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Transmission Network Expansion Planning Considering Line Switching

IEEE ACCESS 2020年 8卷 115148-115158页

作者： Meneses, Marco Nascimento, Edgar Macedo, Leonardo H. Romero, Ruben Sao Paulo State Univ Dept Elect Engn BR-15385000 Ilha Solteira Brazil Fed Inst Educ Sci & Technol Mato Grosso BR-78050000 Cuiaba Brazil

Commonly, in the transmission network expansion planning (TNEP) problem, the objective is to define the minimal-cost investment in new transmission devices, e.g., the transmission lines and transformers, for the system to operate adequately in a planning horizon. In addition to the traditional approach of considering the installation of new components, the presented model considers the enhancement of the system operation performance through the modification of its topology in each operation scenario. This modification is made by switching off the lines that degrade the system's performance. By using an illustrative example, we discuss why congestion is eliminated by switching off specific lines from the system, thereby improving the performance of the existing network and constructed candidate lines and leading to lower investment costs. The proposed method also considers a strategy to reduce the number of lines switched off in order to improve the reliability of the system and avoid alternative optimal solutions with unnecessary lines switched. The tests are carried out using the 46-bus southern Brazilian system and the IEEE 24-bus system, which are usually used as benchmarks for the TNEP problem. The results are compared with the solutions of the traditional model for TNEP to show the efficiency of the proposed approach.

关键词： Disjunctive model mixed-integer linear programming network planning transmission switching

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Short-term generation scheduling of cascade hydropower plants with strong hydraulic coupling and head-dependent prohibited operating zones

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JOURNAL OF HYDROLOGY 2020年 591卷 125556-125556页

作者： Su, Chengguo Yuan, Wenlin Cheng, Chuntian Wang, Peilin Sun, Lifei Zhang, Taiheng Zhengzhou Univ Sch Hydraul Sci & Engn Zhengzhou 450001 Peoples R China Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China Minist Water Resources Gen Inst Water Resources & Hydropower Planning & Beijing 100120 Peoples R China Huadian Elect Power Res Inst Co LTD Hangzhou 310030 Peoples R China

A lot of large hydropower plants have been built in China in the past few decades. Large-capacity hydropower units usually have multiple prohibited operating zones (POZs) varying with the net head. Many cascade hydropower plants are hydraulically coupled because the distance between the upstream and downstream reservoirs is so small that the forebay water level of the downstream reservoir will influence the tailwater level of its immediate upstream reservoir. The integrated consideration of the strong hydraulic coupling between cascade hydropower plants, the head-dependent POZs of individual units, and other operation constraints make the daily operation of cascade hydropower plants very challenging for both operators and researchers. Therefore, this paper has developed an accurate optimization model for determining the hourly generation scheduling of cascade hydropower plants with strong hydraulic coupling and head-dependent POZs. The objective is to maximize the total profits of the cascade hydropower plants from selling electricity in the day-ahead market. To solve such a complicated mathematical model with non-convex and nonlinear features, the model is converted into a mixed-integer linear programming (MILP) formulation using multiple linear approximation techniques so as to take full advantage of the effective and mature commercial solvers. The MILP formulation focuses mainly on addressing two nonlinearities, namely the three-dimensional tailwater level curves and head-dependent POZs, which are approximated through the piecewise linear interpolations based on the meshing and triangulation technique. The developed model is applied to the optimal operation of the Tianshengqiao cascade hydropower plants which are located on the Hongshui River, China. The optimization results demonstrate that the proposed model is able to be applied in the short-term generation scheduling of cascade hydropower plants in different hydrological conditions, and the optimized total pr

关键词： Cascade hydropower plants Strong hydraulic coupling Head-dependent prohibited operating zones mixed-integer linear programming

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A matheuristic for a bi-objective demand-side optimization for cooperative smart homes

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ELECTRICAL ENGINEERING 2020年第4期102卷 1913-1930页

作者： Garroussi, Zineb Ellaia, Rachid El-ghazali-Talbi Lucas, Jean-yves Mohammed V Univ Rabat Mohammadia Sch Engineers Engn Smart & Sustainable Syst Res Ctr E3S LERMA Lab Ibn Sina Ave 765 Rabat Morocco Inria Lille Nord Europe Res Ctr Big Optimizat & Ultra Scale Comp Team BONUS F-59655 Villeneuve Dascq France Elect France SA EDF R&D 1 Ave Gen de Gaulle F-92140 Clamart France

