|2015||Wu M, Dong J, Zhao A, Tang WC, Sher W, Chen GW, et al., 'A Cooling Vest for Construction Workers', Advanced Materials Research, 1061-1062 728-732 (2015) [C1]|
|2014||Dong Z, Zhao J, Wen F, Xue Y, 'From smart grid to energy internet: Basic concept and research framework', Dianli Xitong Zidonghua/Automation of Electric Power Systems, 38 1-11 (2014) [C1]|
The traditional way of economic and social development, characterized by centralized utilization of fossil fuel energy, is gradually changing. On the other hand, the third industrial revolution is now rising. As the core technology of the third industrial revolution, the Energy Internet aims at facilitating large-scale utilization and sharing of renewable energy by integrating renewable energy and internet technologies. It will enhance the merging of electricity, transportation and natural gas networks, change the way of energy utilization, and finally achieve the goal of promoting sustainable economic and social development. Given this background, an overview of the Energy Internet is first provided, and a basic research framework developed. A definition of the Energy Internet is then suggested, followed by its basic architecture and main components. Several main research challenges to the Energy Internet, such as the wide-area coordination and control of distributed devices, the integration of the power system with the transportation system and natural gas network, as well as the cyber physical modeling and security, are next discussed in more details.
|2014||Zhao J, Xu Y, Luo F, Dong Z, Peng Y, 'Power system fault diagnosis based on history driven differential evolution and stochastic time domain simulation', Information Sciences, (2014) [C1]|
Fault diagnosis is an important task in power system analysis. In this paper, a hybrid method is proposed to perform online fault diagnosis of transmission lines. Stochastic time domain simulation (STDS) is firstly introduced to generate simulated fault and system data so as to improve the computational speed of fault diagnosis and handle the possible malfunction of protective relays and circuit breakers. The fault diagnosis problem is then formulated as an optimization problem, which can take into account the possible malfunction of protection devices and post-fault system trajectories. We propose a novel optimization algorithm, namely history driven differential evolution (HDDE) to solve the formulated optimization problem. The proposed methodology is finally tested using comprehensive case studies to demonstrate its effectiveness. Â© 2014.
|2014||Xu Y, Dong ZY, Zhang R, Wong KP, 'A decision tree-based on-line preventive control strategy for power system transient instability prevention', INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 45 176-186 (2014) [C1]|
|2014||Zheng Y, Dong ZY, Luo FJ, Meng K, Qiu J, Wong KP, 'Optimal Allocation of Energy Storage System for Risk Mitigation of DISCOs With High Renewable Penetrations', IEEE TRANSACTIONS ON POWER SYSTEMS, 29 212-220 (2014) [C1]|
|2014||Zheng Y, Dong ZY, Xu Y, Meng K, Zhao JH, Qiu J, 'Electric Vehicle Battery Charging/Swap Stations in Distribution Systems: Comparison Study and Optimal Planning', IEEE TRANSACTIONS ON POWER SYSTEMS, 29 221-229 (2014) [C1]|
|2014||Wan C, Xu Z, Pinson P, Dong ZY, Wong KP, 'Optimal Prediction Intervals of Wind Power Generation', IEEE TRANSACTIONS ON POWER SYSTEMS, 29 1166-1174 (2014) [C1]|
|2014||Xu Y, Dong ZY, Zhang R, Wong KP, Lai M, 'Solving Preventive-Corrective SCOPF by a Hybrid Computational Strategy', IEEE TRANSACTIONS ON POWER SYSTEMS, 29 1345-1355 (2014) [C1]|
|2014||Xu Y, Dong ZY, Zhang R, Wong KP, Lai M, 'Closure to Discussion on "Solving Preventive-Corrective SCOPF by a Hybrid Computational Strategy"', IEEE TRANSACTIONS ON POWER SYSTEMS, 29 3124-+ (2014) [C3]|
|2014||Wan C, Xu Z, Pinson P, Dong ZY, Wong KP, 'Probabilistic forecasting of wind power generation using extreme learning machine', IEEE Transactions on Power Systems, 29 1033-1044 (2014) [C1]|
Accurate and reliable forecast of wind power is essential to power system operation and control. However, due to the nonstationarity of wind power series, traditional point forecasting can hardly be accurate, leading to increased uncertainties and risks for system operation. This paper proposes an extreme learning machine (ELM)-based probabilistic forecasting method for wind power generation. To account for the uncertainties in the forecasting results, several bootstrap methods have been compared for modeling the regression uncertainty, based on which the pairs bootstrap method is identified with the best performance. Consequently, a new method for prediction intervals formulation based on the ELM and the pairs bootstrap is developed. Wind power forecasting has been conducted in different seasons using the proposed approach with the historical wind power time series as the inputs alone. The results demonstrate that the proposed method is effective for probabilistic forecasting of wind power generation with a high potential for practical applications in power systems. Â© 2013 IEEE.
