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A combinatorial optimization approach to scenario filtering in portfolio selection

COMPUTERS & OPERATIONS RESEARCH 2022年 142卷 105701-105701页

作者： Puerto, Justo Ricca, Federica Rodriguez-Madrena, Moises Scozzari, Andrea Inst Math Univ Seville IMUS Seville Spain Univ Seville Dept Stat & Seville Spain Univ Roma La Sapienza Fac Econ MEMOTEF Rome Italy Univ Niccolo Cusano Roma Fac Econ Rome Italy

Recent studies stressed the fact that covariance matrices computed from empirical financial time series appear to contain a high amount of noise. This makes the classical Markowitz Mean-Variance Optimization model unable to correctly evaluate the performance associated to selected portfolios. Since the Markowitz model is still one of the most used practitioner-oriented tool, several filtering methods have been proposed in the literature to overcome the problem. Among them, the two most promising ones refer to the Random Matrix Theory and to the Power Mapping strategy. The basic idea of these methods is to transform the estimated correlation matrix before applying the Mean-Variance Optimization model. However, experimental analysis shows that these two strategies are not always effective when applied to real financial *** this paper we propose a new filtering method based on quadratic programming. We develop a mixed integer quadratic programming model, which is able to filter those observations that may affect the performance of the selected portfolio. We discuss the properties of this new model and test it on some real financial datasets. We compare the out-of-sample performance of our portfolios with the one of the portfolios provided by the two above mentioned alternative filtering methods giving evidence that our method outperforms them. Although our model can be solved efficiently with standard optimization solvers, the computational burden increases for large datasets. To solve also these problems, we propose a heuristic procedure, which, on the basis of our empirical results, shows to be both efficient and effective.

关键词： Mean-Variance optimization Portfolio selection Filtering methods mixed integer quadratic programming

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An Exact Algorithm for the Optimal Chiller Loading Problem and Its Application to the Optimal Chiller Sequencing Problem

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ENERGIES 2020年第23期13卷 6372-6372页

作者： Acerbi, Federica Rampazzo, Mirco De Nicolao, Giuseppe Univ Pavia Dept Ind & Informat Engn I-27100 Pavia Italy Univ Padua Dept Informat Engn I-35131 Padua Italy

The optimal management of multiple chiller systems calls for the solution of the so-called optimal chiller loading (OCL) problem. Due to the interplay of continuous and logical constraints, OCL is an NP-hard problem, so that a variety of heuristic algorithms have been proposed in the literature. Herein, an algorithm for its exact solution, named X-OCL, is developed under the assumption that the chillers' power consumption curves are quadratic. The proposed method hinges on a decomposition of the solution space so that the overall OCL problem is decomposed to a set of equality constrained quadratic programming problems that can be solved in closed form. By applying the new X-OCL solver to well known case studies, we assess and compare the performances of several literature algorithms, highlighting also some errors in the published results. Moreover, X-OCL is used to design a greedy optimal chiller sequencing (OCS) solver, called X-OCS. The X-OCS is tested on two literature benchmarks and on the model of the heating, ventilation and air-conditioning (HVAC) system of a semiconductor plant, over a two-year period. The performances of X-OCS are remarkably close to the theoretical optimal performance.

关键词： optimal chiller loading optimal chiller sequencing HVAC multiple chiller energy saving mixed integer quadratic programming semiconductor manufacturing HVAC operation economic dispatch

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Water supply network model for sustainable industrial resource use a case study of Zeeuws-Vlaanderen in the Netherlands

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WATER RESOURCES AND INDUSTRY 2020年 24卷

作者： Willet, Joeri King, Jude Wetser, Koen Dykstra, Jouke E. Essink, Gualbert H. P. Oude Rijnaarts, Huub H. M. Wageningen Univ Environm Technol Bornse Weilanden 9 NL-6708 WG Wageningen Netherlands Univ Utrecht Dept Phys Geog Utrecht Netherlands Deltares Unit Subsurface & Groundwater Syst Utrecht Netherlands Wageningen Environm Res Water & Food POB 47 NL-6700 AA Wageningen Netherlands