This paper proposes the demand-side management (C-DSM) of collaborative homes during one day. Some homes may have photovoltaic panels and batteries, other homes may have batteries, and the remaining homes are pure energy consumers. Homes are interconnected and connected to the main grid. The proposed C-DSM is formulated as a constrained bi-objective and mixed-integer linear optimization model with one objective related to the total net energy cost and the other related to discomfort caused by allowing flexibility of controllable loads within an acceptable comfort range. A matheuristic approach has been proposed to determine an efficient Pareto set for the problem, combining the non-dominated sorting genetic algorithm II (NSGAII) with an exact solver. In this approach, discrete decision variables are represented as partial chromosomes and an exact solver determines the continuous decision variables in an optimal way. A number of simulations are performed and compared with the weighted sum algorithm (WSA) under four cases for small to large number of homes. The results demonstrate the effectiveness of power cooperation among homes and show that our algorithm is able to obtain more Pareto solutions in a much shorter time that are far better than those obtained by the WSA. The proposed algorithm is suitable for large-sized C-DSM problem instances, promotes power cooperation between homes, reduces the dependency to the main grid and achieves individual fairness of energy net cost of each home without the need for installation of photovoltaic panels and batteries for all homes.

关键词： Microgrids Demand-side management of multiple homes Multi-objective evolutionary algorithm mixed-integer linear programming Matheuristic

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Optimal planning and modular infrastructure dynamic allocation for shale gas production

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APPLIED ENERGY 2020年第0期261卷 114439-000页

作者： Hong, Bingyuan Li, Xiaoping Song, Shangfei Chen, Shilin Zhao, Changlong Gong, Jing China Univ Petr Natl Engn Lab Pipeline Safety MOE Key Lab Petr Engn Beijing Key Lab Urban Oil & Gas Distribut Technol Fuxue Rd 18 Beijing 102249 Peoples R China China United Coalbed Methane Corp Ltd CNOOC China Ltd Unconvent Oil & Gas Branch 21B Jiuxianqiao Rd Beijing 100015 Peoples R China

Compared with the conventional method utilizing permanent processing facilities, modular infrastructure has shown greater potential to hedge against the uncertainty due to the rapidly declining characteristic of shale gas production. However, there is still a lack of a comprehensive approach that integrates the production planning and the dynamic allocation of the modular infrastructure based on the production curve of shale gas wells. Therefore, a systematic optimization framework is developed to simultaneously optimize the production planning and modular infrastructure allocation over a given time horizon, maximizing the net present value (NPV) of the system, considering the production curve and gas well status, the processing capacity as well as the scheduling of modular infrastructure. The proposed mixed-integer linear programming model combines the decisions relevant to shale gas production, transportation, and processing together with the decisions regarding modular infrastructure, including allocation, capacity selection, installment planning, moving scheduling, and salvage operation. A case study deciding a development strategy for 24 multi-well pads over a period of 15 years is implemented to illustrate the applicability of the proposed model. The results show that the dynamic allocation of the modular infrastructure can adapt to productivity fluctuations. The use of the modular approach increases the NPV by 9.12% and has a high utilization efficiency of processing devices compared to the conventional method. This work reveals that the synergistic interaction of the production planning and modular infrastructure dynamic allocation can increase efficiencies in the uses of energy, resources, and human capital to promote cleaner production practices.

关键词： Shale gas Modular infrastructure Optimization Capacity planning mixed-integer linear programming Production planning

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A new DEA common-weight multi-criteria decision-making approach for technology selection

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2020年第12期58卷 3686-3700页

作者： Chu, Junfei Wu, Jie Chu, Chengbin Liu, Ming Cent South Univ Sch Business Changsha Hunan Peoples R China Univ Sci & Technol China Sch Management Hefei Peoples R China Fuzhou Univ Sch Econ & Management Fuzhou Fujian Peoples R China Univ Paris Est ESIEE Paris Noisy Le Grand France Tongji Univ Sch Econ & Management Shanghai Peoples R China