|2014||Yao W, Zhao J, Wen F, Dong Z, Xue Y, Xu Y, Meng K, 'A multi-objective collaborative planning strategy for integrated power distribution and electric vehicle charging systems', IEEE Transactions on Power Systems, 29 1811-1821 (2014) [C1]|
An elaborately designed integrated power distribution and electric vehicle (EV) charging system will not only reduce the investment and operation cost of the system concerned, but also promote the popularization of environmentally friendly EVs. In this context, a multi-objective collaborative planning strategy is presented to deal with the optimal planning issue in integrated power distribution and EV charging systems. In the developed model, the overall annual cost of investment and energy losses is minimized simultaneously with the maximization of the annual traffic flow captured by fast charging stations (FCSs). Additionally, the user equilibrium based traffic assignment model (UETAM) is integrated to address the maximal traffic flow capturing problem. Subsequently, a decomposition based multi-objective evolutionary algorithm (MOEA/D) is employed to seek the non-dominated solutions, i.e., the Pareto frontier. Finally, collaborative planning results of two coupled distribution and transportation systems are presented to illustrate the performance of the proposed model and solution method. Â© 2014 IEEE.
|2014||Xu Y, Dong ZY, Meng K, Yao WF, Zhang R, Wong KP, 'Multi-objective dynamic VAR planning against short-term voltage instability using a decomposition-based evolutionary algorithm', IEEE Transactions on Power Systems, 29 2813-2822 (2014) [C1]|
Short-term voltage stability is an increasing concern in today's power systems due to the growing penetration of induction motors. This paper proposes a systematic method for optimal placement of dynamic VAR support against short-term voltage instability. The problem is formulated as a multi-objective optimization model minimizing two conflicting objectives: 1) the total investment cost and 2) the expected unacceptable short-term voltage performance subject to a set of probable contingencies. STATCOM is employed for its stronger dynamic VAR support capability. Indices for quantifying the short-term voltage stability and the related risk level are proposed for problem modeling. Candidate buses are selected based on the concept of trajectory sensitivity. Load dynamics are fully considered using a composite load model containing induction motor and other typical components. A relatively new and superior multi-objective evolutionary algorithm called MOEA/D is introduced and employed to find the Pareto optimal solutions of the model. The proposed method is verified on the New England 39-bus system using industry-grade models and simulation tool.
|2014||Yang H, Zhang D, Meng K, Dong ZY, Lai M, 'MULTI-NETWORK COMBINED COOLING HEATING AND POWER SYSTEM SCHEDULING CONSIDERING EMISSION TRADING', PACIFIC JOURNAL OF OPTIMIZATION, 10 177-198 (2014)|
|2014||Yang H, Yi D, Zhao J, Luo F, Dong Z, 'Distributed optimal dispatch of virtual power plant based on elm transformation', Journal of Industrial and Management Optimization, 10 1297-1318 (2014) [C1]|
To implement the optimal dispatch of distributed energy resources (DER) in the virtual power plant (VPP), a distributed optimal dispatch method based on ELM (Extreme Learning Machine) transformation is proposed. The joint distribution of maximum available outputs of multiple wind turbines in the VPP is firstly modeled with the Gumbel-Copula function. A VPP optimal dispatch model is then formulated to achieve maximum utilization of renewable energy generation, which can take into account the constraints of electric power network and DERs. Based on the Gumbel-Copula joint distribution, the nonlinear functional relationship between the wind power cost and wind turbine output is approximated using ELM. The approximated functional relationship is then transformed into a set of equality constraints, which can be easily integrated with the optimal dispatch model. To solve the optimal dis-patch problem, a distributed primal-dual sub-gradient algorithm is proposed to determine the operational strategies of DERs via local decision making and limited communication between neighbors. Finally, case studies based on the 15-node and the 118-node virtual power plant prove that the proposed method is effective and can achieve identical performance as the centralized dispatch approach.
