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2021 International MultiConference of Engineers and Computer Scientists, IMECS 2021

作者： Diaba, Sayawu Yakubu Elmusrati, Mohammed Shafie-Khah, Miadreza The School of Technology and Innovation University of Vaasa Vaasa Finland

ISBN: (纸本)9789881404916

This paper introduces a novel concept for customer load scheduling in the Smart Grid (SG). The concept is based on the forthcoming internet of things (IoT). Approximate optimization algorithms are deduced for optimum customer load scheduling, maximization of electric power suppliers performance, and fairness in scheduling customers load. Using these approximate optimization algorithms as constraints, some loads are given priority. Other loads are scheduled in order to control the maximum demand load and electricity bills. To evaluate the effectiveness of the algorithms, we utilize the mixed integer linear programming (MILP). Simulations are carried out and the impact on reducing the peak-to-average power ratio (PAPR), the electricity bills, and ensuring fairness in customers load schedules are investigated. Simulation results establish that our algorithms significantly cut down on electricity bills, maximizes utility performance, and deliver fairness in customers load schedules. © 2021 Newswood Limited. All rights reserved.

关键词： Demand response (DR) Electric vehicle (EV) Internet of things Load scheduling mixed integer linear programming Optimization algorithms Power management system (PMS) Smart grid

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Thermal-aware detour routing in 3D NoCs

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JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING 2020年 144卷 230-245页

作者： Mukherjee, Priyajit Chatterjee, Navonil Chattopadhyay, Santanu Indian Inst Technol Kharagpur Dept Elect & Elect Commun Engn Kharagpur 721302 W Bengal India

Three-dimensional Network-on-Chips (3D NoCs) is a popular design choice due to its low packet latency, low network power consumption and high packing density. However, 3D NoCs suffer from high temperature issues. The 3D stacking of Si-layers elongates heat transfer path from different Si-layers to the heat sink resulting in increase in peak temperature of the chip. Since routers of NoCs have high power densities, a higher router activity may result in signification increase in temperature of the chip. Therefore, a judicious selection of the routing path is necessary to reduce the chip temperature. As the routers placed at the lower Si-layers have higher thermal conductance to the heat sink, a routing path consisting of more number of routers in the lower Si-layers may improve the temperature profile of the chip. In this paper, we have proposed two different thermal-aware routing approaches, which use downward detoured routing for some optimally selected communication paths to reduce the chip temperature. The first technique is a thermal-aware application-specific mixed integer linear programming based method (named TMD), while the second one is an application-agnostic heuristic approach (named TSD). To predict the effect of detour decisions on the temperature profile of the chip, TMD technique has applied two different thermal models with a constraint on the average packet delay (APD) of the network. Experimental results show that a significant temperature reduction (up to 22 degrees) can be achieved within minimal performance loss (10% increase in APD) using either of the proposed techniques, compared to the minimal path routing algorithms - XYZ, ZXY and EDGE and the greedy detour approaches - All Detour and Random Detour. (C) 2020 Elsevier Inc. All rights reserved.

关键词： 3D network-on-chip mixed integer linear programming Thermal-aware routing Average packet delay

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Optimized power dispatch for solar photovoltaic -storage system with multiple buildings in bilateral contracts

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APPLIED ENERGY 2020年 273卷

作者： Ahsan, Syed M. Khan, Hassan A. Hassan, Naveed-ul Arif, Syed M. Lie, Tek-Tjing Lahore Univ Management Sci SBA Sch Sci & Engn Dept Elect Engn Lahore 54792 Pakistan Auckland Univ Technol Sch Engn Comp & Math Sci Elect & Elect Engn Dept Auckland New Zealand

