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A MILP Model for Revenue Optimization of a Compressed Air Energy Storage Plant with Electrolysis

ENERGIES 2021年第20期14卷

作者： Klaas, Ann-Kathrin Beck, Hans-Peter Tech Univ Clausthal Inst Elect Power Engn & Energy Syst Leibnizstr 28 D-38678 Clausthal Zellerfeld Germany

Energy storage, both short- and long-term, will play a vital role in the energy system of the future. One storage technology that provides high power and capacity and that can be operated without carbon emissions is compressed air energy storage (CAES). However, it is widely assumed that CAES plants are not economically feasible. In this context, a mixed-integer linear programming (MILP) model of the Huntorf CAES plant was developed for revenue maximization when participating in the day-ahead market and the minute-reserve market in Germany. The plant model included various plant variations (increased power and storage capacity, recuperation) and a water electrolyzer to produce hydrogen to be used in the combustion chamber of the CAES plant. The MILP model was applied to four use cases that represent a market-orientated operation of the plant. The objective was the maximization of revenue with regard to price spreads and operating costs. To simulate forecast uncertainties of the market prices, a rolling horizon approach was implemented. The resulting revenues ranged between EUR 0.5 Mio and EUR 7 Mio per year and suggested that an economically sound operation of the storage plant is possible.

关键词： compressed air energy storage CAES Huntorf hydrogen electrolysis day-ahead-market mixed-integer linear programming MILP rolling horizon optimization

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Investigating Hydrogen-Based Non-Conventional Storage for PV Power in Eco-Energetic Optimization of a Multi-Energy System

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ENERGIES 2021年第23期14卷

作者： Di Somma, Marialaura Caliano, Martina Cigolotti, Viviana Graditi, Giorgio Italian Natl Agcy New Technol Energy & Sustainabl Dept Energy Technol & Renewable Sources I-00123 Rome Italy

Through the integration of multiple energy carriers with related technologies, multi-energy systems (MES) can exploit the synergies coming from their interplay for several benefits towards decarbonization. In such a context, inclusion of Power-to-X technologies in periods of excess renewable electricity supply, removes the need for curtailment of renewable electricity generation. In order to achieve the environmental benefits of MES without neglecting their economic feasibility, the optimal design problem is as crucial as challenging and requires the adoption of a multi-objective approach. This paper extends the results of a previous work, by investigating hydrogen-based non-conventional storage for PV power in the eco-energetic optimization of an MES. The system under study consists of a reversible fuel cell (r-SOC), photovoltaic (PV), electric heat pump, absorption chiller and thermal storage, and allows satisfying the multi-energy needs of a residential end-user. A multi-objective linear problem is established to find the optimal MES configuration including the sizes of the involved technologies with the goal of reducing the total annual cost and the fossil primary energy input. Simulation results are compared with those obtained in previous work with a conventional nanogrid where a combined heat and power (CHP) system with gas-fired internal combustion engine and a battery were present instead of an r-SOC. The optimized configuration of the non-conventional nanogrid allows achieving a maximum primary energy reduction amounting to 66.3%, compared to the conventional nanogrid. In the face of the environmental benefits, the non-conventional nanogrid leads to an increase in total annual costs, which, compared to the conventional nanogrid, is in the range of 41-65%.

关键词： multi-energy system multi-objective optimal design hydrogen carrier Power-to-X primary energy saving annual cost mixed-integer linear programming

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A multi-objective model to optimize country-scale municipal solid waste management with economic and environmental objectives: A case study in Malaysia

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JOURNAL OF CLEANER PRODUCTION 2021年 316卷

作者： Ooi, Jun Keat Woon, Kok Sin Hashim, Haslenda Xiamen Univ Malaysia Sch Energy & Chem Engn Jalan SunsuriaBandar Sunsuria Sepang 43900 Selangor Malaysia Univ Teknol Malaysia Fac Chem & Energy Engn Sch Chem & Energy Engn Proc Syst Engn Ctr PROSPECT UTM Johor Bahru Skudai 81310 Johor Malaysia