|2014||Xu Y, Dong ZY, Luo F, Zhang R, Wong KP, 'Parallel-differential evolution approach for optimal event-driven load shedding against voltage collapse in power systems', IET Generation, Transmission and Distribution, 8 651-660 (2014) [C1]|
Event-driven load shedding is an effective countermeasure against voltage collapse in power systems. Conventionally, its optimisation relies on sensitivity-based linear methods, which, however, could suffer from unrealistic assumptions and suboptimality. In this study, an alternative approach based on parallel-differential evolution (P-DE) is proposed for efficiently and globally optimising the event-driven load shedding against voltage collapse. Working in a parallel structure, the approach consists of candidate buses selection, voltage stability assessment (VSA) and DE optimisation. Compared with conventional methods, it fully considers the non-linearity of the problem and is able to effectively escape from local optima and not limited to system modelling and unrealistic assumptions. Besides, any type of objective functions and VSA techniques can be used. The proposed approach has been tested on the IEEE 118-bus test system considering two cases for preventive control and corrective control, respectively, and compared with the two existing methods. Simulation results have verified its effectiveness and superiority over the compared methods. Â© The Institution of Engineering and Technology 2014.
|2014||Zhang R, Dong ZY, Xu Y, Wong KP, Lai M, 'Hybrid computation of corrective security-constrained optimal power flow problems', IET Generation, Transmission and Distribution, 8 995-1006 (2014) [C1]|
Corrective security-constrained optimal power flow (CSCOPF) considers the use of corrective control to remove system security violations in the post-contingency state. Its optimality not only depends on the pre-contingency state, but also the post-contingency state as well as the involved corrective control actions. This study first gives a comprehensive review on the relevant OPF models and then proposes a hybrid method to solve the CSCOPF problem. It makes use of the evolutionary algorithms to randomly search the maximum feasible region and state-of-the-art OPF solution technique (interior-point method) to provide deterministic solutions in the found region. The two interact iteratively to progressively approach the final solution. The proposed method is verified on the IEEE 14-bus and 118-bus systems. Comparison studies show that (i) CSCOPF can better balance the security and economy and (ii) the hybrid method is overall superior (in solution quality, robustness and convergence characteristic) over the single evolutionary algorithm. Parallel processing is applied to speed-up the computations. Â© The Institution of Engineering and Technology 2014.
|2014||Luo F, Zhao J, Qiu J, Foster J, Peng Y, Dong Z, 'Assessing the transmission expansion cost with distributed generation: An australian case study', IEEE Transactions on Smart Grid, 5 1892-1904 (2014) [C1]|
Distributed generation (DG) is rapidly increasing its penetration level worldwide and is expected to play a more important role in providing power. An important benefit of DG is its ability to defer transmission investments. In this paper, a simulation model is implemented to conduct quantitative analysis on the effect of DG on transmission investment deferral. The transmission expansion model is formulated as a multi-objective optimization problem with comprehensive technical constraints, such as AC power flow and system reliability and/or security. The case study that was selected is the Queensland electricity market in Australia. Simulation results show that DG can reduce transmission investments significantly. This ability however is greatly influenced by a number of factors, such as the location of DG, the network topology, and power system technical constraints. Â© 2014 IEEE.