This paper addresses an advanced manufacturing technology selection problem by proposing a new common-weight multi-criteria decision-making (MCDM) approach in the evaluation framework of data envelopment analysis (DEA). We improve existing technology selection models by giving a new mathematical formulation to simplify the calculation process and to ensure its use in more general situations with multiple inputs and multiple outputs. Further, an algorithm is provided to solve the proposed model based on mixed-integer linear programming and dichotomy. Compared with previous approaches for technology selection, our approach brings new contributions. First, it guarantees that only one decision-making unit (DMU) (referring to a technology) can be evaluated as efficient and selected as the best performer while maximising the minimum efficiency among all the DMUs. Second, the number of mixed-integer linear programs to solve is independent of the number of candidates. In addition, it guarantees the uniqueness of the final optimal set of common weights. Two benchmark instances are used to compare the proposed approach with existing ones. A computational experiment with randomly generated instances is further proceeded to show that the proposed approach is more suitable for situations with large datasets.

关键词： Technology selection data envelopment analysis common weight multi-criteria decision-making mixed-integer linear programming

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AC/DC Hybrid Distribution System Expansion Planning Under Long-Term Uncertainty Considering Flexible Investment

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IEEE ACCESS 2020年 8卷 94956-94967页

作者： Wu, Zhi Sun, Qirun Gu, Wei Chen, Yiwei Xu, Hua Zhang, Jing Southeast Univ Sch Elect Engn Nanjing 210096 Peoples R China Taizhou Elect Power Supply Co State Grid Zhejiang Elect Power Co Ltd Taizhou 318000 Peoples R China

This paper presents a novel flexible multistage AC/DC distribution system expansion planning model, where the flexible investment strategy is taken into account to address the long-term development uncertainty of load demand and DG. Uncertainty is modeled through a multistage scenario tree to capture the possible system states across the planning horizon. As uncertain information revealed gradually over the planning horizon, the planning decisions at each stage are made sequentially within limited disposable reservation funds (RFs). The overall problem is formulated as a mixed-integer linear programming model that guarantees the convergence to optimality by using commercially available software. We compare the total costs of the optimal planning solutions within different proportions of RFs and analyze the flexibility value of RFs for long-term planning problems. In addition, the impact of RFs on the adjustment ability of the plans and the investment risks under uncertainty are evaluated. Case studies are carried out on an AC/DC hybrid system to validate the effectiveness of the proposed model to constitute flexible options when facing long-term uncertainty. The obtained results show the importance of reserving a suitable proportion of RFs in the planning stage, which has a significant influence on the adaptability of the planning solution to uncertain factors.

关键词： AC DC distribution system expansion planning mixed-integer linear programming flexible investment long-term uncertainty

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Assessing the costs of contributing to climate change targets in sub-Saharan Africa: The case of the Ghanaian electricity system

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ENERGY FOR SUSTAINABLE DEVELOPMENT 2020年 57卷 32-47页

作者： Diawuo, Felix Amankwah Scott, Ian J. Baptista, Patricia C. Silva, Carlos A. Univ Tecn Lisboa Ctr Innovat Technol & Policy Res IN Inst Super Tecn Av Rovisco Pais 1 P-1049001 Lisbon Portugal Univ Energy & Nat Resources UENR Sch Engn POBx 214 Sunyani Ghana MIT Lab Informat & Decis Syst 77 Massachusetts Ave Cambridge MA 02139 USA

Ghana is one of the few countries within the sub-Saharan region which has been successful in reducing energy poverty. However, ensuring energy security, affordability, and environmental sustainability remains a significant challenge for the future development of the sub-region. Here, we examine how the electricity supply can evolve into the future tomeet potential emission obligations for the period of 2020-2040. A generation expansion planning model which is able to incorporate the reality of fuel shortages and fuel switching typical of a developing country's power system is used. In doing so, we generate a range of emission reduction costs that provide important benchmarks for the relatively under-studied sub-Saharan region and identify drivers of these costs specific to developing countries. Results indicate that the total discounted cost in expanding generation to meet the demand for all scenarios range from 13-17 billion US$, while the expected emission ranges from 99-189 mtCO(2). Subsequently, the cost ofmeeting different emission targets up to 2040 was quantified for each scenario ranging from 11-39 US$/tonne, which could be used as a benchmark for comparison in developed countries. We find that discount rates, representing Ghana's access to capital, are a particularly important variable for developing countries. We find that lower discount rates can lead to more investment in capital intensive renewable energy in the long run but can also lock in an additional conventional generation investment in the short term. Sensitivity analysis of demand growth reduction shows that with a 1% growth rate, the requirement of generation capacity could be reduced by 84%, providing initial evidence for the benefits of investing in demand-side measures. The study provides data and policy recommendations needed to inform decision-makers in developing countries as well as a comparison point for identifying decarbonization costs internationally. (c) 2020 International Energy In

