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Chunsheng Wang
School of Automation, Central South University, Changsha, 410083, China

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Journal article
Published: 11 May 2021 in International Journal of Electrical Power & Energy Systems
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In this paper, a framework of multi-energy system (MES) integrating with a liquid air energy storage (LAES) system was proposed. LAES, where liquid air works as an energy storage media, is a powerful and eco-friendly technology for storing renewable energy resources and reducing grid curtailment. Considering the characteristics of LAES (i.e. cold and heat circulation), the incorporation of LAES system into the Combined Cooling, Heating and Power system can achieve integrated use of energy and effectively save energy. Moreover, the prices of electricity will affect the overall cost of the MES. In other words, the decision-makers of the MES need to consider the uncertainty of electricity prices when making power dispatching decisions. To model the uncertainty of electricity prices, the information gap decision theory method was used to study power dispatching strategies of the MES. Three different strategies were proposed, including risk-neutral, risk-averse and risk-taker. In addition, demand response algorithms were used to study load transfer strategies. The results show that the demand responses of the three strategies are effective in terms of load transfer and cost saving. The total operation cost in the risk-neutral strategy with demand response can be 6.82% less than that without demand response; In the risk-taker strategy with demand response, the allowable grid electricity price is reduced by 25.24% when the opportunity cost drops by $8,000, and 23.32% without demand response. With additional robustness cost, the acceptable price change ratio using demand response is 21.91% in the risk-averse strategy, and 20.04% without demand response.

ACS Style

Caixin Yan; Chunsheng Wang; Yukun Hu; Minghui Yang; Hao Xie. Optimal operation strategies of multi-energy systems integrated with liquid air energy storage using information gap decision theory. International Journal of Electrical Power & Energy Systems 2021, 132, 107078 .

AMA Style

Caixin Yan, Chunsheng Wang, Yukun Hu, Minghui Yang, Hao Xie. Optimal operation strategies of multi-energy systems integrated with liquid air energy storage using information gap decision theory. International Journal of Electrical Power & Energy Systems. 2021; 132 ():107078.

Chicago/Turabian Style

Caixin Yan; Chunsheng Wang; Yukun Hu; Minghui Yang; Hao Xie. 2021. "Optimal operation strategies of multi-energy systems integrated with liquid air energy storage using information gap decision theory." International Journal of Electrical Power & Energy Systems 132, no. : 107078.

Journal article
Published: 21 February 2021 in Energies
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An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified.

ACS Style

Xiao Tang; Chunsheng Wang; Yukun Hu; Zijian Liu; Feiliang Li. Adaptive Fuzzy PID Based on Granular Function for Proton Exchange Membrane Fuel Cell Oxygen Excess Ratio Control. Energies 2021, 14, 1140 .

AMA Style

Xiao Tang, Chunsheng Wang, Yukun Hu, Zijian Liu, Feiliang Li. Adaptive Fuzzy PID Based on Granular Function for Proton Exchange Membrane Fuel Cell Oxygen Excess Ratio Control. Energies. 2021; 14 (4):1140.

Chicago/Turabian Style

Xiao Tang; Chunsheng Wang; Yukun Hu; Zijian Liu; Feiliang Li. 2021. "Adaptive Fuzzy PID Based on Granular Function for Proton Exchange Membrane Fuel Cell Oxygen Excess Ratio Control." Energies 14, no. 4: 1140.

Journal article
Published: 21 November 2020 in Energies
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With the rapid increase of photovoltaic (PV) penetration and distributed grid access, photovoltaic generation (PVG)-integrated multi-area power systems may be disturbed by more uncertain factors, such as PVG, grid-tie inverter parameters, and resonance. These uncertain factors will exacerbate the frequency fluctuations of PVG integrated multi-area interconnected power systems. For such system, this paper proposes a load frequency control (LFC) strategy based on double equivalent-input-disturbance (EID) controllers. The PVG linear model and the multi-area interconnected power system linear model were established, respectively, and the disturbances were caused by grid voltage fluctuations in PVG subsystem and PV output power fluctuation and load change in multi-area interconnected power system. In PVG subsystems and multi-area interconnected power systems, two EID controllers add differently estimated equivalent system disturbances, which has the same effect as the actual disturbance, to the input channel to compensate for the impact of actual disturbances. The simulation results in MATLAB/Simulink show that the frequency deviation range of the proposed double EID method is 6% of FA-PI method and 7% of conventional PI method, respectively, when the grid voltage fluctuation and load disturbance exist. The double EID method can better compensate for the effects of external disturbances, suppress frequency fluctuations, and make the system more stable.

ACS Style

Minghui Yang; Chunsheng Wang; Yukun Hu; Zijian Liu; Caixin Yan; Shuhang He. Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers. Energies 2020, 13, 6103 .