|2014||Yang H, Yang S, Zhao J, Dong Z, 'Complex dynamics and chaos control of electricity markets with heterogeneous expectations', INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 24 1047-1064 (2014) [C1]|
|2014||Yang H, Zhang D, Meng K, Dong ZY, Lai M, 'Multi-network combined cooling heating and power system scheduling considering emission trading', Pacific Journal of Optimization, 10 177-198 (2014) [C1]|
|2013||Li XR, Yu CW, Luo FJ, Ren SY, Dong ZY, Wong KP, 'Impacts of emission trading schemes on GENCOs' decision making under multimarket environment', Electric Power Systems Research, 95 257-267 (2013) [C1]|
|2013||Arief A, Dong Z, Nappu MB, Gallagher M, 'Under voltage load shedding in power systems with wind turbine-driven doubly fed induction generators', Electric Power Systems Research, 96 91-100 (2013) [C1]|
|2013||Li XR, Yu CW, Xu Z, Luo FJ, Dong ZY, Wong KP, 'A Multimarket Decision-Making Framework for GENCO Considering Emission Trading Scheme', IEEE TRANSACTIONS ON POWER SYSTEMS, 28 4099-4108 (2013) [C1]|
|2013||Xu Y, Dong ZY, Wong KP, Liu E, Yue B, 'Optimal capacitor placement to distribution transformers for power loss reduction in radial distribution systems', IEEE Transactions on Power Systems, 28 4072-4079 (2013) [C1]|
Deploying shunt capacitor banks in distribution systems can effectively reduce the power loss and provide additional benefits for system operation. In practice, the power loss on distribution transformers can account for a considerable portion of the overall loss. This paper proposes a method for optimal placement of capacitor banks to the distribution transformers to reduce power loss. The capacitor bank locations are considered at the low-side of transformers. The net present value (NPV) criterion is adopted to evaluate the cost benefit of the capacitor installation project. First, an explicit formula for directly calculating the power loss of radial distribution systems is derived. Then, the optimal capacitor bank placement is formulated as a mixed-integer programming (MIP) model maximizing the NPV of the project subject to certain constraints. The model is suitable for being solved by commercial MIP packages, and the operational control of the capacitor banks to maximize the power loss reduction can be simply achieved by local automatic switching according to VAR measurements. The proposed method has been practically applied in the Macau distribution system, and the simulation results show that the proposed method is computationally efficient, and a considerable positive NPV can be obtained from the optimal capacitor bank placement. Â© 2013 IEEE.
|2013||Yang H, Yi D, Zhao J, Dong Z, 'Distributed optimal dispatch of virtual power plant via limited communication', IEEE Transactions on Power Systems, 28 3511-3512 (2013) [C1]|
|2013||Wang YY, Zeng XJ, Jian JB, Dong ZY, Li ZW, Huang Y, 'Studies on the Stator Single-Phase-to-Ground Fault Protection for a High-Voltage Cable-Wound Generator', IEEE TRANSACTIONS ON ENERGY CONVERSION, 28 344-352 (2013) [C1]|
|2013||Yang H, Chung CY, Zhao J, Dong Z, 'A probability model of ice storm damages to transmission facilities', IEEE Transactions on Power Delivery, 28 557-565 (2013) [C1]|
|2013||Yang H, Yi J, Zhao J, Dong Z, 'Extreme learning machine based genetic algorithm and its application in power system economic dispatch', Neurocomputing, 102 154-162 (2013) [C1]|
|2013||Xu Y, Dai Y, Dong ZY, Zhang R, Meng K, 'Extreme learning machine-based predictor for real-time frequency stability assessment of electric power systems', NEURAL COMPUTING & APPLICATIONS, 22 501-508 (2013) [C1]|
|2013||Radzi NH, Bansal RC, Dong ZY, Hassan MY, Wong KP, 'An efficient distribution factors enhanced transmission pricing method for Australian NEM transmission charging scheme', Renewable Energy, 53 319-328 (2013) [C1]|
|2013||Dong ZY, Xu Y, Zhang P, Wong KP, 'Using IS to Assess an Electric Power System's Real-Time Stability', IEEE INTELLIGENT SYSTEMS, 28 60-66 (2013) [C2]|
|2013||Zhang R, Dong ZY, Xu Y, Meng K, Wong KP, 'Short-term load forecasting of Australian national electricity market by an ensemble model of extreme learning machine', IET Generation, Transmission and Distribution, 7 391-397 (2013) [C1]|
Artificial Neural Network (ANN) has been recognized as a powerful method for short-term load forecasting (STLF) of power systems. However, traditional ANNs are mostly trained by gradient-based learning algorithms which usually suffer from excessive training and tuning burden as well as unsatisfactory generalization performance. Based on the ensemble learning strategy, this paper develops an ensemble model of a promising novel learning technology called extreme learning machine (ELM) for high-quality STLF of Australian National Electricity Market (NEM). The model consists of a series of single ELMs. During the training, the ensemble model generalizes the randomness of single ELMs by selecting not only random input parameters but also random hidden nodes within a pre-defined range. The forecast result is taken as the median value the single ELM outputs. Owing to the very fast training/tuning speed of ELM, the model can be efficiently updated to on-line track the variation trend of the electricity load and maintain the accuracy. The developed model is tested with the NEM historical load data and its performance is compared with some state-of-the-art learning algorithms. The results show that the training efficiency and the forecasting accuracy of the developed model are superior over the competitive algorithms.Â©The Institution of Engineering and Technology 2013.
