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Bucharest PowerTech Conference

作者： Capitanescu, Florin Rosehart, William Wehenkel, Louis Univ Liege Dept Elect Engn & Comp Sci B-4000 Liege Belgium Univ Calgary Dept Elect Engn Calgary AB T2N 1N4 Canada

ISBN: (纸本)9781424422340

This paper focuses on optimal power flow (OPF) computations in which no more than a pre-specified number of controls are allowed to move. The benchmark formulation of this OPF problem constitutes a mixed integer nonlinear programming (MINLP) problem. To avoid the prohibitive computational time required by classical MINLP approaches to provide a (potentially sub-optimal) solution, we propose instead two alternative approaches. The first one consists in reformulating the MINLP problem as a mathematical program with equilibrium constraints (MPEC). The second approach includes in the classical OPF problem a nonlinear constraint which approximates the integral constraint limiting the number of control variables movement. Both approaches are solved by an interior point algorithm (IPA), slightly adapted to the particular characteristics of each approach. We provide numerical results with the proposed approaches on two test systems and for two practical problems: minimum cost to remove thermal congestion, and minimum cost of load curtailment to restore a feasible equilibrium point.

关键词： mathematical programming with equilibrium constraints nonlinear programming optimal power flow

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Generalized stationary points and an interior-point method for mathematical programs with equilibrium constraints

Generalized stationary points and an interior-point method f...

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3rd International Conference on Complementarity Problems

作者： Liu, XW Sun, J Natl Univ Singapore Sch Business Singapore 117548 Singapore Hebei Univ Technol Dept Appl Math Tianjin Peoples R China Natl Univ Singapore Singapore MIT Alliance Singapore 117548 Singapore

Generalized stationary points of the mathematical program with equilibrium constraints (MPEC) are studied to better describe the limit points produced by interior point methods for MPEC. A primal-dual interior-point method is then proposed, which solves a sequence of relaxed barrier problems derived from MPEC. Global convergence results are deduced under fairly general conditions other than strict complementarity or the linear independence constraint qualification for MPEC (MPEC-LICQ). It is shown that every limit point of the generated sequence is a strong stationary point of MPEC if the penalty parameter of the merit function is bounded. Otherwise, a point with certain stationarity can be obtained. Preliminary numerical results are reported. which include a case analyzed by Leyffer for which the penalty interior-point algorithm failed to find a stationary point.

关键词： global convergence interior-point methods mathematical programming with equilibrium constraints stationary point

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Sustainable Distribution Network Planning Considering Multi-Energy Systems and Plug-In Electric Vehicles Parking Lots

Sustainable Distribution Network Planning Considering Multi-...

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作者： Nilufar Neyestani UNIVERSIDADE DA BEIRA INTERIOR

学位级别：博士

Among all resources introduced by the evolution of smart grid, multi-energy systems and plug- in electric vehicles are the two main challenges in research topics. Although, these resources bring new levels of uncertainties to the system, their capabilities as flexible demand or stochastic generation can enhance the operability of system. When the concept of multi- energy systems and plug-in electric vehicles (PEV) parking lots are merged in a distribution system, the demand estimation may vary significantly. As the main feed of planning process, it is critical to estimate the most accurate amount of required demand. Therefore, three stages of load pattern should be extracted taking into account the demand substitution between energy carriers, demand affected by home-charging PEVs, and parking lot presence in system. The presence of PEVs in a multi-energy system oblige other requirements (i. e. fueling system) that should be provided in the system, including charging stations. However, the electric base of PEVs adds to the responsibilities of the system operator to think about the best solution to provide the required services for PEVs and utilize their potentials in a multi-energy concept. However, the socio-technical behavior of PEV users makes it difficult for the system operator to be able to manage the potential sources of PEV batteries. As a result, this study tries to raise the solution to new problems that will occur for the system planners and operators by the future components of the system. In this thesis, various aspects of integrating PEVs in a multi-energy system is studied. Firstly, a carrier-based demand response program is proposed for the multi-energy system with the technologies on the demand side to switch between the carriers for providing their services. Then, a comprehensive study on the issues regarding the modeling of the PEVs in the system are conducted including modeling their uncertain traffic behavior, modeling the preferences of vehicle

关键词： Charging stations flexible load multi-energy systems, multi-energy demand mathematical programming with equilibrium constraints mixed integer linear programming network planning parking lots plug-in electric vehicles

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Electricity Market Participation and Investment Planning Frameworks for Energy Storage Systems

Electricity Market Participation and Investment Planning Fra...

