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A collaborative planning methodology of energy stations and energy networks in integrated energy system

IET RENEWABLE POWER GENERATION 2022年第14期16卷 3023-3040页

作者： Zhang, Hanlin Zhou, Suyang Gu, Wei Liu, Zhong Zhan, Xin Liu, Hengmen Southeast Univ Sch Elect Engn 2 Sipailou Nanjing Peoples R China State Grid China Jiangsu Elect Power Co Yangzhou Power Supply Bran Yangzhou Jiangsu Peoples R China

Investments in the energy networks will significantly influence the outcome of Integrated Energy System (IES) planning. It is difficult to optimally plan the energy stations and energy networks of IES while taking into consideration the energy network investments. Thus, a collaborative planning methodology is proposed for energy stations and energy networks containing multiple energy carriers, which can optimize both the capacity of the energy devices and networks and the topology of the energy networks. The linearization for the energy storage devices and electric air conditioning models, as well as the second-order relaxation for the power grid and gas network models are implemented, and the optimization model is subsequently transformed into a mixed-integer second-order cone programming (MISOCP) form which can be directly solved by the commercial solvers. Numerical analysis is carried out to prove the effectiveness of the proposed model and method and the results show that energy networks with optimal topology can significantly improve the energy utilization efficiency of the system and reduce the total cost. In addition, the investment cost of the energy networks plays a decisive role in the network topology as well as the way how the energy is supplied to energy stations.

关键词： investment energy utilization efficiency optimization model multiple energy carriers energy storage devices MISOCP gas network models numerical analysis integer programming power generation economics energy storage power grid second-order relaxation total cost reduction power generation planning investment cost power grids energy stations air conditioning optimal topology network topology electric air conditioning model integrated energy system planning mixed-integer second-order cone programming collaborative planning methodology energy network investment

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Reliability-Oriented Reconfiguration of Power Distribution Systems Considering Load and RES Production Scenarios

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IEEE TRANSACTIONS ON POWER DELIVERY 2022年第6期37卷 4668-4678页

作者： Karafotis, Panagiotis Evangelopoulos, Vasileios Georgilakis, Pavlos Natl Tech Univ Athens Sch Elect & Comp Engn Athens 15780 Greece

The ever-increasing integration of non-dispatchable distributed generation, i.e., renewable energy sources (RES), arises new challenges in the field of power system's reliability. Distribution network reconfiguration (DNR) is a cost-effective approach for the distribution system operator (DSO) that wishes to enhance system's reliability without infrastructure upgrades. This paper introduces a novel path-basedmixed-integer second-order cone programming model to optimally solve the reliability-oriented DNR problem. The DSO's objectives that are optimized are: a) improvement of distribution system's reliability indices and b) minimization of power losses. The proposed model is enriched with a scenario-based stochastic programming formulation that considers multiple levels of load and RES production. The standard 33-nodes distribution system and a real-world 83-nodes distribution system are employed to prove the efficiency and applicability of the model. Firstly, the multi-objective nature of the reliability-oriented DNR problem is investigated by conducting a sensitivity analysis, which reveals a trade-off region between reliability indices and power losses. Moreover, the obtained results show different global optimal solutions when the variability of load and RES production is considered. This highlights the importance of considering a scenario-based approach for load and RES production when solving the reliability-oriented DNR problem.

关键词： Distribution network reconfiguration mixed-integer second-order cone programming scenario-based stochastic programming reliability improvement

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Designing a service system with price- and distance-sensitive demand: A case study in mining industry

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2022年第3期303卷 1355-1371页

作者： Hoseinpour, Pooya Marand, Ata Jalili Amirkabir Univ Technol Tehran Polytech Dept Ind Engn & Management Syst Tehran Iran Aarhus Univ Dept Econ & Business Econ CORAL Aarhus Denmark

This study incorporates pricing decision into a congested facility location problem with immobile servers. The operations of facilities are modelled as queueing systems with price- and distance-sensitive streams of customer arrivals. Given a set of potential locations, a central service provider decides on the location of facilities, the allocation of customers to open facilities and also the service rate and price at each facility. The service provider's profit maximization problem is investigated in two settings, i.e., continuous and discrete service rates, each representing a class of real-world problems. In either case, the resulting mixed-integer non-linear program is reformulated as a mixed-integer second-order cone program which enables us to solve it in a reasonable time using commercial software packages. To demonstrate the applicability of the proposed models, a real-world case in the mining industry is presented and solved. (C) 2022 Elsevier B.V. All rights reserved.

