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

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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Hybrid Improved concave Matching Algorithm and ResNet Image Recognition Model

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IEEE ACCESS 2024年 12卷 39847-39861页

作者： Zheng, Wenda Ai, Yibo Zhang, Weidong Univ Sci & Technol Beijing Natl Ctr Mat Serv Safety Beijing 100083 Peoples R China

With the increase of organic matter content in global water bodies, timely and accurate identification of algae objects in water bodies is of great significance for rapid treatment of water eutrophication. To improve the performance of seaweed microscopic image recognition model, an improved concave matching algorithm was designed and applied to the segmentation of original microscopic images. In addition, an IResNet algorithm with self-adjusting pooling layer is designed. In this study, an improved concave matching algorithm and an improved ResNet algorithm were used to construct a microscopic algae image recognition model. The average Accuracy and Precision of the proposed algorithm in the data set are 88.6% and 90.3%, which is significantly higher than all tr4aditional and mainstream image segmentation algorithms. Among the five modified ResNet algorithms with self-adjusting pooling layers designed in this study, the fifth modified scheme has the best performance on the training set. The model's recognition accuracy and accuracy corresponding to the improved ResNet algorithm on the whole test set are 84.1% and 82.8%, respectively. The experimental data on the real data set show that the algae microscopic image recognition model has certain practical potential.

关键词： concave programming Neural networks Microscopy Algae Water resources Water monitoring Pollution measurement Organic materials Image recognition Seaweed Object recognition Data models Water pollution Eutrophication concave point matching algorithm neural network ResNet algae microscopic image

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Linear inequalities convex transformation for optimal reactive power flow model based on MISOCP relaxations

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IET GENERATION TRANSMISSION & DISTRIBUTION 2018年第7期12卷 1589-1594页

作者： Lin, Chunmei Wei, Hua Hou, Wenting Tan, Jiancheng Guangxi Univ Guangxi Key Lab Power Syst Optimizat & Energy Tec Nanning 530004 Peoples R China

A convex optimisation model for global optimum solution of optimal reactive power flow (ORPF) problem is proposed in this study, to solve the challenge of discrete variables of transformer taps involved in traditional ORPF models. Based on the second-order cone programming relaxation, a set of inequalities with 0-1 variables are introduced, to convexify the non-convex items that are products of discrete variables (or squares of discrete variables) and linear functions. After convexification, items containing second order of transformer ratio variables are dropped to the first order, and the non-convex non-linear nodal power equalities are equivalently transformed into linear equalities, thus formulating a mix-integer second-order cone programming (MISOCP) model of ORPF problem over feasible convex domain, which guarantees the global optimum theoretically. The results of IEEE-14, 30, 57, 118 bus systems show that, with stable numerical property and good optimum effect, the proposed model can give consideration to not only the quality of solution, but also the efficiency of calculation.

关键词： reactive power load flow convex programming concave programming power supply quality integer programming power transformers linear inequalities convex transformation optimal reactive power flow model MISOCP relaxations convex optimisation model global optimum solution discrete variables transformer taps second-order cone programming relaxation 0-1 variables nonconvex items linear functions convexification second order-of-transformer ratio variables nonconvex nonlinear nodal power equalities mix-integer second-order cone programming model convex domain numerical property

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Probabilistic transmission expansion planning considering distributed generation and demand response programs

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IET RENEWABLE POWER GENERATION 2017年第5期11卷 650-658页

作者： Hejeejo, Rashid Qiu, Jing Univ Newcastle Ctr Intelligent Elect Networks Callaghan NSW 2308 Australia CSIRO Energy Cluster 10 Murray Dwyer Circuit Mayfield West NSW 2304 Australia

Transmission expansion planning (TEP) is generally determined by peak demands. To improve the efficiency and sustainability of energy systems, attention has been paid to demand response programs (DRPs) and distributed generation (DG). DRPs and DG will also have significant impacts on the controllability and economics of power systems, from short-term scheduling to long-term planning. In this study, a non-linear economic design for responsive loads is introduced, based on the price flexibility of demand and the customers' benefit function. Moreover, a probabilistic multi-objective TEP model which considers DRPs is also proposed. A probabilistic analysis method, the so-called Monte-Carlo simulation method, is implemented to handle the uncertainty of the loads, DRPs and DG in the TEP problems. Due to the problems' non-convex formulations, a non-dominated sorting differential evolution program is used to solve the TEP problems. The proposed TEP model can find the optimal trade-off between transmission investment and demand response expenses. The planning methodology is then demonstrated on an IEEE 118-bus system in order to show the feasibility of the proposed algorithm.