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作者： Alharbi, Hisham University of Waterloo

学位级别：博士

The recent trend of increasing share of renewable energy sources (RES) in the generation mix has necessitated new operational and planning studies because of the high degree of uncertainty and variability of these sources. RES such as solar photovoltaic and wind generation are not dispatchable, and when there is excess energy supply during off-peak hours, RES curtailment is required to maintain the demand-supply balance. Furthermore, RES are intermittent resources which have introduced new challenges to the provision of ancillary services that are critical to maintaining the operational reliability of power systems. Energy storage systems (ESS) play a pivotal role in facilitating the integration of RES to mitigate the aforementioned issues. Therefore, there is a growing interest in recent years to examine the potential of ESS in the future electricity grids. This research focuses on developing market participation and investment planning frameworks for ESS considering different ownership structures. First, a novel stochastic planning framework is proposed to determine the optimal battery energy storage system (BESS) capacity and year of installation in an isolated microgrid using a novel representation of the BESS energy diagram. A decomposition-based approach is proposed to solve the problem of stochastic planning of BESS under uncertainty. The optimal decisions minimize the net present value of total expected costs over a multi-year horizon considering optimal BESS operation using a novel matrix representing BESS energy capacity degradation. The proposed approach is solved in two stages as mixed integer linear programming (MILP) problems; the optimal ratings of the BESS are determined in the first stage, while the optimal installation year is determined in the second stage. Extensive studies considering four types of BESS technologies for deterministic, Monte Carlo Simulations, and stochastic cases are presented to demonstrate the effectiveness of the proposed app

关键词： ancillary services battery bi-level optimization electricity markets energy storage investment mathematical programming with equilibrium constraints microgrid mileage planning pumped hydro regulation market stochastic strategic bidding

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Robust Strategic Bidding in Auction-Based Markets

Robust Strategic Bidding in Auction-Based Markets

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作者： Bruno Fanzeres dos Santos Pontificia Universidade Catolica do Rio de Janeiro

学位级别：博士

We propose an alternative methodology to devise profit-maximizing stra- tegic bids under uncertainty in markets endowed with a sealed-bid uniform- price auction with multiple divisible products. The optimal strategic bid of a price maker agent largely depends on the knowledge (information) of the rivals' bidding strategy. By recognizing that the bid of rival competitors may devi- ate from the equilibrium and are of difficult probabilistic characterization, we proposed a two-stage robust optimization model with equilibrium constraints to devise an risk-averse strategic bid in the auction. The proposed model is a trilevel optimization problem that can be recast as a particular instance of a bilevel program with equilibrium constraints. Reformulation procedures are proposed to construct a single-level-equivalent formulation suitable for co- lumn and constraint generation (CCG) algorithm. Differently from previously reported works on two-stage robust optimization, our solution methodology does not employ the CCG algorithm to iteratively identify violated scenarios for the uncertain factors, which in this thesis are obtained through continuous variables. In the proposed solution methodology, the CCG is applied to iden- tify a small subset of optimality conditions for the third-level model capable of representing the auction equilibrium constraints at the optimum solution of the master (bidding) problem. A numerical case study based on short-term electricity markets is presented to illustrate the applicability of the proposed robust model. Results show that even for the case where an impression of 1% on the rivals' offer at the Nash equilibrium is observed, the robust solution provides a non-negligible risk reduction in out-of-sample analysis.

关键词： Sealed-Bid Uniform-Price Auction Strategic Bidding mathematical programming with equilibrium constraints Column-and-Contraint Generation Day-Ahead Electricity Markets

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Tri-Level Adaptive Robust Optimization for the Optimal Charging Coordination of EVs Considering Grid Impact

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IEEE ACCESS 2024年 12卷 169755-169767页

作者： Silva, Jessica Alice A. Lopez, Juan Camilo Arias, Nataly Banol Terada, Lucas Zenichi Rider, Marcos J. Univ Estadual Campinas UNICAMP Sch Elect & Comp Engn FEEC Dept Syst & Energy DSE BR-13083852 Campinas SP Brazil Univ Twente Dept Elect Engn Math & Comp Sci EEMCS NL-7522 NB Enschede Netherlands

The rapid integration of electric vehicles (EVs) into power grids introduces substantial operational challenges, particularly in managing the grid and ensuring efficient energy distribution. Addressing these issues, this paper presents a novel tri-level adaptive robust optimization model for EV charging coordination, explicitly considering active and reactive power control (RPC) and its impact on the distribution network. The first level optimizes the operation of unbalanced three-phase AC distribution systems through economic dispatch of distributed generation (DG) units, modeled using mathematical programming with equilibrium constraints (MPEC). The second level minimizes the energy non-supplied (ENS) to EVs during charging, considering both grid constraints and DG dispatches. The third level introduces an adaptive robust approach to handle uncertainties related to demand, renewable energy generation, and EV initial states of charge. This tri-level model, formulated as a min-max-min optimization, is solved using the column-and-constraint generation (C&CG) method. Validation on 25-node and 123-node systems equipped with dispatchable DG units, photovoltaic systems, and an EV fleet managed by a charging point operator (CPO) demonstrates the model's ability to mitigate uncertainties and balance conflicting interests between the CPO/aggregator and the distribution system operator (DSO). The results show that incorporating RPC reduces grid impact and ENS by up to 17.26% in the 25-node system and 30.68% in the 123-node system, highlighting the effectiveness of the proposed approach in enhancing grid resilience amidst increasing EV penetration. This work offers a comprehensive and scalable solution for private charging infrastructures, providing critical insights into improving grid resilience, optimizing EV charging operations, and effectively balancing the interests of both the CPO/aggregator and the DSO.

