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3rd IEEE Student Conference on Electrical Machines and Systems (SCEMS)

作者： Yang, Jingying Yu, Huiping Zhang, Zhipeng Zhou, Lin Gao, Xuefeng Wang, Di State Grid Jilin Elect Power Co Ltd Econ & Technol Res Inst Changchun Peoples R China State Grid Jilin Elect Power Co Ltd Econ & Technol Res Inst Planning & Review Ctr Changchun Peoples R China Northeast Elect Power Univ Dept Elect Engn Jilin Jilin Peoples R China

ISBN: (纸本)9781728156224

Growing dissemination of distributed energy resources (DERs) has led to the rapid expansion of distribution networks. Distribution system operators (DSOs) tend to employ optimal scheduling to arrange controllable DERs to meet load demand or exist in the reserve markets to provide reserve capacity. When DERs participate in the reserve market, the market clearing strategy of the transmission and distribution network managed by transmission system operators (TSO) and DSO has changed. Therefore, this study constructs a bi-level optimization problem for the clearing strategy of a DSO in energy and reserve markets, and the operating problems of two independent system operators are classified as upper and lower level problems. The proposed nonlinear bi-level problem is transformed into a single-level mixed integer linear programming model using the Karush-Kuhn-Tucker condition and duality theory. Case studies demonstrate the model's effectiveness.

关键词： bi-level optimization model market clearing energy and reserve markets

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Multi-Objective bi-level Optimal Dispatch Method of Active Distribution Network Considering Dynamic Reconfigurations 5

Multi-Objective Bi-Level Optimal Dispatch Method of Active D...

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5th Asia Conference on Power and Electrical Engineering (ACPEE)

作者： Ni, Shiyuan Zhang, Linyao Wu, Guilian Shi, Pengjia Zheng, Jieyun State Grid Fujian Elect Power Co Econ Technol Res Inst Fuzhou Peoples R China

ISBN: (纸本)9781728152813

A bi-level optimal dispatching model for active distribution network considering dynamic reconfiguration is put forward. The coordination optimized is realized by defining same optimal function of upper and lower level which are lowest operation cost and best fast voltage stability. The decision variables of upper level are grid structure at every reconfiguration period. decimal encoding method based on fundamental loops is employed to improve the calculation efficiency. The decision variables of lower level are power of distribution generation, reactive power of capacitor banks and static var compensator, tap position of OLTC. IEEE 33 bus system is employed to verify the proposed method.

关键词： Active distribution network grid dynamic reconfigurations bi-level optimization model optimal dispatching

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A model for Cordon Pricing Scheme Considering Spatial Equity

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TRANSPORTATION IN DEVELOPING ECONOMIES 2021年第2期7卷 1-11页

作者： Afandizadeh, Shahriar Abdolmanafi, Seyed Ebrahim Iran Univ Sci & Technol IUST Sch Civil Engn Tehran Iran Islamic Azad Univ Sch Civil Engn Sci & Res Branch Tehran Iran

This paper investigates the issue of spatial equity in the cordon pricing scheme. The spatial inequity is for drivers whose travel destinations are located within the cordon or should travel through it and finally they may face with higher travel time. Thus, to alleviate this inequity, a bi-level multi-objective optimization model is developed. Next, an algorithm is implemented according to the second version of the Strength Pareto Evolutionary Algorithm (SPEA2). Then, the developed model is applied to Sioux Falls network and the results is discussed. The results reveal that it seems reasonable to consider spatial equity as an objective function in cordon pricing. In addition, we can create a sustainable situation for the transportation system by improving spatial inequity with a relatively low reduction in social welfare. Moreover, there are spatial inequity impacts in real networks, which should be considered in the cordon pricing scheme. Furthermore, the developed model can increase the public acceptance of drivers and transportation authorities.

关键词： Cordon pricing Spatial equity Multi-modal network bi-level optimization model SPEA2

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A bi-level Approach for Determining Optimal Dynamic Retail Electricity Pricing of Large Industrial Customers

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IEEE TRANSACTIONS ON SMART GRID 2019年第2期10卷 2267-2277页

作者： Shu, Jun Guan, Rui Wu, Lei Han, bing North China Elect Power Univ EE Dept Beijing 102206 Peoples R China China Yangtze Power Co Ltd Mkt Dept Beijing 100033 Peoples R China Clarkson Univ ECE Dept Potsdam NY 13699 USA China Three Gorges Corp Mkt Dept Beijing 100038 Peoples R China

