2016 INFORMS Annual Meeting Program

MA04

INFORMS Nashville – 2016

MA05 101E-MCC Remuneration of Flexibility in Electricity Markets Sponsored: Energy, Natural Res & the Environment, Energy I Electricity Sponsored Session Chair: Anthony Papavasiliou, CORE, UCL, Voie du Roman Pays 34, Louvain la Neuve, B-1348, Belgium, tpapva@hotmail.com 1 - A Revenue Adequate, Cost Recovering, Uniform Pricing Scheme For Wind Generation Golbon Zakeri, University of Acukland, g.zakeri@auckland.ac.nz Geoff Pritchard, Mette Bjorndal, Endre Bjorndal In 2010, Pritchard et. al proposed a stochastic program that would accommodate absorbing electricity generation from wind into an electricity market. We will present a strict improvement over this mechanism which is based on uniform pricing, is revenue adequate in every scenario, recovers cost for each generator in expectation, is incentive compatible and displays a number of other desirable properties. 2 - Operating Reserve Demand Curves For Improved Pricing In We present a probabilistic method for determining operating reserve demand curves (ORDCs) in electricity markets, accounting for the uncertainty in wind power forecasts. We present case studies analyzing how ORDCs influence incentives for short-term operations as well as long-term generation expansion in electricity markets with increasing shares of renewable energy. Finally, we discuss to what extent ORDCs reward flexible resources through improved pricing of energy and reserves. 3 - Ramp Capability Pricing: Environmental, Economic And Reliability Outcomes In Markets With High Penetration Of Renewables And Flexible CCS Plants Dalia Patino Echeverri, Assistant Professor, Duke University, 9 Circuit Drive, Box 90328, Durham, NC, 27708, United States, dalia.patino@duke.edu, Rubenka Bandyopadhyay Ramp Capability (RC) pricing, recently implemented by MISO, is expected to improve economics and reliability by adequately compensating flexible ramping resources. Coal-fired power plants retrofit with flexible Carbon Capture and Storage (CCS) systems, would allow air emissions reductions and improved system ramping capability. This paper explores the effects of dispatching CCS in a market with RC products. A modified Unit Commitment/Economic Dispatch (UC/ED) with CO2 emissions constraint and RC pricing, simulates 10-minute, annual operations of a scaled version of the MISO power generation fleet, to estimate changes in generators revenue, systems costs, reliability and air emissions. 4 - Deterministic Market Designs With Efficient Scheduling Of Flexible Ramping Products Stefanos Delikaraoglou, Technical University of Denmark, Elektrovej, Building 325, room 105, Kgs. Lyngby, 2800, Denmark, stde@dtu.dk, Yves Smeers, Anthony Papavasiliou, Pierre Pinson The variable and uncertain nature of stochastic renewables calls for revised market designs to optimally allocate available flexibility between energy and ramping services. Unlike stochastic dispatch models that endogenously co- optimize these services, deterministic models require the explicit definition of ramping products, e.g., CAISO market design. However, these products pertain only to capacity and thus disregard the energy cost from the deployment of flexible resources. Contrary to existing penalty-based heuristics, we propose a systematic approach, using nested Benders decomposition, to bring the deterministic dispatch close to the stochastic ideal in terms of costs and prices. Electricity Markets With Renewable Energy Audun Botterud, Argonne National Laboratory, abotterud@anl.gov, Zhi Zhou, Todd Levin

2 - Vungle Inc. Improves Monetization Using Data Analytics Ioannis Fragkos, Erasmus University, Burgemeester Oudlaan 50, Rotterdam, Netherlands, fragkos@rsm.nl, Bert De Reyck, Yael S Grushka-Cockayne, Casey Lichtendahl, Hammond Guerin Big data have enabled firms to customize their services to unprecedented levels of granularity. In mobile advertising, once a customer enters the network, the ad- serving decision must be made in milliseconds. In this work, we describe the design and implementation of an algorithm we developed for Vungle Inc., one of the largest global mobile ad networks, that incorporates machine learning methods to make personalized ad-serving decisions. When compared to the company’s legacy algorithm, our algorithm generated a 23% lift, which represents a $1 million increase in monthly revenue. MA04 101D-MCC Low-Carbon Power Sector: Policy and Technology Analysis Sponsored: Energy, Natural Res & the Environment, Energy I Electricity Sponsored Session Chair: Afzal Siddiqui, University College London, Department of Statistical Science, London, WC1E 6BT, United Kingdom, afzal.siddiqui@ucl.ac.uk 1 - Strategic Offering Of A Flexible Producer Imbalances caused by intermittent renewable generation may give an opportunity to a strategic producer to exert market power. We study offering strategies of a flexible producer in day-ahead and intraday markets using a bi-level model in which the upper-level represents the profit maximization of the producer and the lower-level problems clear both markets sequentially. Using data from the Nordic power market, we find that the flexible producer can increase its profit by withholding production and by causing transmission grid congestion in both markets. Moreover, we compare the welfare impacts of the strategies to those of perfect competition and the dispatch policies in Morales et al. (2014). 2 - Power And Heat Market Model Vilma Virasjoki, Aalto University, Espoo, Finland, vilma.virasjoki@aalto.fi, Afzal Siddiqui, Behnam Zakeri, Ahti Salo Power markets are changing, i.a. due to an increasing share of renewable energy. This will also have effects on combined heat and power (CHP) plants and further on the district heating (DH) sector. It is thus essential to understand the financial and technical interrelations of these asymmetrically regulated sectors. We use complementarity modelling to study this linkage and give a numerical example using the Nordic energy system. We model the power system as a mix of DC and DC load flow linearized AC lines. We formulate perfect competition and Cournot oligopoly models and use GAMS to solve the market equilibrium. The results provide insights e.g. into the market power impacts on CHP and DH operations. 3 - Market Power In Electricity Markets In South-east Europe Verena Viskovic, PhD Student, UCL, 1-19 Torrington Place, 2 Cubitt Street, London, United Kingdom, verena.viskovic.13@ucl.ac.uk, Yihsu Chen, Afzal Siddiqui, Makoto Tanaka We examine the effect of market power in electricity and permits markets via single and bi-level model. We analyse potential scenarios of ownership structure in the post-privatisation phase in South-East Europe. We expect producers with market power to be able to influence electricity prices through permits market. In addition, we study the effect of virtual divestitures in mitigating market power. 4 - Variability Management In Long-term Investment Models Lina Reichenberg, Chalmers University of Technology, lina.reichenberg@chalmers.se, Sonja Wogrin, Afzal Siddiqui Time representation in large-scale energy investment models has been typically governed by variability in demand. However, as CO2 abatement is becoming a stronger driving force, variability enters also on the generation side. As a response to this, two families of alternative time reduction methods have been developed: one based on representative days and the other on using time slices based on variable resources. We investigate the performance of these two families of methods, in terms of accuracy in predicting the system plant capacity mix and CPU time. Tuomas Rintamäki, Aalto University, Espoo, Finland, tuomas.rintamaki@aalto.fi, Afzal Siddiqui, Ahti Salo

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