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Predictive management for energy supply networks using photovoltaics, heat pumps, and battery by two-stage stochastic programming and rule-based control

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ENERGY 2019年 179卷 1302-1319页

作者： Wakui, Tetsuya Sawada, Kento Yokoyama, Ryohei Aki, Hirohisa Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan Univ Tsukuba Fac Engn Informat & Syst 1-1-1 Tennodai Tsukuba Ibaraki 3058573 Japan

Predictive management for energy supply networks using photovoltaics generation (PV) units, heat pump water-heating units (HPUs), and battery units is developed by uniquely combining two-stage stochastic schedule programming and rule-based control to enhance their operating performances, including operating cost reduction under low selling prices of the surplus PV output after a feed-in tariff system and uncertain input conditions. The forecast scenarios of input conditions are generated from the probability distributions at each sampling time. The schedule planning problem is formulated using two stage stochastic mixed-integer linear programming and solved by inputting the forecast scenarios and the initial operation states of network components. In the operation control, the energy flow rates are modulated according to the actual input conditions under the obtained operation schedule. The forecast scenario generation and stochastic schedule planning are updated using a receding horizon approach. The developed management is applied to an annual operating simulation of a residential energy supply network for a housing complex, consisting of a shared PV unit, four sets of an HPU and thermal storage tank, and shared battery unit. The simulation results reveal that the decrease in the annual operating cost reduction by the developed management from the ideal management based on the previously-known PV output is just 1.57% point. Moreover, at the selling price of the surplus PV output higher than 6 yen/kWh, the developed management has an advantage in the annual operating cost over the charging- and exporting-priority managements. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Energy management Model predictive control Energy supply network Microgrid Two-stage stochastic programming mixed-integer linear programming

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Profitability of active retrofitting of multi-apartment buildings: Building-attached/integrated photovoltaics with special consideration of different heating systems

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ENERGY AND BUILDINGS 2019年 190卷 86-102页

作者： Fina, Bernadette Auer, Hans Friedl, Werner Tech Univ Wien Energy Econ Grp Gusshausstr 25-29E370-3 A-1040 Vienna Austria Austrian Inst Technol Giefinggasse 4 A-1210 Vienna Austria

Multi-apartment buildings comprise almost half of the European housing stock and are for the most part old and energy inefficient, making active retrofitting an important topic. The objective of this paper is to determine the profitability and optimal size of different technology portfolios for renewable building energy. A mixed-integer linear programming optimisation model is developed in Matlab with the objective of maximising the Net Present Value over a time horizon of 20 years. To examine multiple use cases, a modular approach is used for realising different multi-apartment building set-ups. Building-attached and building-integrated photovoltaic systems on different parts of the building skin already achieve breakeven. Heat pumps, pellet and district heating can hardly compete with gas heating yet. However, heat pumps have synergy effects with PV systems, thus reinforcing their implementation, as does a tenant portfolio with a good correlation with the sunshine hours. The profitability gap between investment costs for passive building renovation and resulting energy cost savings is significant. However, it is the smallest for buildings with quality standards. In conclusion, governmental subsidies and financial incentives such as the true cost pricing of CO2 emissions are necessary to trigger investments in reasonable combinations of passive and active retrofitting measures. (C) 2019 The Authors. Published by Elsevier B.V.

关键词： Retrofitting Multi-apartment building Net Present Value mixed-integer linear programming Electricity and heating technologies Building-attached/integrated photovoltaics

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Heuristic Approaches to Solve E-Scooter Assignment Problem

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IEEE ACCESS 2019年 7卷 175093-175105页

作者： Masoud, Mahmoud Elhenawy, Mohammed Almannaa, Mohammed H. Liu, Shi Qiang Glaser, Sebastien Rakotonirainy, Andry Queensland Univ Technol CARRS Q Brisbane Qld 4000 Australia King Saud Univ Civil Engn Dept Riyadh 11451 Saudi Arabia Fuzhou Univ Sch Econ & Management Fuzhou 350108 Peoples R China

