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An efficient algorithm for bi-objective combined heat and power production planning under the emission trading scheme

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ENERGY CONVERSION AND MANAGEMENT 2014年 88卷 525-534页

作者： Rong, Aiying Figueira, Jose Rui Lahdelma, Risto Univ Lisbon ISEG Cemapre Ctr Appl Math & Econ P-1200781 Lisbon Portugal Univ Lisbon Inst Super Tecn CEG IST P-1049001 Lisbon Portugal Aalto Univ Dept Energy Technol Aalto 00076 Finland

The growing environmental awareness and the apparent conflicts between economic and environmental objectives turn energy planning problems naturally into multi-objective optimization problems. In the current study, mixed fuel combustion is considered as an option to achieve tradeoff between economic objective (associated with fuel cost) and emission objective (measured in CO2 emission cost according to fuels and emission allowance price) because a fuel with higher emissions is usually cheaper than one with lower emissions. Combined heat and power (CHP) production is an important high-efficiency technology to promote under the emission trading scheme. In CHP production, the production planning of both commodities must be done in coordination. A long-term planning problem decomposes into thousands of hourly subproblems. In this paper, a bi-objective multi-period linear programming CHP planning model is presented first. Then, an efficient specialized merging algorithm for constructing the exact Pareto frontier (PF) of the problem is presented. The algorithm is theoretically and empirically compared against a modified dichotomic search algorithm. The efficiency and effectiveness of the algorithm is justified. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Combined heat and power production multi-objective linear programming Energy optimization Energy efficiency Environmental/economic dispatch

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An optimization model for regional renewable energy development

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2012年第7期16卷 4606-4615页

作者： Arnette, Andrew Zobel, Christopher W. Univ Wyoming Coll Business Laramie WY 82071 USA

This research effort details the modeling component of a comprehensive decision support system for energy planning that allows for combining existing electricity generating capabilities with increased use of renewable energy sources. It focuses on energy planning at the regional level, and it is illustrated by applying it to the greater southern Appalachian mountains of the eastern United States: a region that was chosen for analysis not only due to its heavy dependence on coal for electricity, but also because of its potential for increased use of wind and solar power. The paper specifically discusses the development of a multi-objective linear programming (MOLP) model that can be used to determine the optimal mix of renewable energy sources and existing fossil fuel facilities on a regional basis. This model allows a decision maker to balance annual generation costs against the corresponding greenhouse gas emissions, and it provides significant support for implementing a variety of different policy analyses. (c) 2012 Elsevier Ltd. All rights reserved.

关键词： Renewable energy multi-objective linear programming Optimization

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Emergy-Based Adjustment of the Agricultural Structure in a Low-Carbon Economy in Manas County of China

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ENERGIES 2011年第9期4卷 1428-1442页

作者： Dong, Xiaobin Zhang, Yufang Cui, Weijia Xun, Bin Yu, Baohua Ulgiati, Sergio Zhang, Xinshi Beijing Normal Univ State Key Lab Earth Surface Proc & Resource Ecol Beijing 100875 Peoples R China Beijing Normal Univ Coll Resources Sci & Technol Beijing 100875 Peoples R China Agrometeorol Ctr Sichuan Prov Chengdu 610072 Peoples R China Beijing Normal Univ Acad Disaster Reduct & Emergency Management Minist Civil Affairs Beijing 100875 Peoples R China Beijing Normal Univ Minist Educ Beijing 100875 Peoples R China Parthenope Univ Naples Dept Environm Sci I-80133 Naples Italy

The emergy concept, integrated with a multi-objective linear programming method, was used to model the agricultural structure of Xinjiang Uygur Autonomous Region under the consideration of the need to develop a low-carbon economy. The emergy indices before and after the structural optimization were evaluated. In the reconstructed model, the proportions of agriculture, forestry and artificial grassland should be adjusted from 19:2:1 to 5.2:1:2.5;the Emergy Yield Ratio (1.48) was higher than the average local (0.49) and national levels (0.27);and the Emergy Investment Ratio (11.1) was higher than the current structure (4.93) and that obtained from the 2003 data (0.055) in Xinjiang Uygur Autonomous Region, the Water Emergy Cost (0.055) should be reduced compared to that before the adjustment (0.088). The measurement of all the parameters validated the positive impact of the modeled agricultural structure. The self-sufficiency ratio of the system increased from the original level of 0.106 to 0.432, which indicated a better coupling effect among the subsystems within the whole system. The comparative advantage index between the two systems before and after optimization was approximately 2:1. When the mountain ecosystem service value was considered, excessive animal husbandry led to a 1.41 x 10(10) RMB.a(-1) indirect economic loss, which was 4.15 times the GDP during the same time period. The functional improvement of the modeled structure supports the plan to "construct a central oasis and protect the surrounding mountains and deserts" to develop a sustainable agricultural system. Conserved natural grassland can make a large contribution to the carbon storage;and therefore, it is wise alternative that promote a low-carbon economic development strategy.

