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Impact of harmonised common balancing capacity procurement in selected Central European electricity balancing markets

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APPLIED ENERGY 2018年 222卷 351-368页

作者： Dallinger, Bettina Auer, Hans Lettner, Georg Tech Univ Wien EEG Inst Energy Syst & Elect Drives Gusshausstr 25-29-E370-3 A-1040 Vienna Austria

Contrary to the U.S., where the Independent System Operator is responsible for electricity balancing, in Europe this is the task of Transmission System Operators. Also in terms of market implementation there are fundamental differences between the U.S. (co-optimisation of day-ahead and balancing/ancillary markets) and Europe (separate bidding and clearing in different market segments). This paper focuses on European electricity markets, where recently the framework for upcoming challenges in electricity balancing has been defined ("Network Code on Electricity Balancing"). In detail, different possible (cross-border) balancing market designs in Europe are evaluated using the model EDisOn + Balancing. We focus on the procurement of up- and downward balancing capacity products (conducted jointly or separately), and how common procurement of frequency restoration reserves influences wholesale electricity market clearings. Different timings and lead-times for the procurement of automatically activated frequency restoration reserve are investigated, starting from weekly off-peak and peak products, leading to daily four-hour products. The quantitative results confirm that in addition to asymmetric procurement of up- and downward balancing capacity, common procurement has significant advantages in terms of cost reductions. The shortening of balancing product timings supports the integration of renewable electricity generation essentially. To achieve these positive effects, the first focus should be on harmonising national balancing markets Europewide. A best practise case is the pilot project between Germany and Austria: the two countries have already started common activation of automatic frequency restoration reserve and there are plans for future common procurements.

关键词： Balancing market designs Harmonised balancing products multi-objective linear programming RES-E integration

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multi-objective optimization for sustainable development of the power sector: An economic, environmental, and social analysis of Iran

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ENERGY 2018年 161卷 493-507页

作者： Atabaki, Mohammad Saeid Aryanpur, Vahid Kharazmi Univ Dept Ind Engn Fac Engn Tehran Iran Sharif Univ Technol Tehran Iran

This paper aims to analyze Iran's long-term power sector development from economic, environmental, social, and sustainable perspectives. For this purpose, a linear programming model is developed, which includes three objective functions: minimization of costs, minimization of CO2 emissions, and maximization of created jobs. To provide a sustainable plan, analytical hierarchy process is employed to allocate expert-based weights to the objective functions. Moreover, to support the decision-makers, Pareto-optimal alternatives are explored by varying the weights of objectives. The multi-objective model is solved by applying a weighted method based on fuzzy membership functions. The results show that a sustainable scenario leads to high technology diversification. Furthermore, the combined cycle would be the dominant option in Iran's long-term generation mix. In addition, power generation from non-hydro renewables, solar PV in particular, should grow faster than the total electricity demand. The findings indicate that the economic scenario fulfills Iran's commitment to 4% reduction of emissions compared to the current trend', however, the sustainable and environmental scenarios would cause achievement of the superior 12% reduction goal. multi-objective analysis shows that moving away from one's objective optimum value leads to significant improvements in other objective values. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： multi-objective linear programming Sustainable development Power system planning CO2 emissions Job creation Renewable energy sources

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Interactive allocation of mobile photo enforcement resources with multiple program objectives

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SUSTAINABLE CITIES AND SOCIETY 2019年 48卷 101572-000页

作者： Li, Yang Kim, Amy El-Basyouny, Karim Univ Alberta Dept Civil & Environm Engn 6-362 Donadeo Ice Edmonton AB T6G 1H9 Canada

Managers of mobile photo enforcement (MPE) programs must account for several road safety goals when deploying operators. However, there is no MPE design structure to systematically connect deployment decisions back to preset goals. We propose a method to aid MPE managers in using goals directly in the efficient allocation of limited program resources. A neighborhood-level resource allocation model is developed, which uses multi-objective optimization to determine how enforcement is allocated to city neighborhoods. The model is applied to an MPE program in Edmonton, Alberta, Canada, and delivered 200 optimal solutions for one month. One illustrative solution is plotted in GIS and assessed alongside the actual program deployment results for the same month. This solution efficiently allocates one month of operator shifts to sites in 44 neighborhoods, based on the specific needs of each neighborhood. The actual MPE deployment was such that 60% of visits occurred in neighborhoods beyond the 44 identified in the illustrative optimal solution. The major contribution of our model is that it allows for MPE managers to quantitatively map performance outcomes to multiple program goals. This can lead to more transparent and efficient MPE programs, which in turn can improve urban road safety and ultimately, urban sustainability.

