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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Ali Esmaeel Nezhad Pedro H.J. Nardelli Subham Sahoo Farideh Ghanavati Gerardo J. Osó rio Department of Electrical Engineering School of Energy Systems LUT University Lappeenranta Finland Department of Energy Technology Aalborg University Aalborg Denmark Department of Industrial Engineering and Management University of Aveiro Aveiro Portugal University Portucalense Infante D. Henrique (UPT) R. Dr. Ant&#x00F3 nio Bernardino de Almeida Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

This paper investigates a centralized, high-resolution and fast model for home energy management. The model is provided within mixed-integer linear programming (MILP) framework while it benefits from an open-access optimization model in Python for running the model free of charge. To minimize the electricity bill, the time-of-use (TOU) electricity tariff has been selected by the consumer to manage the daily electricity consumption. This consumer-centric home energy management system (HEMS) enhances the flexibility that can be provided by the dedicated consumers during peak periods while reducing the electricity bill of the end-users benefiting from the TOU tariff. The time resolution of home appliance scheduling is 15 minutes in this study and it is compatible with the smart metering data recording for energy consumed by the end-users. The simulation results show that the electricity bill would be considerably decreased by using the proposed self-scheduling model.

关键词： Home appliances Costs Simulation Tariffs Recording mixed integer linear programming Energy management systems

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Open Pit Mine Production Scheduling using New Global Constraint

Open Pit Mine Production Scheduling using New Global Constra...

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IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering, SIBIRCON

作者： Yurii A. Oleynik Alexander A. Zuenko Institute for Informatics and Mathematical Modelling Kola Science Centre of the Russian Academy of Sciences Apatity Russia

ISBN: (纸本)9781665464819

The work deals with solving one of the important problems of Scheduling Theory – the Open Pit Mine Production Scheduling Problem. To solve this problem, methods of mixed integer linear programming are widely used, the fundamental disadvantage of which is that they impose increased requirements on the amount of RAM required to store the model and implement calculations. This article presents the results that develop previous studies of the authors, in which it was proposed to solve the Open Pit Mine Production Scheduling Problem as a Constraint Satisfaction Problem, and also described the main types of global constraints for modeling the conditions of the problem under consideration. Particularly, it was proposed to represent and process the conditions for the extraction sequence of blocks using a set of global constraints max for each block separately. The study presents the Global Block Sequencing Constraint developed by the authors, which propagator (handler) analyzes the conditions for the block extraction sequence, as well as some additional requirements in one launch for all blocks in the queue of propagator, which can significantly increase the efficiency of calculations. In comparison with the methods of integer linear programming, the use of the Constraint programming Paradigm allow you to significantly decrease RAM consumption due implicit representation of constraints, which leads to the ability to solve problems with the required level of discretization of pit model.

关键词： Constraint handling Sequential analysis Computational modeling Random access memory Production Search problems mixed integer linear programming

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Grid-Aware Layout of Photovoltaic Panels in Sustainable Building Energy Systems

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FRONTIERS IN ENERGY RESEARCH 2021年 8卷

作者： Middelhauve, Luise Baldi, Francesco Stadler, Paul Marechal, Francois Ecole Polytech Fed Lausanne Ind Proc & Energy Syst Engn Sion Switzerland Italian Natl Agcy New Technol Energy & Sustainabl Bologna Italy