Storage coupled solar photovoltaic systems have gained traction in recent years due to a) advancements in battery storage technologies and b) decreasing system costs. The viability and optimum operation of these systems is typically studied for building(s) in isolation or with grid interactions. In this paper a grid-interactive photovoltaic-storage system in a multi building scenario with net-metering is evaluated. A simulation model is developed for an interconnected multi building environment with a primary building owning the photovoltaic- battery system. The optimization model is formulated as a mixed integer linear programming problem and is solved in ILOG optimization studio with CPLEX solver. Multiple secondary buildings can procure power from the primary building based on suitable bilateral contracts. The applicability of the model is demonstrated through real-time load demand of three buildings along with actual time-of-use pricing data from the utility in the city of Auckland, New Zealand. The results provide an insight on the financial gains of installing rooftop photovoltaic- battery systems at buildings with power trading agreements under time-varying electricity tariffs. The detailed results from the model signify that primary building (with solar and storage) earns up to 43% of annual profits after incorporating installation costs of photovoltaic-battery system. Further, secondary buildings (without solar or storage) achieve 3-16% of savings in the electricity costs based on different contracted loads and agreement tariffs. This work can further enhance the utilization of solar energy resource via rooftop solar photovoltaic to help mitigate the per capita carbon dioxide emissions in countries with high dependency over fossil fuel for electricity generation.

关键词： Photovoltaics Energy storage system mixed integer linear programming Commercial buildings Bilateral contracts Techno-economic assessment

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MARS: A Multi-Attribute Routing and Scheduling Algorithm for DTN Interplanetary Networks

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IEEE-ACM TRANSACTIONS ON NETWORKING 2020年第5期28卷 2065-2076页

作者： El Alaoui, Sara Ramamurthy, Byrav Univ Nebraska Dept Comp Sci & Engn Lincoln NE 68588 USA

The Interplanetary Network (IPN) or the Interplanetary Internet is a network composed of interconnected space objects, which are in turn connected to mission control stations on the surface of Earth. The IPN is our only portal to the deep space, and yet it has been relatively sparse, until recently. With the ongoing and the planned missions to the outer space, the Delay Tolerant Networking (DTN) based network infrastructure will require more scalable routing and scheduling algorithms. In this paper, we propose the first mixed integer linear programming (MILP) model for message routing and scheduling in the IPN using Multi-Attribute Decision Making (MADM) principles. Based on this model, we propose a novel MADM-based algorithm called Multi-Attribute Routing and Scheduling (MARS) algorithm. This algorithm uses a sliding window of size n to schedule the first n messages in the buffer based on multiple attributes. After finding the optimal schedule for these messages (in terms of delivery rate), they are routed using our proposed Dijkstra-based routing algorithm. We use an existing MADM technique, PROMETHEE II, and consider the four main attributes of a message: size, priority, time to live (TTL), and time in buffer (TiB). Finally, we run multiple simulation experiments in order to test the performance of the proposed MARS and show that MADM coupled with scheduling and routing in IPN delivers at least three times more messages than a previously proposed technique, the Contact Graph Routing (CGR), while significantly reducing the average end-to-end delay and overhead.

关键词： Routing Scheduling Mars Space missions Delays Routing protocols Aerospace electronics Delay Tolerant Networking Interplanetary Networks Satellite Communication Joint Scheduling and Routing Multiple Attribute Decision Making MADM PROMETHEE II contact Graph Routing mixed integer linear programming Multi-Attribute Routing and Scheduling

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Optimized scheduling of multi-region Gas and Power Complementary system considering tiered gas tariff

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ENERGY 2020年 193卷 197-221页

作者： Zhou, Suyang Zhuang, Wennan Wu, Zhi Gu, Wei Zhan, Xin Liu, Zhong Cao, Siming Southeast Univ Sch Elect Engn 2 Sipailou Xuanwu Qu Nanjing 210096 Peoples R China State Grid Cooperat China Yangzhou Power Supply Co Jiangsu Elect Power Co 179 Weiyang Rd Yangzhou 225000 Jiangsu Peoples R China