Nowadays, rapid urbanization causes a wide-range of congestion and pollution in megacities worldwide, which bears an urgent need for micromobility solutions such as electric scooters (e-scooter). Many e-scooter firms use freelancers to charge the scooter where they compete to collect and charge the e-scooters at their homes. This competition leads the chargers to travel long distances to collect e-scooters. In this paper, we developed a mixed-integer linear programming (MILP) model for a real-world e-scooter-Chargers Allocation (ESCA) problem. The proposed model allocates the e-scooters to the chargers with an emphasis on minimizing the chargers' average travelled distance to collect the e-scooters. The MILP returns optimal solutions in most cases;however, the ESCA is identified as a generalized assignment problem which classifies as an NP-complete combinatorial optimization problem. Moreover, we modelled the charging problem as a game between two sets of disjoint players, namely e-scooters and chargers. Then we adapted the college admission algorithm (ACA) to solve the ESCA problem. For the sake of comparison, we applied the black hole optimizer (BHO) algorithm to solve this problem using small and medium cases. The experimental results show that the ACA solutions are close to the optimal solutions obtained by the MILP. Furthermore, the BHO solutions are not as good as the ACA solutions, but the ACA solution consumes more time to solve large-scale real cases. Based on the obtained results, we recommend applying the ACA1 to find the near-optimal solution for large-scale instances, as the MILP is inapplicable to find the exact solution in comparison.

关键词： Micromobility modes e-scooter-chargers allocation mixed-integer linear programming heuristic

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A mathematical model and algorithms for the aircraft hangar maintenance scheduling problem

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APPLIED MATHEMATICAL MODELLING 2019年 67卷 491-509页

作者： Qin, Yichen Wang, Z. X. Chan, Felix T. S. Chung, S. H. Qu, T. Jinan Univ Sch Elect & Informat Engn Zhuhai Campus Zhuhai 519070 Peoples R China Hong Kong Polytech Univ Dept Ind & Syst Engn Hong Kong Peoples R China Dongbei Univ Finance & Econ Sch Business Adm Dalian Peoples R China

An aircraft hangar maintenance scheduling problem is studied, motivated by the aircraft heavy maintenance conducted in a hangar operated by an independent maintenance service company. The aircraft hangar maintenance scheduling problem in such context consists of determining a maintenance schedule with minimum penalty costs in fulfilling maintenance requests, and a series of hangar parking plans aligned with the maintenance schedule through the planning period. A mixed-integer linear programming (MILP) mathematical model, integrating the interrelations between the maintenance schedule and aircraft parking layout plans, is presented at first. In the model, the variation of parking capacity of the maintenance hangar and the blocking of the aircraft rolling in and out path are considered. Secondly, the model is enhanced by narrowing down the domain of the time-related decision variables to the possible rolling in and out operations time of each maintenance request. Thirdly, to obtain good quality feasible solutions for large scale instances, a rolling horizon approach incorporating the enhanced mathematical model is presented. The results of computational experiments are reported, showing: (i) the effectiveness of the event-based discrete time MILP model and (ii) the scalability of the rolling horizon approach that is able to provide good feasible solutions for large size instances covering a long planning period. (C) 2018 Elsevier Inc. All rights reserved.

关键词： Aircraft maintenance scheduling Hangar parking layout planning mixed-integer linear programming Event-based model Rolling horizon approach

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Sharing Energy Storage Between Transmission and Distribution

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IEEE TRANSACTIONS ON POWER SYSTEMS 2019年第1期34卷 152-162页

作者： Elliott, Ryan T. Fernandez-Blanco, Ricardo Kozdras, Kelly Kaplan, Josh Lockyear, Brian Zyskowski, Jason Kirschen, Daniel S. Univ Washington Dept Elect Engn Seattle WA 98195 USA Univ Malaga Dept Appl Math Malaga 29076 Spain Doosan GridTech Seattle WA 98104 USA Snohomish Cty PUD Everett WA 98206 USA