|2013||Sun Z-L, Lam K-M, Dong Z-Y, Wang H, Gao Q-W, Zheng C-H, 'Face Recognition with Multi-Resolution Spectral Feature Images', PLOS ONE, 8 (2013) [C1]|
|2013||Xue Y, Li T, Yin X, Dong Z, Wen F, Huang J, Xue F, 'Managements of Generalized Congestions', IEEE TRANSACTIONS ON SMART GRID, 4 1675-1683 (2013) [C1]|
|2012||Taggart S, James G, Dong ZY, Russell C, 'The future of renewables linked by a transnational Asian grid', Proceedings of the IEEE, 100 348-359 (2012) [C1]|
|2012||Ziser CJ, Dong ZY, Wong KP, 'Incorporating weather uncertainty in demand forecasts for electricity market planning', International Journal of Systems Science, 43 1336-1346 (2012) [C1]|
|2012||Kong SY, Bansal RC, Dong ZY, 'Comparative small-signal stability analyses of PMSG-, DFIG- and SCIG-based wind farms', International Journal of Ambient Energy, 33 87-97 (2012) [C1]|
|2012||Huang J, Xue Y, Dong ZY, Wong KP, 'An efficient probabilistic assessment method for electricity market risk management', IEEE Transactions on Power Systems, 27 1485-1493 (2012) [C1]|
|2012||Mai RK, Fu L, Dong ZY, Wong KP, Bo ZQ, Xu HB, 'Dynamic phasor and frequency estimators considering decaying DC components', IEEE Transactions on Power Systems, 27 671-681 (2012) [C1]|
|2012||Yang L, Xu Z, Ostergaard J, Dong ZY, Wong KP, 'Advanced control strategy of DFIG wind turbines for power system fault ride through', IEEE Transactions on Power Systems, 27 713-722 (2012) [C1]|
|2012||Xu Y, Dong ZY, Guan L, Zhang R, Wong KP, Luo F, 'Preventive dynamic security control of power systems based on pattern discovery technique', IEEE Transactions on Power Systems, 27 1236-1244 (2012) [C1]|
|2012||Xu Y, Dong ZY, Meng K, Zhao J, Wong KP, 'A hybrid method for transient stability-constrained optimal power flow computation', IEEE Transactions on Power Systems, 27 1769-1777 (2012) [C1]|
|2012||Xu Y, Dong ZY, Zhao J, Zhang P, Wong KP, 'A reliable intelligent system for real-time dynamic security assessment of power systems', IEEE Transactions on Power Systems, 27 1253-1263 (2012) [C1]|
|2012||Dong ZY, Zhao J, Hill DJ, 'Numerical simulation for stochastic transient stability assessment', IEEE Transactions on Power Systems, 27 1741-1749 (2012) [C1]|
|2012||Dong ZY, Meng K, Xu Y, Wong KP, Ngan HW, 'Electricity price forecasting with extreme learning machine and bootstrapping', IEEE Transactions on Power Systems, 27 2055-2062 (2012) [C1]|
|2012||Lei X, Xue Y, Xue F, Xu T, Dong ZY, Wen F, 'Quantitative analysis for transient voltage stability of induction generators', Dianli Xitong Zidonghua/Automation of Electric Power Systems, 36 1-6 (2012) [C1]|
|2012||Xue Y, Lei X, Xue F, Wen F, Dong ZY, Ledwich G, 'Review on wide area protection of electric power systems', Gaodianya Jishu/High Voltage Engineering, 38 513-520 (2012) [C2]|
|2012||Xu Y, Dong ZY, Xu Z, Meng K, Wong KP, 'An intelligent dynamic security assessment framework for power systems with wind power', IEEE Transactions on Industrial Informatics, 8 995-1003 (2012) [C1]|
|2012||Zhao J, Wen F, Dong ZY, Xue Y, Wong KP, 'Optimal dispatch of electric vehicles and wind power using enhanced particle swarm optimization', IEEE Transactions on Industrial Informatics, 8 889-899 (2012) [C1]|