Municipal solid waste (MSW) is a universal issue affecting all countries. In Malaysia, almost 90% of the MSW is disposed of in open landfills with no energy recovery system. Due to the heterogeneous characteristics of MSW, it is essential to develop a combination of different waste processing facilities with simultaneous cost and greenhouse gas (GHG) minimization. A novel multi-objective mixed-integer linear programming with the augmented e-constraint method is developed to assess the optimum MSW allocation on seven conventional waste processing facilities, including open landfills, material recycling facility, sanitary landfills, anaerobic digestion, composting, incineration, and plasma gasification. The avoided emissions of the valuable products valorized from MSW, which have been often neglected in the optimization model, are included in the study to investigate the extent of emissions reduction in the MSW management system. Compared to the current scenario in Malaysia (total cost: 66.66 MYR/tonne MSW, net GHG emissions: 0.42 tonne CO2-eq/tonne MSW), the least-cost solution (i.e., 74% open landfill, 10% sanitary landfill, and 15% material recycling facility) shows 26% reduction for both cost and GHG emissions, while the least GHG emissions solution (i.e., 20% sanitary landfill, 21% anaerobic digestion, 21% composting, 21% plasma gasification, and 17% material recycling facility) indicates 159% reduction of GHG emissions with 15% increase in cost. Among the 11 Pareto-optimal solutions, the 10th solution (34% sanitary landfill, 21% anaerobic digestion, 21% composting, 17% material recycling facilities, and 8% plasma gasification) reduces 3% of national greenhouse gas emissions and is recommended for future MSW management in Malaysia. The sensitivity analysis indicates that plasma gasification is more favorable when the electricity price is higher. A change of waste separation rate from 30% to 90% reduces total MSW management cost and the net GHG emissions by 18.24

关键词： Augmented epsilon-constraint Cost minimization Greenhouse gas mixed-integer linear programming Municipal solid waste Pareto-optimal solutions

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Optimal Charging Schedule Planning for Electric Buses Using Aggregated Day-Ahead Auction Bids

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ENERGIES 2021年第16期14卷

作者： Zoltowska, Izabela Lin, Jeremy Warsaw Univ Technol Inst Control & Computat Engn PL-00665 Warsaw Poland New Grid Solut Austin TX 78731 USA

This study aims to plan a cost-minimizing charging schedule for electric buses with fast charging stations. The paper conceptualizes the problem as a three-stage procedure, which is oriented around the participation of an electric bus aggregator in a day-ahead energy auction. First, the aggregation stage determines the bid parameters of buses. With bid parameters, aggregated cost-minimizing charging plans are obtained in the second stage conceived as the hourly day-ahead auction. The disaggregation of hourly plans into feasible minutely charging schedules is the third stage. The main contribution is the formulation of mixed-integer linear programming aggregation models to determine charging availability expressed as minimum and maximum hourly energy requirements taking into account detailed, minutely characteristics and constraints of the charging equipment and the buses. No price forecasts are required, and the plans adjust to the wholesale prices of energy. Defining only a few aggregated bids parameters used in linear programming constraints and incorporating them into the auction model is another contributing factor of this paper, allowing the scheduling of storage-based participants economically. The proposed methodology has been verified on a recently published case study of a real-world bus service operated on the Ohio State University campus. We show that the auction-based charging of all 22 buses outperforms as-soon-as-possible schedules by 7% to even 28% of daily cost savings. Thanks to the aggregated bids, buses can flexibly shift charges between high- and low-price periods while preserving constraints of the charging equipment and timetables.

关键词： aggregator coordinated charging double auction mixed-integer linear programming

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Structural design of distributed energy networks by a hierarchical combination of variable- and constraint-based decomposition methods

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ENERGY 2021年 224卷

作者： Wakui, Tetsuya Hashiguchi, Moe Yokoyama, Ryohei Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

A near-optimal solution method of a large-scale design problem of a distributed energy network, consisting of multiple energy-supply systems under power and heat interchanges, is developed by hierarchically combining variable-and constraint-based decompositions. The design problem is formulated using mixed-integer linear programming, and its scale increases with the number of connected energy supply systems and daily patterns of energy demand. By focusing on the hierarchical relationship between design and operation variables, the original problem is decomposed into an upper-level design problem and lower-level coordinated operation problems based on the Benders decomposition. By focusing on power-and heat-interchange constraints, the coordinated operation problem is further decomposed into a master problem concerning power and heat interchanges and subproblems for energy supply in each energy-supply system based on the Dantzig-Wolfe decomposition. A near-optimal solution is calculated through a two-level iterative calculation, consisting of delayed constraint generation between the design problem and the coordinated operation problems and delayed column generation between the master problem and the subproblems in each coordinated operation problem. The near-optimal solution method is applied to the structural design problem of distributed energy networks incorporating 5e100 cogeneration systems, in which suboptimal solutions cannot be found in the conventional solution method. ? 2021 Elsevier Ltd. All rights reserved.

