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Optimization Model for the Long-Term Operation of an Interprovincial Hydropower Plant Incorporating Peak Shaving Demands

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ENERGIES 2020年第18期13卷

作者： Cao, Rui Shen, Jianjian Cheng, Chuntian Wang, Jian Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Utah State Univ Dept Civil & Environm Engn 4110 Old Main Logan UT 84322 USA

The increasing peak-to-valley load difference in China pose a challenge to long-distance and large-capacity hydropower transmission via high-voltage direct current (HVDC) lines. Considering the peak shaving demands of load centers, an optimization model that maximizes the expected power generation revenue is proposed here for the long-term operation of an interprovincial hydropower plant. A simulation-based method was utilized to explore the relationships between long-term power generation and short-term peak shaving revenue in the model. This method generated representative daily load scenarios via cluster analysis and approximated the real-time electricity price of each load profile with the time-of-use price strategy. A mixed-integer linear programming model with HVDC transmission constraints was then established to obtain moving average (MA) price curves that bridged two time-coupled operations. The MA price curves were finally incorporated into the long-term optimization model to determine monthly generation schedules, and the inflow uncertainty was addressed by discretized inflow scenarios. The proposed model was evaluated based on the operation of the Xiluodu hydropower system in China during the drawdown season. The results revealed a trade-off between long-term energy production and short-term peak shaving revenue, and they demonstrated the revenue potential of interprovincial hydropower transmission while meeting peak shaving demands. A comparison with other long-term optimization methods demonstrated the effectiveness and reliability of the proposed model in maximizing power generation revenue.

关键词： hydropower system HVDC transmission peak shaving energy price mixed-integer linear programming

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The impacts of an integrated European adjustment market for electricity under high share of renewables

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ENERGY POLICY 2020年 136卷

作者： Zalzar, Shaghayegh Bompard, Ettore Purvins, Arturs Masera, Marcelo Politecn Torino Dept Energy Turin Italy European Commiss DG JRC Energy Secur Distribut & Markets Unit Energy Transport & Climate Directorate Petten Netherlands

The European Commission has set a target of establishing an integrated Europe-wide electricity market for day-ahead and intraday transactions. However, there are still many open questions on the potential benefits of a Europe-wide intraday market integration and the harmonizing market rules. This paper intends to provide a precise insight into the potential impacts of EU policies regarding integrating electricity markets on market efficiency and on different market players with the aim of supporting policy makers to increase the penetration of renewables in a cost efficient manner. In this paper, we investigate and compare the current option of regional intraday electricity market with the option of an integrated Europe-wide one, with reference to the three European test cases with high renewable penetration: the Iberian electricity market including Spain and Portugal, the Italian electricity market including Italy and Slovenia, and the electricity market of Germany. We consider two 2030 scenarios: (i) the regional/local intraday electricity market, and (ii) the integration of the current regional intraday market of the test cases into a single intraday market in Europe. The two scenarios are modelled through stochastic Monte Carlo simulation, considering uncertainty on electricity demand, wind and solar power. The performance of the intraday market under the two options are compared in terms of generation cost, electricity prices, producer' surplus, and load expenditure inside the European test cases. The simulation results lead to the conclusion that integrating to a Europe-wide intraday electricity market is not advantageous for power producers inside the European countries with high share of variable renewable generation, in terms of annual generation surplus. However, from the customers' point of view, intraday market integration is beneficial, leading to lower cost to loads. Furthermore, it is shown that the flexibility provided by the installed capacity of hy

关键词： Intraday market Monte-carlo simulation mixed-integer linear programming Market coupling Operating reserve

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A prediction-based optimization strategy to balance the use of diesel generator and emergency battery in the microgrid

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INTERNATIONAL JOURNAL OF ENERGY RESEARCH 2020年第7期44卷 5425-5440页

