2016 INFORMS Annual Meeting Program

SA09

INFORMS Nashville – 2016

SA10 103C-MCC Optimizing Distributed Energy Generation I Sponsored: Energy, Natural Res & the Environment, Energy II Other Sponsored Session Chair: Alexandra M Newman, Colorado School of Mines, 1, Golden, CO, 1, United States, anewman@mines.edu 1 - Hybrid Energy System Dispatch Strategy For A Forward Operating Base Mark Husted, Colorado School of Mines, mhusted@mines.edu Given a set of systems (i.e., batteries, diesel generators, and photovoltaics), we determine a dispatch strategy for a forward operating base, isolated from the grid. This cost-minimizing strategy subscribes to minute-level fidelity over a 24-hour time horizon given the expected demand profile and the anticipated solar generation. Operational constraints include (i) ramp-up and ramp-down and minimum up and down times of the generators, (ii) spinning reserve levels, and (iii)other interoperability requirements among the systems. We show how our model results improve over traditional rules of thumb used for real-time dispatch. 2 - A Capacity Expansion Model For Energy Planning For Turkey Muhammed Sutcu, Assistant Professor, Abdullah Gul University, Sumer Campus, Erkilet Bulvari, Kayseri, 38060, Turkey, muhammed.sutcu@agu.edu.tr, Tugba Degirmenci There has been a considerable effort to raise the share of their renewable energy (RE) sources in the total sum to reach an environmental sustainability. This study addresses the question of what level of each type of RE should actually be provided year by year to maximize the total productions by minimizing the associated costs for RE policies of Turkey. With this goal on mind, a multistage optimization model for years 2016-2023 is constructed and solved with the interpretation of the results throughout the study. 3 - Integrated Model For Power Interruption Contracts Lakshmi Palaparambil Dinesh, University of Cincinnati, 601 Mc Alpin Avenue, Apartment 5, Cincinnati, OH, 45220, United States, lakshmi603@gmail.com, Uday S Rao, Jeffrey D. Camm, Kenneth Skinner Demand response is changing electricity usage based on a change in price of electric power. We study a demand response program where residential customers participate. Each customer has to sign up for a contract to enroll in the program. We develop a model that helps to decide which power unit to turn on or off, which customers to cut power during peak demand hours, and what contract parameters to use while designing contracts between the supplier and residential customers. The proposed model leads to higher overall costs savings for the power supplier compared to the current model used in practice. 4 - Optimal Sizing Of An EV Parking Facility Within A Microgrid Ebrahim Mortaz, Auburn University, 115 N. Debardeleben St. Apt 29, Auburn, AL, 36830, United States, emortaz@auburn.edu Jorge F Valenzuela Integrating the provided energy and storage capacity by the electric vehicles into the microgrid reduces the cost of electricity supply. In this talk, we assume that a grid-connected microgrid is set to transform an EV parking facility into a large energy storage resource by investing on the V2G technology. We propose a mathematical model that aims to determine the optimal number of V2G stations in the parking facility by minimizing the total cost of the microgrid. The results show that the investment in the V2G technology is an enhancement to the long- term economics of microgrids. SA11 104A-MCC Cliques and Clique Relaxations Sponsored: Optimization, Network Optimization Sponsored Session Chair: Eugene Lykhovyd, Texas A&M University, College Station, TX, United States, lykhovyd@tamu.edu 1 - Exact Algorithms For The Minimum S-Club Partitioning Problem Oleksandra Yezerska, Texas A&M Univeristy, Fort Worth, TX, United States, yaleksa@tamu.edu Graph clustering (partitioning) is a helpful tool in understanding complex systems and analyzing their structure and internal properties. An $s$-club is a distance- based relaxation of a clique and is formally defined as a subset of vertices inducing a subgraph with a diameter of at most $s$. We study the minimum $s$- club partitioning problem, which is to partition the graph into a minimum number of $s$-club clusters. Integer programming techniques and combinatorial branch-and-bound framework are employed to develop exact algorithms to solve this problem. We also compare the computational performance of the proposed algorithms for the special case of $s=2$ on a test-bed of real-life graphs.