Matching regional water supply and demand can be improved by allocating local renewable water resources through decentralized water supply networks (WSNs). The feasibility of decentralized WSNs depends on the costs for the required pipeline infrastructure. The lowest costs for pipeline infrastructure depend on the local landscape characteristics. We present a model that designs decentralized WSNs to supply water with regional supply sources. The objective of the model is to include the effects of landscape characteristics on infrastructure costs and to minimize overall WSN costs. We tested the model on a case study in the fresh-water scarce region of Zeeuws-Vlaanderen in the southwestern part of The Netherlands with known (hydro)geological, geographical and climate data. The model was tested to supply a large industrial water user with groundwater resources operated within sustainable yields. The generated WSNs cover a demand between 0.5 and 5.5 million m(3) year(-1). Between 1 and 12 supply locations are needed to cover the demand. The pipeline infrastructure needed ranges from 25.1 to 114.5 km. The model determines the optimal pipeline route, the amount of water flowing over each pipeline segment, and reveals if a small increase in demand causes a relatively large increase in costs. The results can be used to determine if water transport is preferred over other water supply options, such as wastewater re-use or desalination of saline water resources.

关键词： Industrial water use Water supply network Network optimization Geo information systems (GIS) mixed integer quadratic programming

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An Optimal and Distributed Demand Response Strategy for Energy Internet Management

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ENERGIES 2018年第1期11卷 215页

作者： Liu, Qian Wang, Rui Zhang, Yan Wu, Guohua Shi, Jianmai North China Inst Aerosp Engn Langfang 065000 Peoples R China Natl Univ Def Technol Coll Syst Engn Changsha 410073 Hunan Peoples R China

This study proposes a new model of demand response management for a future smart grid that consists of smart microgrids. The microgrids have energy storage units, responsive loads, controllable distributed generation units, and renewable energy resources. They can buy energy from the utility company when the power generation in themselves cannot satisfy the load demand, and sell extra power generation to the utility company. The goal is to optimize the operation schedule of microgrids to minimize the microgrids' payments and the utility company's operation cost. A parallel distributed optimization algorithm based on games theory is developed to solve the optimization problem, in which microgrids only need to send their aggregated purchasing/selling energy to the utility company, thus avoid infringing its privacy. Microgrids can update their operation schedule simultaneously. A case study is implemented, and the simulation results show that the proposed method is effective and efficient.

关键词： microgrids smart grid games theory demand and response strategy mixed integer quadratic programming distributed optimization

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Medium-term scheduling of a hydropower plant participating as a price-maker in the automatic frequency restoration reserve market

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ELECTRIC POWER SYSTEMS RESEARCH 2020年 185卷 106399-106399页

作者： Perez-Diaz, Juan, I Guisandez, Ignacio Chazarra, Manuel Helseth, Arild Univ Politecn Madrid Dept Hydraul Energy & Environm Engn C Prof Aranguren 3 Madrid 28040 Spain SINTEF Energy Res Sem Saelands Vei 11 N-7465 Trondheim Norway

This paper presents a novel optimization model for the calculation of the water value of a hydropower plant. The model has a time horizon of 1 year with 1-day decision stages, considers sales of both energy and frequency restoration reserves (FRR) and is solved by stochastic dynamic programming. The novelty of the model is that it considers the producer's price-making ability in the FRR market. The proposed model is used to obtain the water values of an existing hydropower plant. The water values are then used to simulate the day-ahead scheduling of the hydropower plant in a 100-year scenario. The results are compared to those obtained without considering the producer's price-making ability in the FRR market. The profit increase is modest compared to the uncertainty existing in the day-ahead scheduling in all analysed cases. However, the water spillage is significantly lower if the producer's price-making ability in the FRR market is considered when computing the water value. This last result may have important implications for the plant's operation, especially when the reservoir is also used for the purpose of flood control, as the one used as case study in the paper, and many others all over the world.