In the context of increasing concern for anthropogenic CO2 emissions, the residential building sector still represents a major contributor to energy demand. The integration of renewable energy sources, and particularly of photovoltaic (PV) panels, is becoming an increasingly widespread solution for reducing the carbon footprint of building energy systems (BES). However, the volatility of the energy generation and its mismatch with the typical demand patterns are cause for concern, particularly from the viewpoint of the management of the power grid. This paper aims to show the influence of the orientation of photovoltaic panels in designing new BES and to provide support to the decision making process of optimal PV placing. The subject is addressed with a mixed integer linear optimization problem, with costs as objectives and the installation, tilt, and azimuth of PV panels as the main decision variables. Compared with existing BES optimization approaches reported in literature, the contribution of PV panels is modeled in more detail, including a more accurate solar irradiation model and the shading effect among panels. Compared with existing studies in PV modeling, the interaction between the PV panels and the remaining units of the BES, including the effects of optimal, scheduling is considered. The study is based on data from a residential district with 40 buildings in western Switzerland. The results confirm the relevant influence of PV panels' azimuth and tilt on the performance of BES. Whereas south-orientation remains the most preferred choice, west-orientationed panels better match the demand when compared with east-orientationed panels. Apart from the benefits for individual buildings, an appropriate choice of orientation was shown to benefit the grid: rotating the panels 20 degrees westwards can, together with an appropriate scheduling of the BES, reduce the peak power of the exchange with the power grid by 50% while increasing total cost by only 8.3%. Incl

关键词： building energy systems mixed integer linear programming photovoltaic systems roof orientation renewable energies global warming potential multi objective optimization power network integration

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Optimal design of European supply chains for carbon capture and storage from industrial emission sources including pipe and ship transport

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INTERNATIONAL JOURNAL OF GREENHOUSE GAS CONTROL 2021年 109卷

作者： d'Amore, Federico Romano, Matteo Carmelo Bezzo, Fabrizio Univ Padua CAPE Lab Comp Aided Proc Engn Lab Dept Ind Engn Via Marzolo 9 IT-35131 Padua Italy Politecn Milan Dept Energy Via Lambruschini 4 IT-20156 Milan Italy

Carbon capture and storage technologies are key to remove carbon dioxide emissions from hard-to-decarbonise industries, such as steel, cement and refining sectors. A multi-echelon mixed integer linear programming model is developed for the optimal design of carbon capture and storage supply chains from industrial sources at a European level. The model is based on exact coordinates and comprises all the stages of a carbon capture and storage chain in Europe, including multiple capture plants across industrial sources, CO2 transport through pipelines or ships to existing docks, onshore and/or offshore geological storage basins. The optimal infrastructure is optimised in economic terms by pursuing either country-wise or Europe-wide carbon reduction targets. Removing 50% of industrial CO2 emissions in each country costs 60.5 euro /t, which increases up to 81.4 euro /t if onshore storage is forbidden. Variations of carbon reduction target are analysed. Although CO2 transport by pipeline dominates in terms of volumes, ships can have an important role for Southern Europe countries, if CO2 storage is restricted to offshore North Sea basins. The setting of a Europe-wide reduction target produces a slight decrease in costs in all analysed scenarios.

关键词： Carbon capture and storage from industry mixed integer linear programming European supply chain optimisation Pipeline against ship transport Country-wise reduction targets

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Techno-Economic Analysis for the Optimal Design of a National Network of Agro-Energy Biomass Power Plants in Egypt

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ENERGIES 2021年第11期14卷

作者： Abdelhady, Suzan Shalaby, Mohamed A. Shaban, Ahmed Fayoum Univ Fac Engn Dept Elect Engn Al Fayyum 63514 Egypt Cairo Univ Fac Engn Dept Mech Design & Prod Cairo 12613 Egypt Fayoum Univ Fac Engn Dept Mech Engn Al Fayyum 63514 Egypt

Extensive studies are conducted to investigate the potential and techno-economic feasibility of bioenergy routes in different countries. However, limited researches have been focused on the whole national agricultural bioenergy resources in Egypt. This research provides an assessment of the potential agricultural biomass resources for electric energy production in Egypt. It provides a strategic perspective for the design of a national network of biomass power plants to utilize the spatially available agricultural residues throughout a country. A comprehensive approach is presented and is applied to Egypt. First, the approach estimates the amount, type, and characteristics of the agricultural residues in each Egyptian governorate. Then, a techno-economic appraisal for locating a set of collection stations, and installing a direct combustion biomass power plant in each governorate is conducted. SAM simulation software is used for the technical and economic appraisals, and preliminary plant capacities are estimated assuming one plant in each governorate. Secondly, a new mixed integer linear programming (MILP) model is proposed and applied to optimally design a biomass supply chain national network to maximize the overall network profit. The network is composed of the collection stations, the potential biomass power plants, and the flow distribution of residues to supply the selected plants. Results indicate that the Egyptian agricultural residue resources can produce 10 million ton/year of dry residues, generate 11 TWh/year, an average levelized cost of electricity (LCOE) of 6.77 cent/kWh, and supply about 5.5% of Egypt's current energy needs. Moreover, the optimization results reveal that a network of 5 biomass power plants with capacities of 460MWeach should be established in Egypt. This approach is thought to be particularly suitable to other developing countries whose energy demand depends on fossil fuels and poses a heavy economic burden, and whose residues are ma