关键词： Mobile photo enforcement Resource allocation multi-objective linear programming Geographic information system

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Optimal strategies for the yard truck scheduling in container terminal with the consideration of container clusters

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 137卷 106083-000页

作者： Hu, Xiaoyuan Guo, Jianquan Zhang, Yue Shanghai Maritime Univ Inst Logist Sci & Engn Shanghai Peoples R China Univ Shanghai Sci & Technol Shanghai Peoples R China

In container loading and unloading operations, container clusters are more suitable for large-scale operation and coupling scheduling of loading and unloading equipment. Taking a container cluster as a work unit, this study analyzes the multi-vessel large container clusters operation and researches the optimal scheduling strategy of the yard truck. A multi-objective mathematical programming model is developed through the pre-distribution of inbound container clusters and outbound container clusters, where the objectives are to minimize the non-loaded traveling distance and obtain the shortest completion time to finish the loading and unloading of containers in multiple vessels. The modeled problem is analyzed and solved by a heuristic-adaptive genetic algorithm. Fuzzy membership function and Pareto optimal solution are used to transform the multi-objective mathematical model into a single objective. The two methods are compared with results from the multi-objective programming problem of the model proposed. The result from the experimental case proved that the result of the Pareto optimal solution is better than that of the fuzzy membership function with regard to the problems of minimizing the distance of non-loaded traveling and finding the shortest completion time to finish the loading and unloading of containers in multiple vessels.

关键词： Yard truck scheduling Container clusters multi-objective linear programming Heuristic-adaptive genetic algorithm

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A mathematical model for solving fully fuzzy linear programming problem with trapezoidal fuzzy numbers

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APPLIED INTELLIGENCE 2017年第3期46卷 509-519页

作者： Das, Sapan Kumar Mandal, T. Edalatpanah, S. A. Natl Inst Technol Jamshedpur Dept Math Jamshedpur 831014 Jharkhand India Islamic Azad Univ Lahijan Branch Dept Appl Math Lahijan Iran Islamic Azad Univ Lahijan Branch Young Researchers Club Lahijan Iran

In this paper, an efficient method is introduced to solve fully fuzzy linear programming problems. The proposed method is derived from the multi-objective linear programming problem and lexicographic ordering method. Theoretical analysis for the proposed method has been provided. Moreover, some numerical experiments are given to show the preference of the proposed methods and are compared with some available methods.

关键词： Fully fuzzy linear programming Trapezoidal fuzzy numbers multi-objective linear programming

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multi-objective design optimization of distributed-energy systems through cost and exergy assessments

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APPLIED ENERGY 2017年 204卷 1299-1316页

作者： Di Somma, M. Yan, B. Bianco, N. Graditi, G. Luh, P. B. Mongibello, L. Naso, V. ENEA Italian Natl Agcy New Technol Energy & Sustainabl I-80055 Cr Portici Portici Italy Univ Connecticut Dept Elect & Comp Engn Storrs CT 06269 USA Univ Federico II DII I-80125 Naples Italy

In recent years, distributed energy systems (DESs) have been recognized as a promising option for sustainable development of future energy systems, and their application has increased rapidly with supportive policies and financial incentives. With growing concerns on global warming and depletion of fossil fuels, design optimization of DESs through economic assessments for short-run benefits only is not sufficient, while application of exergy principles can improve the efficiency in energy resource use for long run sustainability of energy supply. The innovation of this paper is to investigate exergy in DES design to attain rational use of energy resources including renewables by considering energy qualities of supply and demand. By using low-temperature sources for low-quality thermal demand, the waste of high quality energy can be reduced, and the overall exergy efficiency can be increased. The goal of the design optimization problem is to determine types, numbers and sizes of energy devices in DESs to reduce the total annual cost and increase the overall exergy efficiency. Based on a pre-established DES superstructure with multiple energy devices such as combined heat and power and PV, a multi-objective linear problem is formulated. In modeling of energy devices, the novelty is that the entire available size ranges and the variation of their efficiencies, capital and operation and maintenance costs with sizes are considered. The operation of energy devices is modeled based on previous work on DES operation optimization. By minimizing a weighted sum of the total annual cost and primary exergy input, the problem is solved by branch-and-cut. Numerical results show that the Pareto frontier provides good balancing solutions for planners based on economic and sustainability priorities. The total annual cost and primary exergy input of DESs with optimized configurations are reduced by 21-36% as compared with conventional energy supply systems, where grid power is used fo

关键词： Distributed energy system Design optimization multi-objective linear programming Annual cost Exergy efficiency

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Integrating column generation in a method to compute a discrete representation of the non-dominated set of multi-objective linear programmes

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4OR-A QUARTERLY JOURNAL OF OPERATIONS RESEARCH 2017年第4期15卷 331-357页

作者： Lin, Kuan-Min Ehrgott, Matthias Raith, Andrea Univ Lancaster Dept Management Sci Lancaster LA1 4YX England Univ Auckland Dept Engn Sci 70 Symonds St Auckland 1010 New Zealand

