environmental impacts, and evaluated according to a multicriteria procedure based on experts’ inputs.This work was financed by: the QREN – Operational Programme for Competitiveness Factors –the EU – European Regional Development Fund and National Funds – Portuguese Foundation for Science and Technology, under Project FCOMP-01-0124-FEDER-011377 and Project Pest- OE/EME/UI0252/2011

Search based software engineering: Trends, techniques and applications

© ACM, 2012. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version is available from the link below.In the past five years there has been a dramatic increase in work on Search-Based Software Engineering (SBSE), an approach to Software Engineering (SE) in which Search-Based Optimization (SBO) algorithms are used to address problems in SE. SBSE has been applied to problems throughout the SE lifecycle, from requirements and project planning to maintenance and reengineering. The approach is attractive because it offers a suite of adaptive automated and semiautomated solutions in situations typified by large complex problem spaces with multiple competing and conflicting objectives. This article provides a review and classification of literature on SBSE. The work identifies research trends and relationships between the techniques applied and the applications to which they have been applied and highlights gaps in the literature and avenues for further research.EPSRC and E