Integrated Energy System (IES) based on Combined Cooling, Heating and Power (CCHP) technology has been proved as an efficient approach, which can resolve energy and environment issues and meanwhile bring economic benefits. For areas with fragile grid infrastructure and abundant oil, gas and renewable resources, various types of energy sources can complement each other and be cooperated as a unity, by operating the energy networks across regions as a single IES through the implementation of multi-region Gas and Power Complementary (GPC) system. Conventionally, the typical optimized scheduling of GPC system does not consider the complementarity among areas with diverse device and load characteristics. Since changes and developments have occurred in power-to-gas conversion technologies and intraregional CCHP system, traditional models need to be updated and improved along with the application of tiered gas price. Based on the existing coupled power-gas flow scheduling model, this paper proposed a multi-region optimized scheduling model where the CCHP systems operated inside a region and power-gas complementarity could be achieved among multiple regions. mixed integer linear programming (MILP) was used to obtain the optimal solution of this scheduling model. The compressor linearization model was designed in order to describe transmission loss of the gas network and perfect the power-gas flow model as well. Results of cases proved that considerable environmental benefits could be achieved when Combined Heating and Power (CHP) equipment was introduced in the multi region GPC system. Finally, combined with the tiered gas tariff, the total operation cost of regions could be reduced and the day-ahead economic optimized scheduling could be improved. It also showed that the operating parameters in each region expressed different sensitivity to gas price due to the flow constraints. Moreover, compared with battery energy storage systems, power-to-gas conversion technology woul

关键词： Combined cooling Heating and power Multi-region gas and power complementary system mixed integer linear programming Compressor linearization Tiered gas tariff Day-ahead economic optimized scheduling

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Comparison of optimization frameworks for the design of a multi-energy microgrid

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APPLIED ENERGY 2020年 257卷

作者： Rigo-Mariani, Remy Wae, Sean Ooi Chea Mazzoni, Stefano Romagnoli, Alessandro Nanyang Technol Univ Energy Res Inst NTU ERI N Singapore Singapore Nanyang Technol Univ Sch Mech & Aerosp Engineer Singapore Singapore

The scope of the paper is to investigate different strategies for the design of a multi-energy system considered as a systemic optimization problem. The objective is to determine the best sizes of the energy assets such as electrochemical and thermal storages, cogeneration units, solar generators and chillers. In these cases, the techno-economic optimization is a tradeoff between the operating costs and the capital expenditures in the form of integrated management and design of the system. The paper addresses the challenges of these optimization problems in two steps. The former implements generic piecewise linearization techniques based on non-linear models. That approach allows a significant reduction of the computational time for the management loop of the assets (i.e. optimal power dispatch). The latter takes into consideration the integration of that management loop in different architectures for optimal system planning. The main contribution of the paper toward filling the gap in the literature is to investigate a wide range of optimization frameworks - with bi-level optimizations (using both deterministic and evolutionary methods), Monte-Carlo simulations as well as a performant 'all-in-one' approach in which both sizes and controls are variables of a single mathematical problem formulation. Finally, a thorough results analysis highlights that the best solution tends to be the same whether the objective to optimize is the traditional net present value at the end of the system lifespan or the total yearly cost of ownership.

关键词： Multi-energy Optimal planning Quadratic programming mixed integer linear programming Evolutionary algorithms

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An ILS heuristic for the ship scheduling problem: application in the oil industry

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INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH 2020年第1期27卷 197-218页

作者： Cunha, Victor Santos, Iuri Pessoa, Luciana Hamacher, Silvio Pontificia Univ Catolica Rio de Janeiro DEI Ind Engn Dept 225 Gavea BR-22430060 Rio de Janeiro Brazil

This paper addresses a real-life rescheduling problem of a pipe-laying support vessel (PLSV) fleet in charge of subsea oil well connections. The short-term schedule of these vessels is subject to uncertainties inherent to its operations, resulting in ships idleness or delays in oil production. The objective of this study is to develop methods to support a Brazilian oil and gas company in overcoming impacts caused by operational disruptions, while reaching its planned production level. The PLSV rescheduling problem was treated as an identical parallel machine scheduling problem, where the machines represent the vessels and the jobs are the activities for the subsea well connections. We propose a mathematical programming model and a method based on the iterated local search (ILS) metaheuristic to solve the problem. This paper contributes to this by considering simultaneously setup times, machine eligibility, release dates, due dates, and machine availability. Both methods were applied on 10 instances based on real PLSV data. Taking into account an objective function that measures the operational impact on schedules, the ILS provided an average improvement above 91% in schedules when compared to the initial solution provided by the studied company. The ILS outperformed a mathematical programming model for the problem, in eight instances, within a 30-minute execution time limit, fitting to the company process.

关键词： oil industry ship scheduling iterated local search metaheuristics mixed integer linear programming

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Should environmental constraints be considered in linear programming based water value calculators?