作者： Liu, Zhonghua Zhang, Huihui Dong, Jichang Yu, Hua Beijing Univ Chem Technol Coll Econ & Management Beijing 100029 Peoples R China China Elect Power Res Inst Informat & Commun Dept Beijing Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing Peoples R China Univ Chinese Acad Sci Sch Engn Sci Beijing Peoples R China

This paper presents a prediction-based optimization strategy (POS) for the Energy Management System to balance the use of diesel generator (DG) and emergency battery (EB) in the microgrid. The POS is developed by combing two operating strategies, the "predictive analysis" and "optimal operation" in each scheduling period for the microgrid. Based on the predicted microgrid state and energy demand, a multi-objective mixed-integer nonlinear programming model (MOMINP) is constructed to minimize the fuel consumption and the regularization of battery charge/discharge subject to the practical constraints in the microgrid. This paper proposes a detailed scheme to deal with the multiple objectives and nonlinear constraints in the MOMINP, then the MOMINP is successfully converted into a mixed-integer linear programming model (MILP). And an adjustment strategy is designed to obtain the nearoptimal solution of the MOMINP based on the optimal solution of the MILP solved by using the CPLEX Optimizer. Experimental results show that in a basic scheduling period, the working time of DG in the POS-softmax regression strategy is shorter than the current operation, and the fuel consumption reduction ratio is about 15.3% with the same battery SoC value at the end of the scheduling. At the same time, the fuel consumption in the POS-accurate prediction strategy can be reduced by up to 54.9% compared with the POS-softmax regression strategy and can be reduced by 61.8% compared to the current operation. Based on the comparative analysis of the actual case data of a micro-grid in 6 months, it can be seen that on average the POS works better than the current operation, with an approximately 23.6% decrease in the objective function and an additional 16.2% decrease with an accurate prediction.

关键词： energy management microgrid mixed-integer linear programming multi-objective mixed-integer nonlinear programming optimal operation

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Future scenario of China's downstream oil supply chain: Low carbon-oriented optimization for the design of planned multi-product pipelines

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JOURNAL OF CLEANER PRODUCTION 2020年 244卷

作者： Zhou, Xingyuan Zhang, Haoran Xin, Shengchao Yan, Yamin Long, Yin Yuan, Meng Liang, Yongtu China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Natl Engn Lab Pipeline Safety Fuxue Rd 18 Beijing 102249 Peoples R China Univ Tokyo Ctr Spatial Informat Sci 5-1-5 Kashiwanoha Kashiwa Chiba 2778568 Japan Univ Tokyo Grad Sch Frontier Sci Dept Environm Syst 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan

With the increasing demand of refined products and growing concern about carbon emissions, the planned multi-product pipelines, serving as the primary way of refined products transportation, should be designed reasonably, economically, and low carbon-oriented so that the sustainable and environmentally friendly production and the rational construction of downstream oil supply chain can be achieved. Aiming at this issue, a multi-objective mixed-integer linear programming (MILP) model is proposed to minimize the total economic costs and CO2 emission simultaneously. Various actual process and technical constraints including pipeline construction, pump stations layout, pipeline hydraulic and pumps configurations are considered in the model. Based on the augmented 8-constraint method, the conflicting objectives are dealt with and the Pareto front can be get. Finally, based on a predicted future scenario of regional refined products demand, the proposed model was successfully applied to a realword planned multi-product pipeline in China. Two cases are given to demonstrate the model's applicability and the influence of CO2 emission objective on the pipeline design scheme determination. Meanwhile, the trade-off between the two objectives was analyzed in detail. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Planned multi-product pipeline Low carbon-oriented optimal design mixed-integer linear programming CO2 emission Augmented e-constraint method

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Energy Cost-Efficient Task Positioning in Manufacturing Systems

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ENERGIES 2020年第19期13卷

作者： Bozek, Andrzej Rzeszow Univ Technol Dept Comp & Control Engn Al Powstancow Warszawy 12 PL-35959 Rzeszow Poland