In this paper, a bi-level optimization model is proposed for determining the optimal dynamic retail electricity price, which balances the monetary benefits between utility companies and large industrial customers. That is, the utility company at the upper level devotes to maximize the profit of electricity sale by tuning dynamic retail electricity prices, while large industrial customers at the lower level minimize their power consumption costs by optimally scheduling tasks and generation outputs of self-provided power plants. Specifically, the task scheduling problem of large industrial customers is formulated as a modified continuous-time mixed-integer linear programing (MILP) problem, for effectively handling the exact start time and cancellation of tasks as well as optimally deploying and executing tasks of large industrial customers. A hybrid optimization algorithm by integrating genetic algorithm (GA) and MILP is proposed for addressing computational complexity of the proposed bi-level optimization problem. That is, GA is used to solve the upper level problem, while the lower level scheduling problem is solved by a commercial MILP optimizer. Numerical case results show that the proposed method can effectively increase the profit of the utility company, while improving electricity consumption patterns and reducing average power consumption costs of large industrial customers.

关键词： bi-level optimization model large industrial customers mixed-integer linear programing retail electricity price

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Capacity optimization for Electrical and Thermal Energy Storage in Multi-energy Building Energy System 10

Capacity Optimization for Electrical and Thermal Energy Stor...

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10th International Conference on Applied Energy (ICAE)

作者： Zhu, Qianwen Li, Qiqiang Zhang, bingying Wang, Luhao Li, Guanguan Wang, Rui Shandong Univ Sch Control Sci & Engn 17923 Jingshi Rd Jinan 250061 Shandong Peoples R China Univ Jinan Sch Elect Engn 336 Nanxinzhuang Rd Jinan 250022 Shandong Peoples R China

In a multi-energy building energy system, the key to improve the energy efficiency and economy is coordinating the capacity configuration and operation scheduling of both electrical and thermal energy storage. Considering the electricity storage characteristics of electricity feedback arbitrage and degradation, as well as part load rate and ON/OFF time constraints for the combined operation of thermal energy storage and ground source heat pump, this paper presents a bi-level optimization method, including upper capacity optimization and lower operation optimization. The simulation results show that, compared to the system without energy storage, the proposed method significantly reduces total annualized cost, shifts large amounts of peak load and increases renewable energy self-consumption rate. (C) 2019 The Authors. Published by Elsevier Ltd.

关键词： building energy capacity optimization electrical and thermal energy storage bi-level optimization model

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Impact of Optimal Storage Allocation on Price Volatility in Energy-Only Electricity Markets

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IEEE TRANSACTIONS ON POWER SYSTEMS 2018年第2期33卷 1903-1914页

作者： Masoumzadeh, Amin Nekouei, Ehsan Alpcan, Tansu Chattopadhyay, Deb Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia KTH Royal Inst Technol Dept Automat Control S-11428 Stockholm Sweden World Bank Power Syst Planning Grp 1818 H St NW Washington DC 20433 USA

Recent studies show that the fast growing expansion of wind power generation may lead to extremely high levels of price volatility in wholesale electricity markets. Storage technologies, regardless of their specific forms, e.g., pump-storage hydro, large-scale, or distributed batteries, are capable of alleviating the extreme price volatility levels due to their energy usage time shifting, fast-ramping, and price arbitrage capabilities. In this paper, we propose a stochastic bilevel optimization model to find the optimal nodal storage capacities required to achieve a certain price volatility level in a highly volatile energy-only electricity market. The decision on storage capacities is made in the upper level problem and the operation of strategic/regulated generation, storage, and transmission players is modeled in the lower level problem using an extended stochastic (Bayesian) Cournot-based game. The South Australia (SA) electricity market, which has recently experienced high levels of price volatility, and a 30-bus IEEE system are considered as the case studies. Our numerical results indicate that 50% price volatility reduction in the SA electricity market can be achieved by installing either 430-MWh regulated storage or 530-MWh strategic storage. In other words, regulated storage firms are more efficient in reducing the price volatility than strategic storage firms.

关键词： bi-level optimization model electricity market Price volatility storage technologies strategic and regulated firms

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Capacity optimization for Electrical and Thermal Energy Storage in Multi-energy Building Energy System

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Energy Procedia 2019年 158卷 6425-6430页

作者： Qianwen Zhu Qiqiang Li bingying Zhang Luhao Wang Guanguan Li Rui Wang School of Control Science and Engineering Shandong University 17923 Jingshi Road Jinan 250061 China School of Electrical Engineering University of Jinan 336 Nanxinzhuang Road Jinan 250022 China

关键词： building energy capacity optimization electrical thermal energy storage bi-level optimization model

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The Optimal Configuration Method for Distribution Network Considering the Uncertainty of the photovoltaic

The Optimal Configuration Method for Distribution Network Co...