关键词： OR in service industries Pricing Queueing Service system design mixed-integer second-order cone programming

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Service restoration framework for distribution networks incorporating switching crew routing

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IET GENERATION TRANSMISSION & DISTRIBUTION 2022年第10期16卷 2074-2085页

作者： Hajizadeh, Hamid Davarpanah, Mahdi Abedini, Moein Univ Tehran Sch Elect & Comp Engn Coll Engn Tehran 14395515 Iran

Here, an optimization framework is proposed for the service restoration (SR) problem in distribution networks based on mixed-integer second-order cone programming (MISOCP). The objective function is to minimize (i) curtailed loads, (ii) the number of switching operations, (iii) crew dispatching cost, and (iv) operational cost. A novel approach is developed for the optimal switching crew routing (SCR) to perform the manual switching operations in a short time. Self-healing actions including (i) network reconfiguration, (ii) load shedding, (iii) adjusting the output power of the dispatchable distributed generations (DGs), and (iv) the optimal tap setting of the voltage regulation devices are adopted in the SR strategy. Both the voltage dependency and the uncertainty nature of loads are modelled. Besides, the switch failure scenario is considered in the proposed model to deal with real operating conditions. Hence, the developed optimization framework offers the most robust SR solution. The simulation studies are performed on an actual 87-bus system in MATLAB/Yalmip environment by adopting Gurobi solver. The obtained results verify that the proposed model enhances quality of the solution in terms of SR process time compared to the other existing models.

关键词： MISOCP mixed-integer second-order cone programming load shedding power system restoration power generation dispatch voltage control crew dispatching cost integer programming distributed power generation dispatchable distributed generations Gurobi solver distribution networks voltage regulation devices power distribution economics switching crew routing optimization framework service restoration framework

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Iterative LP-Based Methods for the Multiperiod Optimal Electricity and Gas Flow Problem

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IEEE TRANSACTIONS ON POWER SYSTEMS 2022年第1期37卷 153-166页

作者： Mhanna, Sleiman Saedi, Isam Mancarella, Pierluigi Univ Melbourne Dept Elect & Elect Engn Melbourne Vic 3010 Australia

In light of the increasing coupling between electricity and gas networks, this paper introduces two novel iterative methods for efficiently solving the multiperiod optimal electricity and gas flow (MOEGF) problem. The first is an iterative MILP-based method and the second is an iterative LP-based method with an elaborate procedure for ensuring an integral solution. The convergence of the two approaches is founded on two key features. The first is a penalty term with a single, automatically tuned, parameter for controlling the step size of the gas network iterates. The second is a sequence of supporting hyperplanes and halfspaces for controlling the convergence of the electricity network iterates. Moreover, the two proposed algorithms use as a warm start the solution from a novel polyhedral relaxation of the MOEGF problem, for a noticeable improvement in computation time as compared to a cold start. Unlike the first method, which invokes a branch-and-bound algorithm to find an integral solution, the second method implements an elaborate steering procedure that guides the continuous variables to take integral values at the solution. Numerical evaluation demonstrates that the two proposed methods can converge to high-quality feasible solutions in computation times at least two orders of magnitude faster than both a state-of-the-art nonlinear branch-and-bound (NLBB) MINLP solver and a mixed-integer convex programming (MICP) relaxation of the MOEGF problem. The experimental setup consists of five test cases, three of which involve the real electricity and gas transmission networks of the state of Victoria with actual linepack and demand profiles.

关键词： Manganese Pipelines programming Computational modeling Mathematical model Iterative methods Regulators Sequential linear programming polyhedral envelopes integrated electricity and gas systems piecewise linear approximations mixed-integer nonlinear programming mixed-integer second-order cone programming branch-and-bound

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A Framework for Service Restoration of Cyber-Physical Power Systems

A Framework for Service Restoration of Cyber-Physical Power ...