This paper addresses the problem of how best to coordinate, or "stack," energy storage services in systems that lack centralized markets. Specifically, its focus is on how to coordinate transmission-level congestion relief with local, distribution-level objectives. We describe and demonstrate a unified communication and optimization framework for performing this coordination. The congestion relief problem formulation employs a weighted l(1)-norm objective. This approach determines a set of corrective actions, i.e., energy storage injections and conventional generation adjustments, that minimize the required deviations from a planned schedule. To exercise this coordination framework, we present two case studies. The first is based on a 3-bus test system, and the second on a realistic representation of the Pacific Northwest region of the United States. The results indicate that the scheduling methodology provides congestion relief, cost savings, and improved renewable energy integration. The large-scale case study informed the design of a live demonstration carried out in partnership with the University of Washington, Doosan GridTech, Snohomish County PUD, and the Bonneville Power Administration. The goal of the demonstration was to test the feasibility of the scheduling framework in a production environment with real-world energy storage assets. The demonstration results were consistent with computational simulations.

关键词： Distribution system operator energy storage system mixed-integer linear programming state of charge transmission congestion transmission system operator unit commitment

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Optimal Detection of Critical Nodes: Improvements to Model Structure and Performance

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NETWORKS & SPATIAL ECONOMICS 2019年第1期19卷 1-26页

作者： Karakose, Gokhan McGarvey, Ronald G. Univ Missouri Dept Ind & Mfg Syst Engn Columbia MO 65211 USA Univ Missouri Harry S Truman Sch Publ Affairs Columbia MO 65211 USA

The identification of critical network components is of interest to both interdictors wishing to degrade the network's performance, and to defenders aiming to preserve network performance in the face of disruption. In this study, novel formulations for the defender's problem, based on the dual to the multi-commodity flow problem, are developed to solve the critical node problem (CNP), in which the nodes can be disabled, for a variety of commonly-studied objectives, including minimum connectivity, cardinality-constraint CNP, and -disruptor problem. These objectives have applications in many types of networks, including transportation, communications, public health, and terrorism. Extensive computational experiments are presented, demonstrating that the proposed models dramatically reduce the computational time needed to solve such problems when compared to the best-performing models in the current literature. The proposed CNP models perform particularly well for networks that are originally disconnected (before interdiction) and for networks with a large number of two-degree nodes.

关键词： Network vulnerability Node disruption mixed-integer linear programming

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Integrated resource expansion planning of wind integrated power systems considering demand response programmes

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IET RENEWABLE POWER GENERATION 2019年第4期13卷 519-529页

作者： Hamidpour, Hamidreza Aghaei, Jamshid Dehghan, Shahab Pirouzi, Sasan Niknam, Taher Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran Islamic Azad Univ Qazvin Branch Fac Elect Biomed & Mechatron Engn Qazvin Iran Islamic Azad Univ Fac Engn Semirom Branch Semirom Esfahan Iran

Here, an optimisation framework is proposed for integrated resource expansion planning (IREP) including conventional generation units, wind generation units, and transmission lines while taking into account the role of demand response program (DRP) aggregators. This problem is a bi-level optimisation problem. In the upper-level problem, the objective function is to maximise the profit for each resource, that is, the generation company (GENCO), wind generation company (WINDCO), and transmission company (TRANSCO) as well as the DRP aggregator. Also, the lower-level problem considers a market model with the participation of private GENCOs, WINDCOs, TRANSCOs, and DRP aggregators. The lower-level problem minimises energy cost subject to AC power flow (PF) equations, power network limitations, pollution constraint, GENCO, WINDCO, TRANSCO constraints, and technical limitations of DRPs. Here, the lower-level problem is non-linear and non-convex. Accordingly, to facilitate the solution of the proposed bi-level optimisation problem, a linear model is proposed. Then, the proposed bilevel optimisation problem is converted into an integrated single-level one using the Karush-Kuhn-Tucker (KKT) conditions. Eventually, a mixed-integer linear programming (MILP) model is proposed. The proposed method is applied to the IEEE 6-bus and the IEEE 30-bus test systems, and finally, the capabilities of the proposed scheme are evaluated.