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International Conference on Power System Technology (POWERCON)

作者： Liu Wenxia Long Weidi Hao Yongkang Qi Huaizhong Wang Chunjian Liu Zongqi North China Elect Power Univ Beijing 102206 Peoples R China State Grid Gansu Elect Power Co Elect Power Res Inst Lanzhou Gansu Peoples R China State Grid Jilin Elect Power Co Baicheng Peoples R China

ISBN: (纸本)9781538664612

Aiming at the voltage and economy problems of PV access to the active distribution network, this paper establishes a coordinate optimal reactive power compensation method by using the shunt capacitor (C) and the static var generator(SVG). Firstly, considering the uncertainty of PV output, a photovoltaic time series output model is established by probabilistic method with multi scenario. Then, study the operation strategy of SVG and make some simplifications in the simulation combined with the practice. On the basis of that, established the bi-level optimal configuration model of dynamic and static reactive power equipment. The lower model considers the optimal operation mode of the equipment and the upper model optimizes the configuration of reactive devices. Finally, verified the effectiveness of the model by the modification IEEE-33 node example, and the simulation results show that the proposed method can significantly improve the voltage quality, reduce the network loss, increase economic efficiency.

关键词： Reactive power optimization Microgrid Static var generator bi-level optimization model Active distribution network

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Coordinated Optimal Voltage Control Strategy in Distribution Networks with Multi-Microgrids 10

Coordinated Optimal Voltage Control Strategy in Distribution...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Sun, Xianzhuo Zhang, Wen Shandong Univ Sch Elect Engn Jinan Shandong Peoples R China

ISBN: (纸本)9781538656860

Nowadays, microgrids have gained lots of popularity as an effective technology to manage distributed generation (DG). However, with the increasing penetration of DGs and microgrids, the voltage profile in distribution networks might be influenced. To solve the voltage problems in distribution networks while considering the economy of multi-microgrids, a bi-level optimization model is formulated. In the proposed bi-level model, the objective of the upper level is to minimize the power losses of distribution networks, and the objective of the lower level is to maximize the profit of microgrids. The voltage and power exchange at the point of common coupling (PCC) are selected as interrelating variables and a master-slave-splitting method is used to solve the problem. A case study is used to illustrate the coordinated control strategy and the results show that the voltage profile in distribution networks can be improved as well as the economy of microgrids can be ensured.

关键词： bi-level optimization model coordinated control strategy distribution networks multi-microgrids

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Integrated waste load allocation for river water pollution control under uncertainty: a case study of Tuojiang River, China

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ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2017年第21期24卷 17741-17759页

作者： Xu, Jiuping Hou, Shuhua Yao, Liming Li, Chaozhi Sichuan Univ State Key & Lab Hydraul & Mt River Engn Chengdu 610064 Sichuan Peoples R China Sichuan Univ Uncertainty Decis Making Lab Chengdu 610064 Peoples R China Neijiang Survey & Design Inst Water Conservancy & Neijiang 641000 Peoples R China

This paper presents a bi-level optimization waste load allocation programming model under a fuzzy random environment to assist integrated river pollution control. Taking account of the leader-follower decision-making in the water function zones framework, the proposed approach examines the decision making feedback relationships and conflict coordination between the river basin authority and the regional Environmental Protection Agency (EPA) based on the Stackelberg-Nash equilibrium strategy. In the pollution control system, the river basin authority, as the leader, allocates equitable emissions rights to different subareas, and the then subarea EPA, as the followers, reallocates the limited resources to various functional zones to minimize pollution costs. This research also considers the uncertainty in the water pollution management, and the uncertain input information is expressed as fuzzy random variables. The proposed methodological approach is then applied to Tuojiang River in China and the bi-level linear programming model solutions are achieved using the Karush-Kuhn-Tucker condition. Based on the waste load allocation scheme results and various scenario analyses and discussion, some operational policies are proposed to assist decision makers (DMs) cope with waste load allocation problem for integrated river pollution control for the overall benefits.

关键词： Waste load allocation bi-level optimization model Stackelberg-Nash game Uncertainty Integrated

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