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IEEE Belgrade PowerTech Conference

作者： Hassan, Chaudhry Talha Jadoon, Tariq Mahmood Lahore Univ Management Sci Dept Elect Engn Lahore Pakistan

ISBN: (纸本)9781665487788

Power systems with high penetration of distributed energy resources (DERs) are essentially cyber-physical systems. Cyber-physical energy systems provide several grid support functions including black-start in islanded mode. Hence, enhancing the resilience of the power system. After a major blackout, a self-sufficient power system can restore healthy nodes by forming microgrids (MGs) around black start distributed generators (DGs). These MGs evolve over time until all the critical loads are restored. The constellation of faults and radial nature of the network determine the load pick-up order and boundaries of MGs. The mathematical optimization model can only solve for the steady-state power equations. However, the associated dynamic transient response can cause instability across all connected nodes in a weak power grid. To address these challenges a multi-layer service restoration framework is proposed for a reconfigurable cyber-physical distribution system. The rolling horizon optimization problem is formulated as a mixed-integer second-order cone program (MISOCP) which explicitly incorporates dynamic stability constraints. The associated network traffic generated from the optimization layer is simulated in a network simulator to determine the communication latencies, whereas the power system simulations are performed in GridLAB-D. The approach is validated over a modified IEEE-123 node test feeder through simulation and the results are presented to demonstrate the efficacy of the framework for real-world applications including multiple fault scenarios with communication latencies.

关键词： cyber-physical system mixed-integer second-order cone programming inverter-based distributed generator (IBDG) energy storage system (ESS)

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A temporal and spatial electric vehicle charging optimization scheme with DSO-EVA coordination framework

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2024年 156卷

作者： Xiao, Tingting Peng, Yonggang Chen, Chunyu Zhejiang Univ Polytech Inst Hangzhou 310015 Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China China Univ Min & Technol Sch Elect Engn Xuzhou 221116 Peoples R China

Burdens of increasing penetration of electric vehicles (EVs) on distribution systems have attracted wide attention to the research of EV charging coordination. Nevertheless, existing coordination lacks the joint consideration of the temporal-spatial flexibility of EVs, which could reduce load fluctuations when meeting the EV charging demands. Moreover, a thorough investigation is required for the coordination of the benefits to the distribution system operator (DSO), EV aggregator (EVA), and EVs. In this paper, a novel EV charging scheme considering the temporal-spatial features of EVs is proposed, achieving the coordination of DSO, EVA, and EVs in two steps. First, a mixed-integer second-order cone programming (MISOCP)-based EV charging schedule is developed for DSO. second, the temporal-spatial features of EVs are exploited by EVA to track the charging schedule. Specifically, a dynamic charging price mechanism based on active power margin is proposed for public charging facilities and a specific load regulation is designed for private charging facilities. On this basis, the modified adaptive multiobjective particle swarm optimization (AMOPSO) algorithm is proposed, including adaptive flight parameter adjustment and termination mechanisms. Case studies demonstrate the proposed strategy can attenuate load variance and raise EVA revenue. Further, the impact analysis of penalty price and the price elasticity of electricity demand can provide references for stable distribution network operation, higher EVA revenue, and charging cost reduction.

关键词： Demand response Particle swarm optimization Temporal-spatial feature mixed-integer second-order cone programming Electric vehicle aggregator

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A mathematical formulation and a tabu search heuristic for the joint vessel-UAV routing problem

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COMPUTERS & OPERATIONS RESEARCH 2024年 169卷

作者： Li, Yantong Wang, Shengjie Zhou, Shanshan Wang, Zheng Dalian Maritime Univ Sch Maritime Econ & Management Dalian 116026 Peoples R China