关键词： demand side management power transmission planning distributed power generation power generation scheduling Monte Carlo methods probability power transmission economics concave programming controllability power transmission control evolutionary computation probabilistic transmission expansion planning distributed generation DG demand response programs DRP energy system efficiency improvement energy system sustainability improvement power system controllability power system economics short-term scheduling long-term planning nonlinear economic design probabilistic multiobjective TEP model probabilistic analysis method Monte-Carlo simulation method nonconvex formulations nondominated sorting differential evolution program transmission investment demand response expenses IEEE 118-bus system

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Instantaneous magnitudes and instantaneous frequencies of signals with their positivity constraints via non-smooth non-convex functional constrained optimisation

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IET SIGNAL PROCESSING 2016年第3期10卷 247-253页

作者： Yang, Zhijing Kuang, Wei-Chao Ling, Bingo Wing-Kuen Dai, Qingyun Guangdong Univ Technol Sch Informat Engn Guangzhou 510006 Guangdong Peoples R China Guangdong Univ Technol Fac Informat Engn Guangzhou 510006 Guangdong Peoples R China

This study proposes an iterative method to approximate an N-dimensional optimisation problem with a weighted Lp norm and L2 norm objective function by a sequence of N independent one-dimensional optimisation problems. This iterative method is inspired by the existing weighted L1 norm and L2 norm separable surrogate functional (SSF) iterative shrinkage algorithm. However, as these independent one-dimensional optimisation problems consist of weighted Lp norm and L2 norm objective functions, these optimisation problems are non-convex and they may have more than one locally optimal solutions. In general, it is very difficult to find their globally optimal solutions. To address this difficulty, this study proposes to partition the feasible set of each approximated problem into various regions such that the sign of the convexity of the objective function in each region remains unchanged. In this case, there is no more than one stationary point in each region. By finding the stationary point in each region, the globally optimal solution of each approximated optimisation problem can be found. Besides, this study also shows that the sequence of the globally optimal solutions of the approximated problems converge to the globally optimal solution of the original optimisation problem.

关键词： signal processing linear programming minimisation concave programming signal instantaneous frequency representation signal instantaneous magnitude representation positivity constraint nonsmooth nonconvex functional constrained optimisation nonconvex functional equality constraint linear functional inequality constraint pth-order derivatives maximum total absolute value minimization linear objective function constraint transcription method

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High-precision hyperboloid location method using passive time-difference-of-arrival measurements

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IET RADAR SONAR AND NAVIGATION 2013年第6期7卷 710-717页

作者： Lei, Wenying Chen, Baixiao Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Shaanxi Peoples R China

The authors consider the minimum square error formulation of the three-dimensional target location problem and provide an efficient solution for this minimisation problem. Two target location scenarios are investigated and it has been found that the convexity of the nonlinear least squares problem depends on the geometric relationship between the receivers and the target. The authors discover that the non-linear least squares problem is not always non-convex. The corresponding non-linear least squares problem is non-convex and sensitive to initial value only when the three time-difference-of-arrival location hyperboloids form two intersections. The convergence of the iterative method is proved when the objective function is convex in the location region. Simulation results demonstrate the effectiveness of the proposed method both in non-convex and convex scenarios, when a proper relative simple initial value is given.

关键词： concave programming iterative methods least squares approximations minimisation radar tracking target tracking time-of-arrival estimation high precision hyperboloid location method passive time difference-of-arrival measurements minimum square error formulation three dimensional target location problem target location scenario nonlinear least squares problem geometric relationship iterative method

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Downlink resource allocation in OFDMA wireless networks under power amplifier non-linearity

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IET COMMUNICATIONS 2017年第18期11卷 2751-2757页

作者： Baghani, Mina Mohammadi, Abbas Majidi, Mahdi Amirkabir Univ Technol Elect Engn Dept Microwave & Wireless Commun Res Lab Tehran Iran Univ Kashan Dept Elect & Comp Engn Kashan Iran

In this study, the physical layer resource allocation in orthogonal frequency-division multiple access (OFDMA) systems is studied by considering the non-linear effects of power amplifier (PA). The non-linearity produces cross-correlation among the subcarriers and results in deteriorating the OFDMA subcarriers orthogonality. Hence, the signal-to-interference ratio (SIR) of the output signal of PA for OFDMA signal with different power scaling factors for subcarriers is derived. Then, the theoretical SIR is verified by simulation result. Next, the optimisation problem is designed to maximise the total achievable downlink rate of all users by assigning subcarriers and power scaling factors. This non-convex problem is solved by comprehensive learning particle swarm optimisation. The simulation results show that when PA is non-linear, better total rate is achieved by considering non-linearity in resource allocation compared with the conventional resource allocation techniques.

