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Energetic and economic optimization of the yearly performance of three different solar assisted heat pump systems using a mixed integer linear programming algorithm

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ENERGY CONVERSION AND MANAGEMENT 2020年 206卷

作者： Simonetti, Riccardo Moretti, Luca Molinaroli, Luca Manzolini, Giampaolo Politecn Milan Dipartimento Energia Via Lambruschini 4 I-20156 Milan Italy

This paper presents a yearly energetic and economic assessment of three different solar assisted heat pump concepts integrated with electrical and thermal storages and applied to a single-family house. The three heat pump-based systems are (i) a conventional air-to-water heat pump plus photovoltaic solar modules, (ii) a water-to-water heat pump coupled to hybrid photovoltaic-thermal solar modules and (iii) a dual source heat pump integrated with hybrid photovoltaic-thermal solar modules. The energetic and economic analysis is performed using physically-based models of each component for different numbers of solar modules and sizes of the electric storage. The maximum economic saving of these highly integrated systems is determined through an optimization algorithm based on the mixed integer linear programming technique. The results show that the dual source heat pump system with the largest battery size is the system that achieves the highest energetic performance, i.e. 77% primary energy saving with respect to traditional boiler-based system, whereas the lowest operating cost and the highest economic saving are obtained using the conventional air-to-water heat pump without any electric storage since it achieves 31% economic saving compared with the baseline system.

关键词： Economic analysis Energetic analysis mixed integer linear programming Hybrid photovoltaic/thermal collectors Solar assisted heat pump

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QAOA-Assisted Benders' Decomposition for mixed-integer linear programming

QAOA-Assisted Benders' Decomposition for Mixed-integer Linea...

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IEEE International Conference on Communications (ICC)

作者： Zhongqi Zhao Lei Fan Yuanxiong Guo Yu Wang Zhu Han Lajos Hanzo Department of Electrical and Computer Engineering University of Houston Houston TX USA Department of Engineering Technology University of Houston Houston TX USA Department of Information Systems and Cyber Security University of Texas at San Antonio San Antonio TX USA Department of Computer and Information Sciences Temple University Philadelphia PA USA School of Electronics and Computer Science University of Southampton Southampton UK

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

Benders' decomposition (BD) algorithm constitutes a powerful mathematical programming method of solving mixed-integer linear programming (MILP) problems with a specific block structure. Nevertheless, BD still needs to solve an NP-hard quasi-integer programming master problem (MAP), which motivates us to harness the popular variational quantum algorithm (VQA) to assist BD. More specifically, we choose the popular quantum approximate optimization algorithm (QAOA) of the VQA family. We transfer the BD's MAP into a digital quantum circuit associated with a physically tangible problem-specific ansatz; and then solve it with the aid of a state-of-the-art digital quantum computer. Next, we evaluate the computational results and discuss the feasibility of the proposed algorithm. The hybrid approach advocated, which utilizes both classical and digital quantum computers, is capable of tackling many practical MILP problems in communication and networking, as demonstrated by a pair of case studies.

关键词： Performance evaluation Quantum computing Quantum algorithm programming Approximation algorithms mixed integer linear programming Quantum circuit

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Energy Management of a Workplace with EVs by mixed-integer linear programming

Energy Management of a Workplace with EVs by Mixed-Integer L...

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International Technical Conference o Circuits/Systems, Computers and Communications (ITC-CSCC)

作者： Yuki Sakamoto Takumi Namba Kiyotsugu Takaba Ritsumeikan University Kusatsu Japan

ISBN: (数字)9798350379051

ISBN: (纸本)9798350379068

The use of EV batteries as secondary energy sources has recently been attracting great attention due to their large capacities. This paper is concerned with energy management of a workplace making use of the employees' EVs. We formulate such an energy management as a mixed-integer linear programming (MILP) problem by taking account of the arrival/departure status of the EVs and the benefits of the EV owners. Through a numerical simulation, we compare the effectiveness of the centralized algorithm and the distributed algorithm (Camisa et al. 2022) for finding a near-optimal solution to the MILP. The following points turn out from the simulation. If the number of EVs is small, the centralized algorithm can obtain a better solution to the MILP problem faster than the distributed algorithm without admitting the EV owners' decision-making. In contrast, in the case of a large number of EVs, the distributed algorithm can solve the problem faster than the centralized one taking account of the EV owners' decision-making at the price of the quality of its solution.