关键词： Hydroelectric power generation Water value Frequency restoration reserve market Price-maker producer mixed integer quadratic programming Stochastic dynamic programming

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Day-ahead optimal dispatch of an integrated energy system considering time-frequency characteristics of renewable energy source output

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ENERGY 2020年 209卷 118434-118434页

作者： Zheng, Lingwei Zhou, Xingqiu Qiu, Qi Yang, Lan Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China

The intermittency and uncertainty output of renewable energy source (RES) poses a challenge for the optimal dispatch of an integrated energy system (IES). Many current studies focus on the time-domain characteristics of the RES prediction, while ignoring the time-frequency characteristics of the prediction, thus the operation is usually scheduled on a uniform time-step. Based on this context, an adaptive hybrid dispatch time-step (AHDT) determination method based on the time-frequency characteristics of the prediction is proposed. Different from the traditional time-step, AHDT is non-uniform. Firstly, the Hilbert-Huang transform is used to convert the predicted RES output data to the time-frequency. Next, a time-step function which reflects the mapping of time-step and instantaneous frequency is constructed to suggest an adaptive time-step in each dispatch segment. Then, an optimal day-ahead dispatch model of a typical IES with AHDT, which is essentially a mixed integer quadratic programming (MIQP) problem, is established. Finally, the day-ahead schedules of each unit are obtained by solving the MIQP problem. The simulations are conducted in a total of twenty randomly selected days. The results show that the AHDT method is superior to the uniform time-step method for its effect in reducing the operating cost and the optimization-calculating time cost. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Integrated energy system Hilbert-Huang transform Day-ahead optimal dispatch Adaptive hybrid dispatch time-step mixed integer quadratic programming

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Flow batteries for energy management: Novel algebraic modelling approaches to properly assess their value

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JOURNAL OF ENERGY STORAGE 2019年 26卷

作者： Roberts, D. Brown, S. Univ Sheffield Dept Chem & Biol Engn Sheffield S10 2TN S Yorkshire England

Redox Flow Battery (RFB) systems are promising technologies for the mull-hour electrical energy storage that will be necessary for on-demand electricity supply based on wind and solar power. Deriving maximum value from a RFB requires optimisation of both the system design and its operation. In this work three novel algebraic modelling approaches are introduced to represent RFB operation more accurately while maintaining quick optimisation times. First the typical linear programming (LP) optimisation problem is re-posed in terms of current-density rather than power, allowing voltaic losses to be expressed as a quadratic function (QP). Secondly, it is then shown that the current-density framework supports a novel constraint for the avoidance of high cell voltage that may damage the stack. Thirdly, for the first time a binary variable (MIQP) to describe active/idle states is introduced. This allows coulombic leakage and pumping losses to be modelled as fixed terms without constantly draining the RFB, and it allows for the optimisation of pump rating in a VRFB. In a day-ahead energy management case study, it is found that the QP optimisation predicts an additional 19% annual revenue when compared to the LP optimisation. This capture of the true flexibility of the RFB operation allows its full value to be assessed, and therefore advances the case for their deployment within the energy system. Furthermore, the formulations developed are not only applicable to RFBs but to the scheduling of other battery systems, particularly Li-ion, and balance of plant optimisation, such as the sizing of inverters and climate control systems in the context of parasitic losses.

关键词： Redox flow battery Optimisation mixed integer quadratic programming Techno-economic analysis Scheduling VRFB

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A flexible interactive coordination control method of commercial virtual power plant based on WCVAR

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2024年 160卷

作者： Hu, Shenghong Chen, Yulin Feng, Jian CHN Energy Qinghai Yellow River Maerdang Hydropowe Xining 811600 Qinghai Peoples R China CHN Energy Zhishen Control Technol Co Ltd Beijing 102211 Peoples R China

Commercial virtual power plant is one of the most efficient means to solve the problem of multi-type distributed power supply and flexible load scheduling. Aiming at the problems of uncertain renewable energy sources and reliable distribution system, a flexible interactive coordinated control method for commercial virtual power plants based on worst-case conditional value-at-risk (WCVAR) is proposed in this paper. In order to reduce the risk of voltage exceeding limits and increased network losses at distribution network nodes, combined with the requirements of technology virtual power plants for power flow control technology in distribution networks, a commercial virtual power plant net profit model based on the reliability of distribution network operation is established. The worst-case conditional risk value theory is used to quantify the risks caused by the uncertainty of wind, water and photovoltaic outputs. A commercial virtual power plant optimization scheduling model based on the WCVAR is established with the goal of minimizing risk cost, and the model is solved by commercial software Cplex. By simulating and analyzing the actual operating data of the improved IEEE-33 distribution system, the output characteristics of commercial virtual power plants under different risk confidence levels are compared and analyzed. The simulation results show that this method fully explores the scheduling potential between electricity, power grid, load and energy storage in commercial virtual power plants, flexibly adjusts risk preferences according to scheduling needs, and achieves flexible control of benefits and risks in commercial virtual power plants.