关键词： integer programming linear programming wind power plants power generation planning load flow power generation economics demand side management power markets power transmission lines power transmission planning power transmission economics concave programming WINDCO integrated resource expansion planning wind integrated power systems demand response programmes wind generation units demand response program aggregators GENCO wind generation company DRP aggregator AC power flow equations power system network limitations energy cost transmission company TRANSCO IREP Karush-Kuhn-Tucker conditions KKT conditions mixed-integer linear programming MILP model IEEE 6-bus test systems IEEE 30-bus test systems CPLEX solver GAMS optimisation package transmission lines

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Analysis of renewable generation's integration using multi-objective fashion for multistage distribution network expansion planning

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2019年 106卷 301-310页

作者： Ugranli, Faruk Bartin Univ Elect Elect Engn Dept TR-74110 Merkez Bartin Turkey

In this paper, the integration of intermittent distributed generation (wind and solar) is dealt with by proposing a multi-objective multistage distribution network expansion planning formulation based on epsilon-constraint method. This approach allows the planners to obtain pareto-optimal solutions based on the two objective functions: (1) installation costs of distributed generation, substations, feeders, maintenance costs of assets, costs of energy purchased from substations, cost of unserved energy and (2) utilization of renewable distributed generation. To represent the intermittent nature of load and renewable distributed generation, several time blocks are utilized, and its effectiveness is compared with an existing approach. The overall problem is formulated as a mixed-integer linear programming and a linear equation-based substation price is utilized within the optimization framework to reduce the size of the problem. The proposed method is applied to the modified 24-nodes test network for different cases to analyse the utilization of renewable distributed generation from different point of views and it is inferred from the results that the proposed model yields a variety of planning solutions which are better to increase the utilization of renewable distributed generation.

关键词： Distribution network expansion planning mixed-integer linear programming Multi-objective fashion Intermittent distributed generation Renewable energy Clustering

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Three stage dynamic heuristic for multiple plants capacitated lot sizing with sequence-dependent transient costs

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COMPUTERS & INDUSTRIAL ENGINEERING 2019年 127卷 1024-1036页

作者： Abdullah, Sari Shamayleh, Abdulrahim Ndiaye, Malick Amer Univ Sharjah Ind Engn Dept Sharjah U Arab Emirates

In this paper we investigate the demand planning problem for a petrochemical industry four tiers supply chain that integrates lot-sizing, scheduling with sequence dependent transient costs, transportation and warehousing decisions between suppliers, plants, warehouses, and customers. The problem was modeled using mixed-integer linear programming (MILP) and featuring a setup carryover and sub-tours elimination constraints. The problem is NP-Hard;therefore, an iterative three stage heuristic was developed which provides quality solutions with a very acceptable computational time. The heuristic computational efficiency was tested on different problem instances of different sizes, and the reported results were within a range of 0.09-2.00% gap from optimality.

关键词： Supply chain Petrochemical Demand planning Scheduling Sequencing mixed-integer linear programming

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Event-based MILP models for ridepooling applications

arXiv

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arXiv 2021年

作者： Gaul, Daniela Klamroth, Kathrin Stiglmayr, Michael School of Mathematics and Natural Sciences University of Wuppertal Wuppertal42119 Germany

Ridepooling services require efficient optimization algorithms to simultaneously plan routes and pool users in shared rides. We consider a static dial-a-ride problem (DARP) where a series of origin-destination requests have to be assigned to routes of a fleet of vehicles. Thereby, all requests have associated time windows for pick-up and delivery, and may be denied if they can not be serviced in reasonable time or at reasonable cost. Rather than using a spatial representation of the transportation network we suggest an event-based formulation of the problem, resulting in significantly improved computational times. While the corresponding MILP formulations require more variables than standard models, they have the advantage that capacity, pairing and precedence constraints are handled implicitly. The approach is tested and validated using a standard IP-solver on benchmark data from the literature. Moreover, the impact of, and the trade-off between, different optimization goals is evaluated on a case study in the city of Wuppertal (Germany). © 2021, CC BY.

关键词： mixed-integer linear programming

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