关键词： Computers Employment Decision making Numerical simulation linear programming mixed integer linear programming Batteries

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Makespan optimization using Timed Petri Nets and mixed integer linear programming Problem

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IFAC-PapersOnLine 2020年第4期53卷 129-135页

作者： E. Di Marino R. Su F. Basile University of Salerno DIEM Italy Nanyang Technological University School of Electrical & Electronic Engineering Singapore

In this paper, a method for generating a mixed integer linear programming problem from deterministic timed Petri nets to optimize the makespan of manufacturing systems is proposed. After exposing several challenges involved in such a model transformation, a novel method is exploited to overcome them. The adopted solution may create a synergy between the highly expressive timed Petri net modelling framework and the computational attractive mathematical programming tool set.

关键词： Discrete Event Systems Timed Petri Nets mixed integer linear programming

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A mixed-integer linear programming Formulation for Human Multi-Robot Task Allocation 30

A Mixed-Integer Linear Programming Formulation for Human Mul...

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30th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN)

作者： Lippi, Martina Marino, Alessandro Roma Tre Univ Rome Italy Univ Cassino & Southern Lazio Cassino Italy

ISBN: (纸本)9781665404921

In this work, we address a task allocation problem for human multi-robot settings. Given a set of tasks to perform, we formulate a general mixed-integer linear programming (MILP) problem aiming at minimizing the overall execution time while optimizing the quality of the executed tasks as well as human and robotic workload. Different skills of the agents, both human and robotic, are taken into account and human operators are enabled to either directly execute tasks or play supervisory roles;moreover, multiple manipulators can tightly collaborate if required to carry out a task. Finally, as realistic in human contexts, human parameters are assumed to vary over time, e.g., due to increasing human level of fatigue. Therefore, online monitoring is required and re-allocation is performed if needed. Simulations in a realistic scenario with two manipulators and a human operator performing an assembly task validate the effectiveness of the approach.

关键词： Collaboration Switches Manipulators Fatigue Real-time systems mixed integer linear programming Resource management

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mixed-integer linear programming (MILP) Approach for Solving Derating Problems in Optimization of Thermal Power Plants Operation Considering Primary Energy Uncertainty

Mixed-Integer Linear Programming (MILP) Approach for Solving...

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Power Engineering Application (ICPEA), IEEE International Conference in

作者： Nur Fauziyah Nanang Hariyanto School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

Electricity has an important role in economic development and people’s lives in a country. As the population increases, so does the demand for electricity, resulting in the problem of shortages of electricity supply which leads to huge economic losses. The important problem to be considered is the primary energy used to produce electricity, especially coal, one of the primary energies of thermal power plants where coal availability has a contribution to the non-optimal scheduling of thermal power plants operation which causes the derating problems. This paper proposes a new algorithm with combining algorithms of unit commitment and economic dispatch, coal transshipment, coal blending and inventory problems which will be implemented using Pyomo based on Python programming language with mixed integer linear programming (MILP) approach. The new algorithm is used to determine the optimal time for coal delivery and maintenance of power plants according to coal inventory. The results showed that the addition of this new algorithm provides 5.57% cheaper and more optimal power plants operation cost.

关键词： Costs Uncertainty Coal Maintenance engineering mixed integer linear programming Thermal analysis Sulfur

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A mixed integer linear programming Method for Generating Backbone Grid 3

A Mixed Integer Linear Programming Method for Generating Bac...

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3rd IEEE International Electrical and Energy Conference (CIEEC)

作者： ZhiYuan, Sun Liu, Mosi Sun, Yan Guangxi Power Grid Co Ltd Elect Power Res Inst Nanning Peoples R China Guangxi Power Grid Co Ltd Power Dispatching & Control Ctr Nanning Peoples R China

ISBN: (纸本)9781728116754

The intelligence algorithm used in the backbone grid search is unrobust and has uncertain results. To tackle the drawback, this paper proposes a mixed integer linear programming (MILP) model for generating the power system backbone grid. Based on the graph theory, this model considers the connectivity of the backbone grid as linear constraints with integer variables. Constrains of line power in the model are elicited by the derivation from Kirchhoff's current law. Since the expressions in this model are analytical and linear, with the help of developed MILP algorithm, the proposed model can fully solve the problem of absence of robustness in existing method. The simulations of IEEE 39-bus system and IEEE 118-bus system show that the proposed model is effective and reliable, which provides a new idea for the development in this research.

关键词： mixed integer linear programming backbone grid Steiner tree connectivity

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Predicting Mode Confusion Through mixed integer linear programming 58

Predicting Mode Confusion Through Mixed Integer Linear Progr...