关键词： Distributed energy network Optimization Structural design Benders decomposition Dantzig-wolfe decomposition mixed-integer linear programming

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Integrated operational planning model, considering optimal delivery routing, incentives and electric vehicle aggregated demand management

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APPLIED ENERGY 2021年 304卷

作者： Diaz-Cachinero, Pablo Munoz-Hernandez, Jose Ignacio Contreras, Javier Univ Castilla La Mancha Escuela Tecn Super Ingn Ind Power & Energy Anal & Res Lab PEARL Ciudad Real 13001 Spain Univ Castilla La Mancha Escuela Tecn Super Ingn Ind Power & Energy Anal & Res Lab PEARL Albacete 02071 Spain

The use of electric vehicles is being promoted to address emerging concerns about global warming associated with emissions from fossil fuels. Besides, in the context of parcel delivery deep growth related to e-commerce, electric vehicle is becoming an alternative to conventional fossil fuel technology. Intrinsically, the charging process implies the interdependence between the transportation and electric power systems. This paper presents a new multistage optimization-based approach that allows linking delivery routing and aggregated demand management in the transportation and electric power systems, respectively. For the routing and charging of each independent electric vehicle, battery degradation, acceleration-and speed-dependent power consumption, penalty for delivery delay, tolls, fixed charging prices and incentives for availability time are considered. An electric vehicle demand aggregator is used to guarantee the synergy between systems. Incentives are included to motivate electric vehicles to remain at charging intersections. However, attractive incentives can create electric power system congestion due to simultaneous charges on nodes. Thus, an iterative decongestion methodology is developed. The resulting model is divided into three stages: delivery allocation, delivery routing for each independent electric vehicle and optimal energy management by electric vehicle demand aggregator. The resulting optimization problem is cast as a mixed-integer linear programming model for the first two stages and a linear programming model for the third stage. Numerical results demonstrate the effectiveness of the proposed model on a real 284-intersection map with a set of 100 electric vehicles, showing that incentives allow electric vehicle demand aggregator to achieve cost savings of 8.5%.

关键词： Routing problem Electric vehicle demand aggregator Incentives for availability time mixed-integer linear programming Power system decongestion methodology

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Optimizing the utilization of excess heat for district heating in a chipboard production plant

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CASE STUDIES IN THERMAL ENGINEERING 2021年 25卷

作者： Halmschlager, Verena Birkelbach, Felix Hofmann, Rene TU Wien Inst Energy Syst & Thermodynam Getreidemarkt 9-BA A-1060 Vienna Austria

The industry is responsible for about one third of the global energy consumption, and thus, reducing energy and emissions in this sector is crucial to reach global climate goals. Methods like operational optimization can improve industrial processes' efficiency, leading to a decrease of excess heat or total energy. By combining operational optimization with flexibility measures like thermal energy storage, intermittent heat can be optimally utilized. This work analyzes the optimal utilization of excess heat for district heating in a real-world industrial use case, a chipboard production plant. The process includes a combined heat and power unit and units for production. Electricity can be sold to the grid, and two district heating demands need to be met while satisfying the production schedule of the plant. To exploit the utilization of excess heat, four adaptations to the process are considered: Increased district heating feed-in capacities, the integration of two different thermal energy storages, and the activation of an additional heat exchanger for district heating. To optimize the process's operation with and without the adaptations, an optimization framework is developed. Its modular structure allows for straight-forward design adaptations. The outcomes show that the process's efficiency can be significantly improved by applying operational optimization and considering the process adaptations. In all scenarios, the currently contracted district heating feed-in capacity can be significantly increased, leading to profits up to 108,000 _ per month and reduction of energy losses up to 87 %. Although the heat exchanger's activation yields the highest profits of all scenarios, thermal energy storages can increase the process's flexibility. In the end, the decision, which modification is most viable depends on the operator's objectives.