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2020年 117卷

作者： Guisandez, Ignacio Ignacio Perez-Diaz, Juan Nowak, Wolfgang Haas, Jannik Univ Politecn Madrid Dept Hydraul Energy & Environm Engn E-28040 Madrid Spain Univ Stuttgart Dept Stochast Simulat & Safety Res Hydrosyst IWS D-70569 Stuttgart Germany

We evaluate the practical usefulness of incorporating maximum ramping rates and minimum environmental flows into a linear programming based water value calculator for hydropower plants that participate in the day-ahead electricity market. The methodology consists of three steps: first computing the water value once with and once without environmental constraints, then simulating the plant operations using each water value, and finally comparing the simulation profits. A set of nine representative hydropower plants formed by combinations of three real locations (in Colombia, Norway and Spain) and three turbine configurations (from one to three Francis units) are individually analyzed. Each plant is simulated in two synthetic 10-year long series subject to fifteen combinations of maximum ramping rates and minimum flows with the two above-mentioned water values, totaling 540 simulations. The results indicate that incorporating the analyzed environmental constraints into a linear programming based water value calculator can be significantly profitable only when the hydropower plants have only one or at most two turbines.

关键词： Maximum ramping rate Minimum environmental flow linear programming mixed integer linear programming Stochastic dynamic programming

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Hybrid electric topology for short sea ships with high auxiliary power availability requirement

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ENERGY 2020年 190卷

作者： Ritari, Antti Huotari, Janne Halme, Jukka Tammi, Kari Aalto Univ Sch Engn Dept Mech Engn Espoo Finland Aalto Univ Sch Elect Engn Dept Elect Engn & Automat Espoo Finland

The inclusion of a battery system for a diesel mechanical short sea ship was investigated. The main benefits of the battery were assumed to emerge from shaving thruster generated power peaks, rather than starting additional generating sets to accommodate the power demand and additionally from replacing a diesel engine as a reserve power source. To support the analysis, an auxiliary engine power output dataset of a roll-on/roll-off passenger ferry operating in the Baltic Sea was acquired. Required capacity for the battery system was derived by considering power availability requirements and battery safety margins for performance deterioration. A multi-period mixed-integer linear programming model was developed to derive a globally optimal power management strategy for the auxiliary engines and the battery, with the goal of minimizing the battery installation total cost. The battery system was found to reduce fuel oil consumption by 257.5 tons annually due to improved auxiliary engine efficiency alone. Furthermore, the battery system total cost advantage was found to vary from -(sic)0.61 to (sic)2.82 million during the ten-year investment period, depending on fuel oil and battery system costs applied in the modeling. For the studied case ship, the hybrid electric topology was concluded to be economically feasible. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Hybrid ship Energy efficiency Energy storage Battery mixed integer linear programming Optimization

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Optimizing the Design of Supply Chains for Carbon Capture, Utilization, and Sequestration in Europe: A Preliminary Assessment

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FRONTIERS IN ENERGY RESEARCH 2020年 8卷

作者： D'Amore, Federico Bezzo, Fabrizio Univ Padua Dept Ind Engn Comp Aided Proc Engn Lab CAPE Lab Padua Italy

Carbon capture and storage represents a key technology for reducing the anthropogenic emissions of greenhouse gases. In addition to this, carbon utilization has often been considered as a viable option for increasing the environmental benefits, while decreasing costs of the mere capture and storage system. This contribution proposes an optimization framework for the design of carbon capture, transport, utilization, and storage supply chains in the European context. Based on literature data, technologies converting CO(2)into methanol and polyether carbonate polyols were selected as the most promising and incorporated into the optimization framework. The goal is to reduce 50% of European emissions from large stationary sources by 2030. Results highlight that, under our assumptions, the significance of carbon utilization in terms of a reduction of the environmental impact is likely to be a minor one: considering the current state of technologies only about 2.4% of the overall CO(2)emitted from large stationary sources can be removed by chemical utilization. However, significant benefits can be obtained in terms of overall cost reduction thanks to revenues deriving from the chemicals being produced.

关键词： carbon capture utilization and storage supply chain optimization mixed integer linear programming European framework CO(2)chemical conversion and utilization

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