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58th IEEE Conference on Decision and Control (CDC)

作者： Sivaramakrishnan, Vignesh Thapliyal, Omanshu Vinod, Abraham Oishi, Meeko Hwang, Inseok Univ New Mexico Elect & Comp Engn Albq NM 87131 USA Purdue Univ Aeronaut & Astronaut W Lafayette IN 47907 USA Univ Texas Austin Oden Inst Computat Engn & Sci Austin TX 78712 USA Univ New Mexico Albuquerque NM 87131 USA

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113982

Mode confusion, in which the human and the automation have a mismatch in intent, is a contributing factor in many aircraft incidents and accidents. Despite extensive work studying and documenting instances of mode confusion, methodological tools to predict and prevent mode confusion are still lacking. We propose a method to identify mismatches between the pilot and automation intents, in which the pilot intent is inferred from the pilot manual, and the automation intent is an abstraction of the underlying hybrid dynamical system representation of the aircraft and flight management system. We employ a mixed-integer linear programming framework to identify all trajectories from a known initial condition that will result in mismatches in discrete event abstractions which encode both pilot and aircraft intents. We then propose heuristics that use traces from failed trajectories to correct the mode confusion through modifications to the automation intent, via parameterization of guards. We demonstrate our method on the canonical kill-the-capture scenario for longitudinal aircraft dynamics.

关键词： Aircraft Atmospheric modeling Automation Hidden Markov models Discrete-event systems Trajectory mixed integer linear programming

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Optimum Scheduling of Residential Appliances along with the Management of Distributed Energy Resources using mixed integer linear programming 5

Optimum Scheduling of Residential Appliances along with the ...

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IEEE 5th International Conference for Convergence in Technology (I2CT)

作者： Singh, Paramvir Tayal, Nisha Verma, Yajvender Pal Singh, Baljit Panjab Univ UIET Dept Elect & Elect Engn Chandigarh India GNDEC Dept Elect & Elect Engn Ludhiana Punjab India

ISBN: (纸本)9781538680759

With the concept of Smart Grid (SG) becoming a reality, the communication between the SG and the smart meters will enable the residential customers to participate in energy trading. The demand based tariffs and incentives will help in efficient management of the Distributed Energy Resources (DERs) employed in the residences along with the scheduling of the residential loads. The study undertaken classifies the appliances of a single residence into schedulable and real-time loads. It then employs a Residential Energy Management System (REMS) to optimally manage the energy from the DERs along with the operation of the schedulable appliances according to the day-ahead Time of Use (ToU) pricing strategy. For the energy management, three scenarios with significant variations in the solar irradiation, wind speed, outside environment temperature, real-time appliances' schedule and Electric Vehicle's (EV) driving schedule have been considered. An MILP problem has been formulated with the objective of reducing the residential energy expenditure. The results were analyzed to understand the operation of the REMS under different weather and operating dynamics.

关键词： Demand Response Time of Use prices Distributed energy resources Residential energy management system mixed integer linear programming MATLAB

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A Prioritization Tool for SUDS Planning in Large Cities by Coupling an Urban Drainage Model with mixed integer linear programming 11th

A Prioritization Tool for SUDS Planning in Large Cities by C...

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11th International Conference on Urban Drainage Modelling (UDM)

作者： Narine Torres, Maria Zhu, Zhenduo Pablo Rodriguez, Juan Univ Andes CIIA Bogota Colombia SUNY Buffalo Dept Civil Struct & Environm Engn Buffalo NY 14260 USA

ISBN: (纸本)9783319998671;9783319998664

Decision making regarding Sustainable Urban Drainage Systems (SUDS) sitting is an analytical complex process, as it involves the evaluation of a high number of environmental, physical and technical considerations. Additionally, as the resources are always limited (e.g. budget and land availability), the prioritization of sub-catchments for SUDS placement would help decision makers to determine where is most beneficial to locate these infrastructures. This study proposes a methodology that couples an urban drainage model and mixed integer linear programming (MILP) to determine where is more beneficial to locate SUDS to reduce both runoff volumes and combined sewer overflows (CSOs). To achieve this goal, the City Drain model is used to model the runoff generation and the flows among sub-catchments. Three indexes are proposed to quantify the reduction on both CSO and runoff volumes, and a lexicographic multi-objective model is used to find the prioritized sub-catchments within a city. The methodology was applied to sub-catchments of Bogota (Colombia), comprising an area of 38 km(2). Preliminary results showed that the prioritized sub-catchments were highly dependent on land availability and the optimal solution did not necessarily involve the selection of the sub-catchments that yield most runoff. This study demonstrates the importance and usefulness of the prioritization tool for SUDS planning, which can be used by other large cities like Bogota.

关键词： Sustainable urban drainage systems Spatial allocation mixed integer linear programming

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