关键词： Adaptation models Renewable energy sources Reactive power control Uncertainty Adaptive systems Linear programming Electric vehicle charging Voltage control Resilience mathematical programming Electric vehicle fleets mathematical programming with equilibrium constraints optimal charging coordination tri-level adaptive robust optimization

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Global Product Design Platforming: A Comparison of Two equilibrium Solution Methods

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JOURNAL OF MECHANICAL DESIGN 2023年第6期145卷 061702-061702页

作者： Case, Sarah Michalek, Jeremy J. Whitefoot, Kate S. Carnegie Mellon Univ Mech Engn Pittsburgh PA 15213 USA Carnegie Mellon Univ Mech Engn Engn & Publ Policy Civil & Environm Engn by Courtesy Pittsburgh PA 15213 USA Carnegie Mellon Univ Mech Engn Engn & Publ Policy Pittsburgh PA 15213 USA

Global product platforms can reduce production costs through economies of scale and learning but may decrease revenues by restricting the ability to customize for each market. We model the global platforming problem as a Nash equilibrium among oligopolistic competing firms, each maximizing its profit across markets with respect to its pricing, design, and platforming decisions. We develop and compare two methods to identify Nash equilibria: (1) a sequential iterative optimization (SIO) algorithm, in which each firm solves a mixed-integer nonlinear programming problem globally, with firms iterating until convergence;and (2) a mathematical program with equilibrium constraints (MPEC) that solves the Karush Kuhn Tucker conditions for all firms simultaneously. The algorithms' performance and results are compared in a case study of plug-in hybrid electric vehicles where firms choose optimal battery capacity and whether to platform or differentiate battery capacity across the US and Chinese markets. We examine a variety of scenarios for (1) learning rate and (2) consumer willingness to pay (WTP) for range in each market. For the case of two firms, both approaches find the Nash equilibrium in all scenarios. On average, the SIO approach solves 200 times faster than the MPEC approach, and the MPEC approach is more sensitive to the starting point. Results show that the optimum for each firm is to platform when learning rates are high or the difference between consumer willingness to pay for range in each market is relatively small. Otherwise, the PHEVs are differentiated with low-range for China and high-range for the US.

关键词： product platform learning by doing design for market systems designoptimization mixed-integer nonlinear programing global optimization mathematical programming with equilibrium constraints mathematical programming with complementarity constraints Nash equilibrium oligopoly product design product familydesign product platform design

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Heterogeneous aggregators competing in a local flexibility market for active distribution system management: A bi-level programming approach

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2022年 136卷 107639-107639页

作者： Evangelopoulos, Vasileios A. Kontopoulos, Theofanis P. Georgilakis, Pavlos S. Natl Tech Univ Athens NTUA Sch Elect & Comp Engn Athens Greece

The emerging role of aggregators in the electric power industry brings forth financial benefits and opportunities for the efficient management of active distribution systems (ADS). Aggregators represent heterogeneous sources of flexibility connected at demand-side, such as flexible loads, small-scale renewable energy sources (RES) and energy storage systems (ESS), and regulate their consumption and/or production in a manner to offer competitive flexibility services. This paper introduces a novel one-leader multi-followers bi-level programming model for the procurement of flexibility services in a local market that is organized for the management of ADS. The upper level problem maximizes the profit of a distribution company, which acts as supplier of electricity to end customers, while considering the network technical constraints that are imposed by the distribution system operator. The lower level problems, in turn, maximize the profit of multiple heterogeneous aggregators acting as flexibility service providers. Two different types of aggregators have been modeled: a) load aggregators, each interacting with a group of flexible end-customers (residential or commercial), and b) RES-ESS aggregators, each managing a group of small-scale RES by exploiting ESS. The model is tested on a modified 33-nodes distribution system to demonstrate the financial benefits that arise, and fruitful findings are extracted with sensitivity analysis.

关键词： Active distribution systems Aggregators Bi-level optimization Demand response Distributed energy resources Flexibility services mathematical programming with equilibrium constraints

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