关键词： Generation expansion plan Unit commitment Renewable energy integration mixed-integer linear programming CO2 emissions

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Shared backup resource assignment for middleboxes

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OPTICAL SWITCHING AND NETWORKING 2020年 37卷 100569-100569页

作者： Fujita, Risa He, Fujun Sato, Takehiro Oki, Eiji Kyoto Univ Grad Sch Informat Sakyo Ku Yoshida Honmachi Kyoto 6068501 Japan

This paper presents five approaches to solve the problem of finding the optimal backup resource assignment which maximizes the survival probability of network functions of middleboxes. In the previous work, no mathematical model to solve this problem is provided, so we formulate the problem as a mixed-integer linear programming (MILP) problem as the first approach. Formulating this MILP problem includes some special steps, which are not considered in the previous work. The MILP problem is not always solved in a practical time when the problem size becomes large. Then, we develop two heuristic approaches by replacing the objective of the original MILP problem relying on the idea of balancing the failure probabilities of functions of connected components. We develop two heuristic approaches by extending the way of assigning functions and servers from the conventional heuristic algorithm. Numerical results show that our four developed heuristic approaches improve the survival probability from the conventional heuristic algorithm in some cases and reduce computation time compared to obtaining the optimal solution. Furthermore, one of our developed heuristic approaches provides exactly the optimal solution with shorter computation time compared to the time solving the original MILP problem in a special case.

关键词： Middlebox Backup Survivability Optimization mixed-integer linear programming

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Program File Placement Strategies for Machine-to-Machine Service Network Platform in Dynamic Scenario

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IEICE TRANSACTIONS ON COMMUNICATIONS 2020年第11期E103B卷 1353-1366页

作者： Sato, Takehiro Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

The machine-to-machine (M2M) service network platform that accommodates and controls various types of Internet of Things devices has been presented. This paper investigates program file placement strategies for the M2M service network platform that achieve low blocking ratios of new task requests and accommodate as many tasks as possible in the dynamic scenario. We present four strategies for determining program file placement, which differ in the computation method and whether the relocation of program files being used by existing tasks is allowed or not. Simulation results show that a strategy based on solving a mixed-integer linear programming model achieves the lowest blocking ratio, but a heuristic algorithm-based strategy can be an attractive option by allowing recomputation of the placement when the placement cannot be obtained at the timing of new task request arrival.

关键词： machine to machine placement problem mixed-integer linear programming heuristic algorithm online algorithm

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Hybrid Ship Unit Commitment with Demand Prediction and Model Predictive Control

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ENERGIES 2020年第18期13卷 4748页

作者： Huotari, Janne Ritari, Antti Vepsalainen, Jari Tammi, Kari Aalto Univ Dept Mech Engn Otakaari 4 Espoo 02150 Finland

We present a novel methodology for the control of power unit commitment in complex ship energy systems. The usage of this method is demonstrated with a case study, where measured data was used from a cruise ship operating in the Caribbean and the Mediterranean. The ship's energy system is conceptualized to feature a fuel cell and a battery along standard diesel generating sets for the purpose of reducing local emissions near coasts. The developed method is formulated as a model predictive control (MPC) problem, where a novel 2-stage predictive model is used to predict power demand, and a mixed-integer linear programming (MILP) model is used to solve unit commitment according to the prediction. The performance of the methodology is compared to fully optimal control, which was simulated by optimizing unit commitment for entire measured power demand profiles of trips. As a result, it can be stated that the developed methodology achieves close to optimal unit commitment control for the conceptualized energy system. Furthermore, the predictive model is formulated so that it returns probability estimates of future power demand rather than point estimates. This opens up the possibility for using stochastic or robust optimization methods for unit commitment optimization in future studies.

关键词： maritime optimization model predictive control predictive model Gaussian Process mixed-integer linear programming

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