|2012||Yao F, Dong ZY, Meng K, Xu Z, Iu HH-C, Wong KP, 'Quantum-inspired particle swarm optimization for power system operations considering wind power uncertainty and carbon tax in Australia', IEEE Transactions on Industrial Informatics, 8 880-888 (2012) [C1]|
|2012||Dai Y, Xu Y, Dong ZY, Wong KP, Zhuang L, 'Real-time prediction of event-driven load shedding for frequency stability enhancement of power systems', IET Generation, Transmission and Distribution, 6 914-921 (2012) [C1]|
|2012||Radzi NH, Bansal RC, Dong ZY, Hasan KN, Lu Z, 'Overview of the Australian national electricity market transmission use of system charges for integrating renewable generation to existing grid', IET Generation, Transmission and Distribution, 6 863-873 (2012) [C1]|
|2011||Xu Y, Dong ZY, Meng K, Zhang R, Wong KP, 'Real-time transient stability assessment model using extreme learning machine', IET Generation, Transmission & Distribution, 5 314-322 (2011) [C1]|| |
|2011||Yang L, Xu Z, Ostergaard J, Dong ZY, Wong KP, Ma X, 'Oscillatory stability and eigenvalue sensitivity analysis of A DFIG wind turbine system', IEEE Transactions on Energy Conversion, 26 328-339 (2011) [C1]|| |
|2011||Mai RK, Fu L, Dong ZY, Kirby B, Bo ZQ, 'An adaptive dynamic phasor estimator considering DC offset for PMU applications', IEEE Transactions on Power Delivery, 26 1744-1754 (2011) [C1]|
|2011||Yang H, Xu W, Zhao J, Wang D, Dong ZY, 'Predicting the probability of ice storm damages to electricity transmission facilities based on ELM and Copula function', Neurocomputing, 74 2573-2581 (2011) [C1]|
|2011||Zhao J, Wen F, Xue Y, Dong ZY, 'Modeling analysis and control research framework of cyber physical power systems', Dianli Xitong Zidonghua - Automation of Electric Power Systems, 35 1-8 (2011) [C2]|| |
|2007||Zhao JH, Dong ZY, Li X, Wong KP, 'A framework for electricity price spike analysis with advanced data mining methods', IEEE TRANSACTIONS ON POWER SYSTEMS, 22 376-385 (2007) [C1]|
|2007||Yang GY, Hovland G, Majuruder R, Dong ZY, 'TCSC allocation based on line flow based equations via mixed-integer programming', IEEE TRANSACTIONS ON POWER SYSTEMS, 22 2262-2269 (2007) [C1]|
|2007||Zhao JH, Dong ZY, Li X, 'Electricity market price spike forecasting and decision making', IET GENERATION TRANSMISSION & DISTRIBUTION, 1 647-654 (2007) [C1]|
|2006||Chen D-Y, Li X, Dong ZY, Chen X, 'Fitness assessment of document model', INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 37 893-903 (2006) [C1]|
|2006||Xu Z, Dong ZY, Wong KP, 'A hybrid planning method for transmission networks in a deregulated environment', IEEE TRANSACTIONS ON POWER SYSTEMS, 21 925-932 (2006) [C1]|
|2006||Ma J, Dong ZY, Zhang P, 'Comparison of BR and QR eigenvalue algorithms system small signal stability analysis', IEEE TRANSACTIONS ON POWER SYSTEMS, 21 1848-1855 (2006) [C1]|
|2006||Xu Z, Dong ZY, Wong KP, 'Transmission planning in a deregulated environment', IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION, 153 326-334 (2006) [C1]|
|2005||Dong ZY, Hill DJ, Guo Y, 'A power system control scheme based on security visualisation in parameter space', INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 27 488-495 (2005) [C1]|
|2005||Duan G, Zhao YD, Wei B, Xin FW, 'Power flow based monetary flow method for electricity transmission and wheeling pricing', ELECTRIC POWER SYSTEMS RESEARCH, 74 293-305 (2005) [C1]|