A problem to determine a production schedule which minimises the cost of energy used for manufacturing is studied. The scenario assumes that each production task has assigned constant power consumption, price of power from conventional electrical grid system is defined by time-of-use tariffs, and a component of free of charge renewable energy is available for the manufacturing system. The objective is to find the most cost-efficient production plan, subject to constraints involving predefined precedence relationships between the tasks and a bounded makespan. Two independent optimisation approaches have been developed, based on significantly different paradigms, namely mixed-integer linear programming and tabu search metaheuristic. Both of them have been verified and compared in extensive computational experiments. The tabu search-based approach has turned out to be generally more efficient in the sense of the obtained objective function values, but advantages of the use of linear programming have also been identified. The results confirm that it is possible to develop efficient computational methods to optimise energy cost under circumstances typical of manufacturing companies. The set of numerous benchmark instances and their solutions have been archived and it can be reused in further research.

关键词： energy cost minimisation production planning time-of-use tariffs renewable energy source mixed-integer linear programming tabu search

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Optimal production planning for flexible manufacturing systems: an energy-based approach

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IFAC-PapersOnLine 2020年第2期53卷 10461-10467页

作者： Jenny L. Diaz C. Carlos Ocampo-Martinez Automatic Control Department Universitat Politècnica de Catalunya Institut de Robòtica i Informàtica Industrial (CSIC-UPC) Llorens i Artigas 4-6 08028 Barcelona Spain

Production programming in a manufacturing industry is usually performed based on off-line optimisations of the processing times or plant productivity. However, most of these approaches do not consider the energy market and its fluctuations. Therefore, it is not possible to take advantage of these fluctuations to also minimise the energy costs and to increase the plant profit. In this regard, a control strategy based on the economic Model Predictive Control approach is proposed to reduce energy costs during the operation of a manufacturing plant. The proposed controller determines the instants in which the production programs should be executed to satisfy the daily demand while minimising the energy costs through regular updates of the energy prices according to the current energy market. Besides, by implementing a control strategy in real time, changes in the demand of parts according to the customer requirements could also be considered, adding more flexibility to the plant operation. The proposed control strategy has been tested in simulation, and the obtained results show that energy costs can be reduced without affecting the plant productivity.

关键词： economic model predictive control energy costs economic production programming mixed-integer linear programming

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Optimal production scheduling for smart manufacturers with application to food production planning

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COMPUTERS & ELECTRICAL ENGINEERING 2020年 84卷

作者： Angizeh, Farhad Montero, Hector Vedpathak, Abhinay Parvania, Masood Univ Utah Dept Elect & Comp Engn Salt Lake City UT 84112 USA

This paper aims at implementing an optimization technique in smart manufacturing applications for co-optimizing the operation of multiple production lines to supply the desired demand for multiple products. The proposed model, which is formulated as a mixedinteger linear programming (MILP) problem, minimizes the total manufacturing cost by co-optimizing the operation schedule of production lines. The proposed model implements several operating constraints of the production lines that include their energy consumption and associated costs, productivity, scrap rates, changeover duration, and labor costs. The proposed model is implemented on a sample manufacturer, where seven production lines with different operational constraints are optimized to manufacture six product types. In addition, the model is utilized to optimize the operation of a real-world food production plant with five lines and twelve different product types. The simulation results show that the proposed optimal scheduling model allows the manufacturers to enhance production efficiency and save on operation costs by co-optimizing the operation schedule of production lines. Sensitivity analyses are conducted to demonstrate the performance of the model in different demand levels, where the manufacturers are enabled to optimally schedule the production lines at minimum cost given the production demand. (c) 2020 Elsevier Ltd. All rights reserved.