关键词： emergy Manas county multi-objective linear programming agricultural structural adjustment low-carbon economy

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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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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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Socio-economic benefit and profitability analyses of Austrian hydro storage power plants supporting increasing renewable electricity generation in Central Europe

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2019年第Jun.期107卷 482-496页

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

Increasing flexibility in electricity systems with high-shares of volatile renewable generation is on top of the European policy making agenda. Large-scale pumped hydro storages are appropriate technology candidates to accomplish this. Therefore, they are one of the focus technologies of the European Commission in the Projects of Common Interest discussion. In order to get listed a thorough system benefit analysis has to be conducted. This paper investigates a comprehensive socio-economic benefit analysis of storage technologies according to the indicators expected by the European Commission. The dispatch model EDisOn + Balancing is applied, which includes the functionalities depicting balancing mechanisms. Additionally, the profitability analysis tries to sort out the most convincing business cases where storage technologies contributing to more flexibility in the electricity system can sustain in the long-run. A simulation tool has been developed to model and quantify flexibility options, and to evaluate the profitability from the owner's point-of-view. The results show that in Central Europe with increasing storage capacities the necessity of reserve capacity and investments in peaking units decreases while maintaining a high security of supply level. In addition to electricity generation and balancing cost reductions, shedding of renewables and significant amounts of environmental damage costs of up to 1300 MEuro/a can be avoided. The profitability study shows that a reduction of minimum load or retrofitting hydro reservoir storages with pump mode increase the hours of participation in balancing markets and machine utilisation, e.g. operating hours and frequency of machine starts. With the latter also wear of machines increases. Therefore, it is important to find the optimum in terms of machine starts and market benefits. Several benefits are presented per installed capacity to provide scalability and transferability of outcomes for other applications. Furthermo

关键词： Pumped hydro storages Socio-economic benefits Operating strategies Profitability multi-objective linear programming Austria

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Planning in feasible region by two-stage target-setting DEA methods: An application in green supply chain management of public transportation service providers

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2014年第1期70卷 324-338页

作者： Azadi, Majid Shabani, Amir Khodakarami, Mohsen Saen, Reza Farzipoor Islamic Azad Univ Karaj Branch Dept Ind Management Fac Management & Accounting Karaj Iran Islamic Azad Univ Young Researchers & Elite Club Sci & Res Branch Tehran Iran Islamic Azad Univ Young Researchers & Elite Club Alborz Iran

To meet green supply chain management's requirements of a company and its transportation service providers (TSPs), it is essential to set clear, achievable, and realistic targets. This paper proposes two data envelopment analysis (DEA) approaches to find targets for two-stage network structures. The objective of proposed approaches is to plan in feasible region. The feasible region specifies bounds to ensure targets are within current operational capacity of TSPs. Applying the approaches to set targets for 24 TSPs lead to different results. However, proposed models ensure that the TSPs would be efficient in their current capacity. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Green supply chain management Supplier monitoring Target setting Network data envelopment analysis multi-objective linear programming Goal-directed benchmarking Feasible planning region

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Characterizing coherence, correcting incoherence

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INTERNATIONAL JOURNAL OF APPROXIMATE REASONING 2015年第PartB期56卷 208-223页

作者： Quaeghebeur, Erik Ctr Wiskunde & Informat NL-1090 GB Amsterdam Netherlands

Lower previsions defined on a finite set of gambles can be looked at as points in a finite-dimensional real vector space. Within that vector space, the sets of sure loss avoiding and coherent lower previsions form convex polyhedra. We present procedures for obtaining characterizations of these polyhedra in terms of a minimal, finite number of linear constraints. As compared to the previously known procedure, these procedures are more efficient and much more straightforward. Next, we take a look at a procedure for correcting incoherent lower previsions based on pointwise dominance. This procedure can be formulated as a multi-objective linear program, and the availability of the finite characterizations provide an avenue for making these programs computationally feasible. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Coherence Avoiding sure loss Polytope theory multi-objective linear programming Incoherence Dominance

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Economic profitability analysis of demand side management program

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ENERGY CONVERSION AND MANAGEMENT 2005年第18-19期46卷 2919-2935页

作者： Sheen, JN Cheng Shiu Univ Dept Elect Engn Kaohsiung Taiwan

This study considers both the internal and external costs of the utility in deriving the avoided capacity cost (ACC) and avoided operating cost (AOC) induced in an electric utility caused by the implementation of a demand side management program (DSM). In calculating the ACC, a multiple objective linear programming model is developed. Meanwhile, the AOC is calculated by considering the differences between the total and specific time period energy consumption ratios before and after the implementation of the DSM program. This study also develops an economic analysis method using Net Present Value and Pay Back Year models to assess the economic profitability of implementing a DSM program from a participant's point of view. The design and construction of a partial load leveling eutectic salt Cooling Energy Storage (CES) air conditioning system in a target office building in Kaohsiung, Taiwan, is discussed in order to simulate the cost benefit of the CES system from the perspective of the utility and from that of the participant. The results confirm the effectiveness of the developed models in simulating the economic benefits of implementing a DSM program from the perspectives of both the utility and the participant. (c) 2005 Elsevier Ltd. All rights reserved.

关键词： avoided cost multi-objective linear programming air pollution cost cooling energy storage air conditioner

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Integrating rooftop solar into a multi-source energy planning optimization model

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APPLIED ENERGY 2013年 111卷 456-467页

作者： Arnette, Andrew N. Univ Wyoming Coll Business Dept Management & Mkt Laramie WY 82071 USA

This research uses an optimization model to compare the role of rooftop solar generation versus large-scale solar and wind farm installations in renewable energy planning. The model consists of competing objectives, minimizing annual generation costs and minimizing annual greenhouse gas emissions. Rather than focus on the individual consumer's investment decision, over 20 scenarios were developed which explored key input parameters such as the maximum penetration level of rooftop solar installations, pricing of equipment, tax credits, and net-metering policy to determine what role rooftop solar plays in renewable energy investment at an aggregate level. The research finds that at lower levels of penetration, such as those currently found in the United States, other renewable energy sources remain viable options, thus rooftop solar should be just one option considered when increasing development of renewable energy sources. The research also shows that a balanced approach taking into account both of the opposing objectives will lead to greater levels of rooftop solar generation than focusing solely on cost or emissions. Therefore, rooftop solar should be considered as part of an overall balanced approach to increasing renewable energy generation. (C) 2013 Elsevier Ltd. All rights reserved.

关键词： Rooftop solar Renewable energy multi-objective linear programming Optimization Public policy

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