关键词： Commercial virtual power plant Worst-case conditional value-at-risk mixed integer quadratic programming Sensitivity analysis Optimal operation

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A Gini Coefficient-Based Impartial and Open Dispatching Model

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ENERGIES 2020年第12期13卷 3146页

作者： Sun, Liang Zhang, Na Li, Ning Song, Zhuo-ran Li, Wei-dong Dalian Univ Technol Sch Elect Engn Dalian 116024 Peoples R China State Grid Shenyang Elect Power Supply Co Shenyang 110081 Peoples R China State Grid Liaoning Econ Res Inst Shenyang 110015 Peoples R China State Grid Liaoning Elect Power Co Ltd Shenyang 110006 Peoples R China

According to the existing widely applied impartial and open dispatching models, operation fairness was mainly emphasized, which severely restricted the optimization space of the economy of the overall system operation and affected the economic benefits. To solve the above problems, a scheduling model based on Gini coefficient under impartial and open dispatching principle is proposed in this paper, which can consider the balance between the fairness and economy of system operation. In the proposed model, the Gini coefficient is introduced to describe the fairness of electric energy completion rate among different generation units in the form of constraint conditions. Because the electricity production schedule can reflect the economic income of the electric power enterprise, and the Gini coefficient is used as an economic statistical indicator to evaluate the fairness in the overall distribution of income in social statistics, it is more appropriate to be used to measure the fairness of the power generation dispatching. The objective of the proposed model is to minimize the total operation costs. In the model, the balance between the system operation economy and fairness can be realized by adjusting the Gini coefficient value. The simulation results show that the proposed model is an extension of the traditional model. Compared with the traditional economic dispatching model and normal "impartial and open dispatching" model, the proposed model can better coordinate the relationship between fairness and economy. It could provide more choices for power generation dispatchers. It could also provide a reference for regulatory departments to formulate relevant policies by adjusting the threshold value of the Gini coefficient. Case studies show that the power dispatching decisions according to the proposed model can provide a scientific and fair reference basis for dispatching schemes, and could reduce the generation costs and also achieve optimal allocation of resources

关键词： impartial and open dispatching economy Gini coefficient generation scheduling mixed integer quadratic programming

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Non-invasive patient breathing effort identification: a b-spline and mixed integer solution

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IFAC-PapersOnLine 2024年第24期58卷 187-192页

作者： K. Lindup J.G. Chase C. Zhou M. Bertoni F. Padula A. Visioli School of Electrical Engineering Computing and Mathematical Sciences Curtin University Australia Department of Mechanical Engineering University of Canterbury Christchurch New Zealand Department of Medical and Surgical Specialties Radiological Science and Public Health University of Brescia Italy and Spedali Civili di Brescia Italy Curtin Centre for Optimisation and Decision Science Curtin University Australia Department of Mechanical and Industrial Engineering University of Brescia Italy

Accurate identification of patient breathing efforts is imperative to the delivery of lung and diaphragm protective ventilation. Existing model-based approaches constrain the allowable shape of the patient effort pressure-time profile to improve model identifiability. A novel method – coined the B-MIQP technique – is presented that extends upon existing methods with aims to further improve identification accuracy. B-spline basis functions and binary decision variables are utilised within a single compartment framework to describe the patient effort pressure-time profile. With reference to the experimental results, identified elastance and resistance values were within expected ranges, while identified patient effort outcomes matched physiological expectations and reflected trends when compared to esophageal pressure signals.

关键词： Mechanical Ventilation PSV B-Spline mixed integer quadratic programming

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