关键词： biomass energy crop residues levelized cost of electricity supply chain power network mathematical models mixed integer linear programming system advisor model Egypt

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Cyberattacks with limited network information leading to transmission line overflow in cyber-physical power systems

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SUSTAINABLE ENERGY GRIDS & NETWORKS 2021年 27卷

作者： Khazaei, Javad Penn State Harrisburg Elect Engn Dept 777 W Harrisburg Pike Middletown PA 17057 USA Penn State Univ Pk Architectural Engn Dept State Coll PA 16801 USA

Recent cyberattacks on the U.S. power grid revealed how vulnerable smart grids are against cyberattacks. Consequently, it is critical to study cyberattacks that can lead to cascading failures in power systems and develop models to realistically emulate attack scenarios that can bypass existing bad data detection algorithms. In this paper, a mixed-integer linear programming model is developed to accurately model load redistribution attacks via false data injections (FDIs) that are targeted to overflow multiple transmission lines while the attackers have limited access to network topology and information. Compared to the existing research on cyberattacks on transmission line overflow, the proposed model considers that the attackers might have limited access to all measurements and can only target a set of measurements in a region (area) instead of full access to the network information. Numerical results on IEEE 118-bus benchmark revealed the effectiveness of the proposed modeling in overflowing up to four transmission lines with incomplete network information and FDIs limited to 40% of nominal loads. (C) 2021 Elsevier Ltd. All rights reserved.

关键词： Stealthy false data injection Incomplete network information mixed integer linear programming Cyberattacks

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Flexibility Provision by Smart Homes in Integrated Energy Management Systems

Flexibility Provision by Smart Homes in Integrated Energy Ma...

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International Conference on Environment and Electrical Engineering (EEEIC)

作者： Mohammad Sadegh Javadi Ali Esmaeel Nezhad Pedro H.J. Nardelli Subham Sahoo Institute for Systems and Computer Engineering Technology and Science (INESC TEC) Porto Portugal Department of Electrical Engineering School of Energy Systems LUT University Lappeenranta Finland Department of Energy Technology Aalborg University Aalborg Denmark

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

This paper presents a mathematical problem formulation for energy management systems for smart homes. The flexibility can be provided by a home energy management system (HEMS) in a local energy community. The main concept is to model the flexibility provision and flexibility procurement within the energy community that can be provided to the aggregator from active consumers. The integrated energy management model is coded as a standard mixed-integer linear programming (MILP) model which can be solved by open-source tools like the PuLP package developed in Python. The simulation results confirm the performance of the proposed model in terms of flexibility provided by the centralized integrated energy system introduced in this paper.

关键词： Home appliances Costs Simulation Smart homes Mathematical models mixed integer linear programming Energy management systems

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Exploring Non-linear programming Formulations in QuantumCircuitOpt for Optimal Circuit Design

Exploring Non-Linear Programming Formulations in QuantumCirc...