关键词： Operational optimization Industrial energy hub Energy and production scheduling Thermal energy storage mixed-integer linear programming

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Optimal Design and Operation of River Basin Storage under Hydroclimatic Uncertainty

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JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT 2021年第9期147卷

作者： Burrow, Andy Hering, Amanda S. Morton, David P. Newman, Alexandra M. Colorado Sch Mines Dept Mech Engn 1500 Illinois St Golden CO 80401 USA Baylor Univ Dept Stat Sci 1301 South Univ Pk Dr Waco TX 76706 USA Northwestern Univ Dept Ind Engn & Management Sci 2145 Sheridan Rd Evanston IL 60208 USA

As populations and economies expand in regions with changing climates, demand for water can quickly grow beyond what natural supply can sustain. This paper proposes to mitigate shortages, such as those that occur along the Lower South Platte River in northeastern Colorado, via a three-step approach: (1) create flow data scenarios, which represent a wide array of hydroclimatic outcomes;(2) use an existing simulation model to process these scenarios in order to locate excess supply and unmet demand both spatially and temporally;and (3) minimize the cost of alleviating identified shortages using a new, multiperiod, two-stage stochastic programming model, which determines reservoir location, size, type, and operation over a 50-year time horizon. Results indicate that demand associated with historical and seasonally shifted scenarios can be satisfied, and unmet demand associated with more challenging reduced-mean runoff scenarios can be mitigated substantially. Furthermore, multiple smaller reservoirs are preferred over a single large reservoir to hedge against these uncertainties.

关键词： Integrated water resource planning mixed-integer linear programming River basin management

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Evaluating the role of commercial parking bays for urban stakeholders on last-mile deliveries - A consideration of various sustainability aspects

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JOURNAL OF CLEANER PRODUCTION 2021年 312卷

作者： Trott, Maik Baur, Niels-Fabian Landwehr, Marvin Auf der Rieck, Julia von Viebahn, Christoph Hannover Univ Appl Sci & Arts Fac Business & Informat 4 Hannover Germany Univ Hildesheim Inst Business Adm & Informat Syst Operat Res Grp Hildesheim Germany

In this contribution, we assess the traditional last mile delivery concept and a framework with commercial parking bays for carriers in terms of their sustainability value for urban stakeholders. We evaluate the potential advantages and disadvantages of commercial parking bays and provide routing solutions based on the given context and stakeholder objectives. To ensure the needs of the stakeholders and the possibility of a near future implementation in the dynamic real-world system, we chose a combined approach of simulation and mathematical optimization, which allows us to investigate the concept efficiently and with a high reliability. By means of an agent-based simulation model as well as a mixed-integer linear model, we establish a heuristic routing solution for minimizing both emissions and delivery durations. We consider different scenarios in which customers are visited in a delivery radius, around a specific commercial parking bay. Outside this radius, delivery operations are conducted through second-row parking activities. Our results for the area of investigation show that the investigated scenario featuring a 200-m delivery radius around the parking bays has a 29.8% emission savings potential compared to traditional parcel delivery procedures. Moreover, optimizing the delivery routes with our green vehicle routing approach has indicated an additional savings potential of 26.4% in terms of delivery duration and 16.4% in terms of emission output for traditional parcel deliveries. Concerning the individual evaluation of the logistics context, our results indicate that dedicated commercial parking bays could be attractive to most urban stakeholders when employed utilizing a hybrid approach, combining traditional delivery activities with commercial parking bay fulfillment.

关键词： Simulation mixed-integer linear programming Green vehicle routing problem Split deliveries Last-mile deliveries Sustainability aspects

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A New Approach to Renewable Energy Sources Allocation considering Robustness against Fluctuations

A New Approach to Renewable Energy Sources Allocation consid...

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International Conference on Smart Grids and Energy Systems (SGES)

作者： Kwangkaew, Akanit Javaid, Saher Kaneko, Mineo Charoenlarpnopparut, Chalie Japan Adv Inst Sci & Technol Sch Informat Sci Nomi Ishikawa Japan Sirindhorn Int Inst Technol Sch ICT Pathum Thani Thailand

ISBN: (纸本)9781728185507

Preserving natural resources and avoiding CO2 emission, renewable energy sources (RESs) are rapidly increasing as alternative energy sources, which is advancing conventional power systems to hybrid renewable energy systems (HRESs). Since RESs rely on fluctuating sources, e.g., wind and solar, the allocation of RESs is becoming a complex problem as the high penetration of RESs in HRESs. In our system design method, the condition for the robustness against power fluctuation of RESs and loads is considered as the mandatory requirement for sizing and allocation of power sources. In this paper, we propose a new system design method for allocation (sizing and locating) of a set of sources and loads for HRES design with the robustness conditions. Another distinguishing feature of our method is to make use of the concept of the minimum matching in Graph Theory. Finally, we verify our proposed method by demonstrations on a simplified model of a real power distribution network.

关键词： allocation design robustness mixed-integer linear programming MILP renewable enery sources

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