3 - A Reformulation Of The Appointment Scheduling Problem With Customer Choice Behavior And Multiple Customer Types Cem Aydin, Koc University, Dept of Industrial Engineering, Istanbul, Turkey, cemaydin@ku.edu.tr, Alp Aribal, Cansu Erol, Begum Tuglu In this paper, we propose a new formulation to the appointment scheduling problem with customer choice behavior and multiple customer classes. Using this new formulation and an approximation of the state space, we find an upper bound to the total expected revenue. We exploit the special structure created by our new formulation to present an efficient algorithm that can find this upper bound. We test methods commonly used in practice using our upper bound to rate their performance and show that performances of traditional methods decay as problem size increases. SA09 103B-MCC Balancing Water Use for Food and Energy Sponsored: Energy, Natural Res & the Environment I Environment & Sustainability Sponsored Session Chair: Hayri Onal, University of Illinois, 305 Mumford Hall, 1301 W. Gregory Dr., Urbana, IL, 61801, United States, h-onal@illinois.edu 1 - A Robust Planning Decision Model For Smart Water System Mengqi Hu, University of Illinois at Chicago, 842 W. Taylor St., 3023 ERF, Chicago, IL, 60607, United States, mhu@uic.edu, Afshin Ghassemi Water is a critical resource for different sections and people’s everyday life. In this research, we propose a robust planning decision model for smart water system including sources, water plants, end users and waste water systems. In the smart water system, the concepts of dynamic pricing and onsite inventory and 3rd-party water plant are explored. Various levels of uncertainties from both water demand and pipeline efficiencies are considered. Three sets of experiments are developed to test the effectiveness of the proposed decision model. It is concluded that our proposed model provides a platform to transform novel smart grid concepts to renovate the existing water infrastructure. 2 - Assessment Of Ecosystem Services In A Semi-arid Agriculture-dominant Area: Framework And Case Study Yihsu Chen, University of California, Santa Cruz, Yihsu Chen, Ramesh Dhungel, Rudy Maltos, Kumar Sivakumaran, Andres Aguilar, Thomas Harmon Evaluating ecosystem services is difficult as the services are not traded at an open market. In this study, we developed a framework that allows for assessing the effectiveness and implied costs of ecosystem services provided by a restored SJR (San Joaquin River) in a semi-arid agriculture-dominant area. This is done by explicitly linking economics-based farmers’ model with a reduced-form hydrological model that is loosely coupled to a physical-based stream-temperature model. We quantify the lower bound of the short-run economic costs and show that current mandated flows are unlikely to have a meaningful impact on restoring fish population. 3 - Predictive Analytics For Sustainable Water Consumption Ellen Wongso, Student, Purdue University, West Lafayette, IN, 47906, United States, ewongso@purdue.edu, Zijian He, Roshanak Nateghi According to a recent report by the EPA, 40 states will experience water shortages in the coming decade. Climate change and increased consumption trends will likely exacerbate the current water scarcity issues. Access to clean water is a basic human right and is an essential element is ensuring energy and food security. There is therefore a critical need to identify the main drivers of consumption to promote sustainable use. Previous research on water sustainably has been local in scope and mostly from a management science perspective. In this research we will leverage advanced statistical learning methods to identify the main drivers of water usage in the US. 4 - Scheduling Water Reuse In The Food Industry: Theory And Application Renzo Akkerman, Technical University of Munich, Munich, 80333, Germany, renzo.akkerman@tum.de Sai Jishna Pulluru Water considerations are increasingly relevant in the planning and scheduling of production activities in the food industry. This includes the reuse of various water streams and their possible treatment or regeneration. We develop a model for production scheduling that integrates water flows and their possible treatment for reuse. We perform a numerical study to analyze the performance of the modelling approach, and also apply the model in a case application from the dairy industry. Overall, the results demonstrate the relevance of the modelling approach and its computational performance. Furthermore, the work provides managerial insights for increased water efficiency in the food industry.

20