Motivated by offshore inspection practices, we investigate a joint vessel-unmanned aerial vehicle (UAV) routing problem where vessels and UAVs work coordinately to perform inspection tasks. The problem is an extension of the mothership-drone routing problem by further considering multiple vessels and realistic constraints such as temporal-spatial coordination, service time, and inspection cycle. The goal is to minimize overall operational costs, including fixed vessel cost, and vessel and UAV routing costs. Decision-making involves task assignment, vessel route determination, and UAV take-off and landing locations. We formulate the problem as a mixed-integer second-order cone program. Addressing its NP-hard nature, we develop an enhanced tabu search algorithm (TS-RC), which incorporates two innovative mechanisms to reduce the computational burden. The first is to determine UAV take-off/landing points based on a new constructive procedure. The second is assessing neighborhood solutions using an approximate procedure. Results on a real-world case demonstrate a 10.29% reduction in operational costs compared to a classic vessel routing model. Moreover, numerical experiments on random instances with up to four vessels and 39 tasks demonstrate the performance of the proposed TS-RC method.

关键词： Vessel-UAV routing mixed-integer second-order cone programming Tabu search algorithm UAV applications for offshore inspection

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Low-Carbon Distribution Network Expansion Planning Considering the Integration of Soft Open Point

Low-Carbon Distribution Network Expansion Planning Consideri...

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58th IEEE/IAS Industrial and Commercial Power Systems Technical Conference Asia (IEEE I and CPS Asia)

作者： Wang, Haoyu Zhang, Shenxi Cheng, Haozhong Shanghai Jiao Tong Univ Key Lab Control Power Transmiss & Convers Minist Educ Shanghai Peoples R China

ISBN: (数字)9781665450669

ISBN: (纸本)9781665450669

Soft open point (SOP) can transfer active power between feeders and compensate reactive power, which help alleviate the operation challenges of large-scale renewable distribution generation (RDG) incorporation, and hence improve the integration capacity of RDG in low-carbon distribution network (LCDN). This paper presents a novel mixed-integer second-order cone programming model to address the expansion planning for the LCDN taking into account the integration of SOP. It co-optimizes the planning of RDG, SOP, capacitor bank, and energy storage system simultaneously with network reinforcement for minimizing the total economic and carbonemission costs over planning horizons. The potential on the economic-environmental benefits of the proposed planning methodology is studied via several test schemes on a 54-node network. The results demonstrate the effectiveness in improving the economy and mitigating carbon emission, when compared with the conventional planning paradigms.

关键词： low-carbon distribution network expansion planning soft open point mixed-integer second-order cone programming

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A two-stage resilience planning for integrated electricity-gas energy system considering hydrogen refueling stations during typhoons

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Smart Power & Energy Security 2025年第1期1卷 25-35页

作者： Fu Gao Hui Hou Zhao Yang Dong Junyi Tang Yulin Yan Ji Zhang Changjun Xie School of Automation Wuhan University of Technology Wuhan 430070 China Department of Electrical Engineering City University of Hong Kong Kowloon Hong Kong China Electric and Economy Research Institute of Hubei Province SGCC Wuhan 430077 China

To reduce the loss of the integrated electricity-gas energy system (IEGS) during typhoons, this paper proposes a two-stage resilience planning method for the IEGS considering hydrogen refueling stations (HRSs). Monte Carlo and simultaneous backward scenario reduction methods are used to generate typical power distribution network (PDN) line fault scenarios, which are then input into the two-stage resilience planning model. The first stage solves the resilience enhancement investment decision problem. It decides the locations and capacities of HRSs and gas-fired distributed generations (DGs). The second stage solves the system operation problem to minimize the cost in all fault scenarios. It determines the power of fuel cells and gas-fired DGs, the load shedding, as well as the line connection status. The resilience planning scheme with the minimum sum of the investment and system operation cost can be obtained by coordinating two stages. Finally, the simulation is verified via the IEEE 33-node PDN coupled with the 7-node gas network using historical data from the 2023 super typhoon “Saola”. The results indicate that the proposed method can not only reduce the investment and system operation cost; but also reduce load shedding and improve the ability to restore power supply in fault scenarios, therefore enhancing IEGS's resilience.

关键词： Typhoons Hydrogen refueling stations Integrated electricity-gas energy system Resilience planning mixed-integer second-order cone programming

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