In this paper we propose the integration of column generation in the revised normal boundary intersection (RNBI) approach to compute a representative set of non-dominated points for multi-objective linear programmes (MOLPs). The RNBI approach solves single objective linear programmes, the RNBI subproblems, to project a set of evenly distributed reference points to the non-dominated set of an MOLP. We solve each RNBI subproblem using column generation, which moves the current point in objective space of the MOLP towards the non-dominated set. Since RNBI subproblems may be infeasible, we attempt to detect this infeasibility early. First, a reference point bounding method is proposed to eliminate reference points that lead to infeasible RNBI subproblems. Furthermore, different initialisation approaches for column generation are implemented, including Farkas pricing. We investigate the quality of the representation obtained. To demonstrate the efficacy of the proposed approach, we apply it to an MOLP arising in radiotherapy treatment design. In contrast to conventional optimisation approaches, treatment design using column generation provides deliverable treatment plans, avoiding a segmentation step which deteriorates treatment quality. As a result total monitor units is considerably reduced. We also note that reference point bounding dramatically reduces the number of RNBI subproblems that need to be solved.

关键词： multi-objective linear programming Column generation Revised normal boundary intersection method Radiotherapy treatment design

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Optimal irrigation planning using multi-objective fuzzy linear programming models

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ISH Journal of Hydraulic Engineering 2012年第3期18卷 232-240页

作者： Mirajkar, A.B. Patel, P.L. Department of Civil Engineering Sardar Vallabhbhai National Institute of Technology Surat Gujarat India

Crisp linear programming approach has been used to get the individual solutions of three conflicting objectives: maximisation of net benefit, maximisation of employment generation and minimisation of cost of cultivation. These crisp solutions were, then, solved together to obtain the solution under fuzzy multi-objective environment with maximum–minimum operators. Also, an effort has been made to improve the solution from maximum-minimum operator approach using two-phase as well as compromised fuzzy approaches. The applicability of the aforesaid algorithms were demonstrated through a case study of Kakrapar Right Bank Main Canal (KRBMC) under Ukai command area in India. © 2012 Taylor & Francis Group, LLC.

关键词： Compromise solution Maximum–minimum operators multi-objective linear programming Satisfaction degree Two-phase approach

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An exact algorithm for biobjective mixed integer linear programming problems

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COMPUTERS & OPERATIONS RESEARCH 2016年 72卷 204-213页

作者： Soylu, Banu Yildiz, Gazi Bilal Erciyes Univ Dept Ind Engn TR-38039 Kayseri Turkey

In this study, we develop a new criterion space search algorithm to find the Pareto frontier of biobjective mixed-integer linear programming problems. Our algorithm starts with the solution of an individual objective function and then sequentially finds all Pareto line segments and points, which are the elements of the Pareto frontier, of biobjective mixed-integer linear programming problems. At each iteration of the algorithm, one line segment (or one isolated point) of the Pareto frontier is detected. If there is no new Pareto line segment available, the algorithm ends. We provide numerical examples and present performance results of the algorithm over several test problems. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： multi-objective linear programming Biobjective mixed-integer linear programming epsilon-constraint methodology Tabu constraint Hamming distance

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Optimizing the environmental performance of integrated waste management scenarios by means of linear programming: a case study

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JOURNAL OF CLEANER PRODUCTION 2016年第Part4期112卷 3086-3096页

作者： Tascione, Valentino Mosca, Raffaele Raggi, Andrea Univ G DAnnunzio DEc Dept Econ Studies Pescara Italy

When municipal waste scenarios are compared by using Life Cycle Assessment, the comparison is usually carried out among a limited number of alternative scenarios identified in advance. Therefore, however accurate and broad the scenario definition may be, the scenario actually generating the lowest environmental impacts might just not be included among the alternatives proposed and analysed. To overcome this limitation, this paper proposes linear programming models developed to identify, among all the potential scenarios, the waste management scenario that minimises one particular environmental impact or a set of impacts at the same time, using environmental data from Life Cycle Assessment. Besides describing the proposed models, a concise overview of solution methods for multi-objective linear programming is provided. These models were tested in a case study and the results obtained are here presented and analysed. As a case-study, a suitable waste management system in the Abruzzo Region, Italy, was identified. In addition, a further hypothetical waste management context, also including an incinerator plant, was considered. Moreover, a sensitivity analysis was carried out to identify how changing distances to plants may affect optimal scenarios. As a result, different best-performing scenarios for the analysed waste management system were obtained, one for each single impact category considered, and one for each solution method adopted. Furthermore, the analysis of the hypothetical context shows how the introduction of an additional treatment plant could affect the system. Both distances and the solution methods used affect the results. The models developed could be used in decision-making processes to identify the best-performing scenario of a waste management system from the environmental point of view. The models are easy to apply and flexible, since they can be modelled according to the context to be analysed by introducing new factors. (C) 2015 Elsevier Ltd. Al

关键词： Life cycle assessment linear programming multi-objective linear programming Scenario optimization Waste management

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