关键词： concave programming frequency division multiple access OFDM modulation particle swarm optimisation power amplifiers radio networks resource allocation

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Signal leakage neutralisation in instantaneous non-regenerative relaying networks under channel uncertainty

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IET COMMUNICATIONS 2014年第8期8卷 1285-1295页

作者： Ho, Zuleita Jorswieck, Eduard Tech Univ Dresden Fac Elect & Comp Engn Commun Lab D-01062 Dresden Germany

In a multi-user wireless network, physical layer security is an important issue, especially when some of the served users are malicious. As these users actively participate in the network, their channel state information can be estimated or feedback, although not perfectly known. With this channel uncertainty, the worst-case signal leakage to eavesdropping users' needs to be managed. The authors propose a robust instantaneous relay design that improves the worst-case secrecy rate performance, and decompose the problem into two sub-problems: First, the achievable signal leakage or leakage-to-noise ratio region is studied. Second, for fixed signal leakage constraints, the achievable secrecy rate region is computed. To approach the non-convex optimisation problems, the authors propose to iteratively solve for the phases and magnitudes of the equivalent channel matrix, a function of the relay matrix. The numerical simulations illustrate that the proposed alternating optimisation algorithm achieves higher secrecy rates than those in a system without an instantaneous relay.

关键词： relay networks (telecommunication) radio networks telecommunication security concave programming matrix algebra signal processing numerical simulations relay matrix equivalent channel matrix nonconvex optimisation problems secrecy rate region fixed signal leakage constraints leakage-to-noise ratio region worst-case secrecy rate performance channel state information physical layer security multiuser wireless network channel uncertainty instantaneous nonregenerative relaying networks signal leakage neutralisation

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Joint source-and-relay beamforming for multiple-input multiple-output systems with single-antenna distributed relays

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IET COMMUNICATIONS 2012年第1期6卷 62-68页

作者： Li, C. Wang, X. Yang, L. Zhu, W. -P. Southeast Univ Minist Educ Key Lab Underwater Acoust Signal Proc Nanjing 210096 Peoples R China Southeast Univ Sch Informat Sci & Engn Nanjing 210096 Peoples R China Nanjing Univ Dept Math Nanjing 210093 Peoples R China Concordia Univ Dept Elect & Comp Engn Montreal PQ H3G 1M8 Canada

A joint source-and-relay beamforming scheme is proposed for multiple-input multiple-output ( MIMO) systems with distributed single-antenna relays. First, a lower-bound of the signal-to-noise ratio at the destination is derived as an objective function to formulate a constrained beamforming optimisation problem. The joint beamforming problem is then divided into two sub-optimisation problems corresponding to the source and the relay beamforming, respectively. The first sub-problem is shown to be a quadratic concave minimisation, and is tackled by developing an iterative algorithm with each iteration solving a linear problem. The second one corresponds to a Rayleigh-Ritz ratio problem which is then solved by the generalised singular-value decomposition in a closed form. Based on the solutions to the subproblems, a global iterative algorithm is designed to implement the joint source-and-relay beamforming. Simulation results show that the proposed method outperforms some existing relaying schemes in terms of the capacity and outage probability of the whole MIMO relay system.

关键词： multiple-input multiple-output systems suboptimisation problems Rayleigh-Ritz ratio problem minimisation signal-to-noise ratio joint source-and-relay beamforming scheme global iterative algorithm quadratic concave minimisation MIMO relay system linear problem Optimisation techniques probability single-antenna distributed relays generalised singular-value decomposition iterative methods concave programming constrained beamforming optimisation problem antenna arrays Antenna arrays array signal processing Interpolation and function approximation (numerical analysis) lower-bound Radio links and equipment outage probability MIMO communication Other topics in statistics

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Joint quantisation levels and power optimisation in uplink network multiple-input and multiple-output under constraint backhaul

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IET COMMUNICATIONS 2015年第16期9卷 2041-2047页

作者： Wang, Shipeng Chen, Li Chen, Xiaohui Wei, Guo Univ Sci & Technol China Chinese Acad Sci Sch Informat Sci & Technol Key Lab Wireless Opt Commun 96 Jinzhai Rd Hefei 230026 Anhui Peoples R China

This article studies the performance of the cooperative system where each base station (BS) is connected to a central processor (CP) via a noiseless and rate-limited backhaul link. The single-user compress-and-forward scheme is deployed at the BSs, and the problem for jointly setting the quantisation noise and the transmit power levels is left open. The authors formulate the weighted sum-rate (WSR) problem of optimising quantisation and transmit power levels for K-users and B-BSs situation. However, the problem is non-convex and difficult to be solved directly by conventional convex methods. In this work, an algorithm is proposed to solve the optimisation problem and achieve its global optimality. More importantly, the authors reveal the reason for the effect of the quantisation levels on the performance of cooperative system. Lower and upper bounds of quantisation levels are derived under the given signal to interference noise ratio (SINR) requirements. The lower and upper bounds are then demonstrated to be rather close to the numerical results. It is also numerically shown that the proposed algorithm can achieve the global optimality and is robust with respect to different multi-user situations.

关键词： quantisation (signal) MIMO communication cooperative communication convex programming concave programming power optimisation problem uplink network multiple input multiple output system constraint backhaul base station cooperative system single-user compress and forward scheme rate-limited backhaul link central processor quantisation noise level weighted sum-rate problem WSR problem nonconvex problem convex problem signal to interference noise ratio SINR

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