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Quantum Computing Software (QCS), IEEE/ACM International Workshop on

作者： Elena R. Henderson Harsha Nagarajan Carleton Coffrin Information Systems and Modeling Los Alamos National Laboratory Los Alamos NM USA Applied Math. and Plasma Physics (T-5) Los Alamos National Laboratory Los Alamos NM USA Advanced Network Science Initiative Los Alamos National Laboratory Los Alamos NM USA

ISBN: (纸本)9781665475372

Given the limitations of current hardware, the theoretical gains promised by quantum computing remain unre-alized across practical applications. But the gap between theory and hardware is closing, assisted by developments in quantum algorithmic modeling. One such recent development is Quan-tumCircuitOpt (QCOpt), an open-source software framework that leverages state-of-the-art optimization-based solvers to find provably optimal compact circuit decompositions, which are exact up to global phase and machine precision. The quantum circuit design problem can be modeled using non-linear, non-convex constraints. However, QCOpt reformulates these non-linear constraints using well-known linearization techniques such that the resulting design problem is solved as a mixed-integer linear programming model. In this work, we instead explore whether the QCOpt's model could also be effective with a continuous Non-linear programming (NLP) model obtained via relaxation of the integer variables in the non-linear constraints. We are able to present not only multiple significant enhancements to QCOpt, with up to 11.3x speed up in run times on an average, but also opportunities for more generally exploring the behavior of gradient-based NLP solvers.

关键词： Conferences Software algorithms Quantum mechanics linearization techniques programming Hardware mixed integer linear programming

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Network-constrained unit commitment with piecewise linear AC power flow constraints

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ELECTRIC POWER SYSTEMS RESEARCH 2021年 195卷

作者： Nanou, Sotirios, I Psarros, Georgios N. Papathanassiou, Stavros A. Natl Tech Univ Athens NTUA Sch Elect & Comp Engn 9 Iroon Polytech Str Athens 15780 Greece

This paper presents a new network-constrained unit commitment (UC) model, which is formulated as a mixedinteger linear programming (MILP) optimization problem with embedded ac power flow (AC-PF) constraints. Piecewise linear AC-PF equations are formulated, which constrain the UC dispatch schedule within permissible transmission capacity and voltage deviation limits, solely by executing the main optimization problem. The proposed model is tested on a six-bus and the IEEE RTS-79 test systems, using GAMS software, whereas the obtained AC-PF results are validated against DIgSILENT/Powerfactory package. The UC schedules are comparatively assessed with detailed results presented in the relevant literature for the same test systems, employing different UC+AC-PF models.

关键词： Unit commitment AC power flow mixed integer linear programming Piecewise linearization

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A hybrid stochastic/robust-based multi-period investment planning model for island microgrid

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2021年 130卷

作者： Liu, Yixin Guo, Li Hou, Ruosong Wang, Chengshan Wang, Xiaoxue Tianjin Univ Minist Educ Key Lab Smart Grid Tianjin 300072 Peoples R China Hebei Univ Technol State Key Lab Reliabil & Intelligence Elect Equip Tianjin 300072 Peoples R China

Microgrid is becoming an effective way to solve the power supply problem in off-grid islands. The investment economy is one of the key factors affecting its development and application, which is very challenging due to various uncertain information involved in the investment decision process. In this paper, a multi-period investment planning model is proposed to support decision-making for the stakeholders in determining the optimal sizing as well as investment timing of distributed energy resources of an island microgrid. The applicability of the model in dealing with various uncertainties is enhanced via a hybrid optimization framework, in which the longterm uncertainty of energy price fluctuation is captured by a stochastic programming approach and the shortterm variations of renewable energy generation and load are addressed through robust optimization method. The dynamic information of load growth, unit cost variation and device degradation are considered to make the decision more practical and economically attractive. The multi-period investment planning model is formulated as a mixed integer linear programming problem, and the conservatism of the decision can be flexibly adjusted by regulating the robustness of the model. Simulation results based on actual data illustrate that the proposed model shows better economic and synergetic performances than the traditional multi-year optimization model, with the total planning cost dropped by nearly 3.6%, the initial investment cost reduced by nearly 36.6%, and the utilization rate of renewable energy increased by nearly 5.4%. In addition, the sensitivity analyses for load growth rate, loan ratio, unit cost, and uncertain budgets further verify the applicability of the proposed model under various conditions.

关键词： Island microgrid Multi-period investment planning Stochastic robust hybrid optimization mixed integer linear programming

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