关键词： Smart manufacturing mixed-integer linear programming Energy cost reduction Energy flexibility Demand response Production planning

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Distance-based measures of incoherence for pairwise comparisons

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KNOWLEDGE-BASED SYSTEMS 2020年 187卷

作者： Brunelli, Matteo Cavallo, Bice Univ Trento Dept Ind Engn Via Sommarive 9 I-38123 Trento Italy Univ Napoli Federico II Dept Architecture Via Toledo 402 I-80134 Naples Italy

Coherence of preferences, and the measurement of its violation, has been a long standing issue in decision analysis. This paper focuses on preferences expressed by means of Pairwise Comparison Matrices. Whereas the consistency, that represents the full coherence, has been quantitatively measured by means of many indices proposed in literature, the same cannot be said for the other coherence conditions;as an example, thus far, the deviation of a set of preferences from transitivity condition has been represented by simple counts of how many times the transitivity condition is violated. As simple counts use only ordinal information discarding the information related with intensities of preferences, this manuscript introduces a cardinal approach where the deviation from the transitivity, and from further coherence levels, is seen as a matter of degree. This approach seems more suitable to cardinal preference relations where the decision makers' preferences themselves are a matter of degree. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Decision analysis Preference relations Coherence Pairwise comparison matrices mixed-integer linear programming

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Multi-type electric vehicle relocation problem considering required battery-charging time

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EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING 2020年第3期14卷 335-368页

作者： Singgih, Ivan Kristianto Kim, Byung-in Pohang Univ Sci & Technol POSTECH Dept Ind & Management Engn Pohang 37673 Gyeongbuk South Korea

This research discusses an electric vehicle (EV) relocation problem, wherein multiple types of EVs are transported using heterogeneous trucks. The initial position, battery level of the EVs, and the required number of EVs and empty parking slots at each station are provided as inputs. Relocations are performed during the night, while no EVs are used. Before the end of the relocation planning horizon, each EV must be charged to a certain battery level. The charging process can only be performed when the EV is not being transported. The objectives are to minimise the total transportation costs, the total truck fixed costs, and the total unsatisfied empty parking slot requirements while ensuring that all EV demands are satisfied. A mixed-integer linear programming (MILP) model and construction and improvement heuristic approaches are proposed. The results of the computational experiments indicate that the proposed approaches perform well. [Received: 25 February 2019;Accepted: 26 August 2019]

关键词： electric vehicle relocation battery-charging heterogeneous truck heuristic adaptive large-neighbourhood search mixed-integer linear programming MILP

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Standardised modelling and optimisation of a system of interconnected energy hubs considering multiple energies-Electricity, gas, heating, and cooling

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ENERGY CONVERSION AND MANAGEMENT 2020年 205卷

作者： Liu, Tianhao Zhang, Dongdong Wu, Thomas Guangxi Univ Sch Elect Engn Nanning Peoples R China Univ Hong Kong Dept Elect & Elect Engn Hong Kong Peoples R China Xi An Jiao Tong Univ Sch Elect Engn Xian Peoples R China Univ Cent Florida Dept Elect & Comp Engn Orlando FL 32816 USA

The system of interconnected energy hubs (EHs) is a key multi-carrier energy system (MES) model. It is difficult, however, to directly calculate the operational state of the model because of its highly dimensional nonlinear characteristics. To resolve the foregoing problem, a standardised modelling and optimisation method for the system of interconnected EH model is introduced in this paper. In this proposed method, one-dimensional and multi-dimensional piecewise linear approximation methods are adopted to simplify non-convex natural gas transmission functions, generator cost functions, and compressor function. Moreover, a multi-step linearisation method is applied to EHs. The whole system can accordingly be reformulated as a mixed-integer linear programming (MILP) problem. In contrast to the traditional model, the formulated MILP model is effortlessly implemented in the optimisation of the MES with existing advanced optimisation techniques. Finally, the method is verified using a modified three-hub interconnected system. The test results show that the method can save more than 90% computational time with sufficient accuracy. The results also demonstrate that the unified dispatch exploits different energy resources, and the applied energy storage devices can reduce the operational cost from $319,840.267 to $316,382.685.

关键词： Multi-carrier energy systems System of interconnected energy hubs Energy storage Energy management Piecewise linear approximation method mixed-integer linear programming

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