AMA Style

Minghui Yang, Chunsheng Wang, Yukun Hu, Zijian Liu, Caixin Yan, Shuhang He. Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers. Energies. 2020; 13 (22):6103.

Chicago/Turabian Style

Minghui Yang; Chunsheng Wang; Yukun Hu; Zijian Liu; Caixin Yan; Shuhang He. 2020. "Load Frequency Control of Photovoltaic Generation-Integrated Multi-Area Interconnected Power Systems Based on Double Equivalent-Input-Disturbance Controllers." Energies 13, no. 22: 6103.

Journal article
Published: 05 September 2018 in Biomedical Signal Processing and Control
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High-frequency oscillations reflect the abnormal brain electrical activity in patients with epilepsy. It is significant to research the relationship between high-frequency oscillation and epilepsy originating area for the diagnosis and treatment of epilepsy. In view of the identification of epileptic EEG and the location of epileptic foci, a localization algorithm based on Teager operator is proposed. Firstly, the original epileptic EEG data are preprocessed, the wavelet weighted threshold and the frequency notch method are used to denoise the original epileptic high frequency oscillation signal. Taking into account the frequency characteristics of the high frequency oscillating signal itself, the FIR (Finite Impulse Response) digital filter is used to filter the epileptic high-frequency oscillation signal. Secondly, because the high frequency oscillation rhythm has the characteristics of high frequency, high energy and low amplitude, the Teager energy operator and curve length method are used to extract the characteristics. The PSD (Power Spectral Density) method is applied to qualitative analysis of epileptic lesion location. Finally, the EMD (Empirical Mode Decomposition) algorithm is used to decompose the high-frequency oscillation signal. Combined with Teager energy operator, Teager-huang transform is used to analyze the signal by time-frequency energy analysis. Quantitative analysis of epileptic lesion location is made by using EMD energy entropy method for different lead epileptic signals. The algorithm can effectively locate the location of the focus, independent of individual parameters and high degree of automation. It has good clinical application prospects.

ACS Style

Chunsheng Wang; Hui Yi; Wei Wang; Palaniappan Valliappan. Lesion localization algorithm of high-frequency epileptic signal based on Teager energy operator. Biomedical Signal Processing and Control 2018, 47, 262 -275.

AMA Style

Chunsheng Wang, Hui Yi, Wei Wang, Palaniappan Valliappan. Lesion localization algorithm of high-frequency epileptic signal based on Teager energy operator. Biomedical Signal Processing and Control. 2018; 47 ():262-275.

Chicago/Turabian Style

Chunsheng Wang; Hui Yi; Wei Wang; Palaniappan Valliappan. 2018. "Lesion localization algorithm of high-frequency epileptic signal based on Teager energy operator." Biomedical Signal Processing and Control 47, no. : 262-275.

Journal article
Published: 03 September 2018 in Energies
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Improved thermal efficiency in energy-intensive metal-reheating furnaces has attracted much attention recently in efforts to reduce both fuel consumption, and CO2 emissions. Thermal efficiency of these furnaces has improved in recent years (through the installation of regenerative or recuperative burners), and improved refractory insulation. However, further improvements can still be achieved through setting up reference values for the optimal set-point temperatures of the furnaces. Having a reasonable expression of objective function is of particular importance in such optimisation. This paper presents a function value-based multi-objective optimisation where the objective functions, which address such concerns as discharge temperature, temperature uniformity, and specific fuel consumption, are dependent on each other. Hooke-Jeeves direct search algorithm (HJDSA) was used to minimise the objective functions under a series of production rates. The optimised set-point temperatures were further used to construct an artificial neural network (ANN) of set-point temperature in each control zone. The constructed artificial neural networks have the potential to be incorporated into a more advanced control solution to update the set-point temperatures when the reheating furnace encounters a production rate change. The results suggest that the optimised set-point temperatures can highly improve heating accuracy, which is less than 1 °C from the desired discharge temperature.

ACS Style

Bo Gao; Chunsheng Wang; Yukun Hu; C. K. Tan; Paul Alun Roach; Liz Varga. Function Value-Based Multi-Objective Optimisation of Reheating Furnace Operations Using Hooke-Jeeves Algorithm. Energies 2018, 11, 2324 .

AMA Style

Bo Gao, Chunsheng Wang, Yukun Hu, C. K. Tan, Paul Alun Roach, Liz Varga. Function Value-Based Multi-Objective Optimisation of Reheating Furnace Operations Using Hooke-Jeeves Algorithm. Energies. 2018; 11 (9):2324.

Chicago/Turabian Style

Bo Gao; Chunsheng Wang; Yukun Hu; C. K. Tan; Paul Alun Roach; Liz Varga. 2018. "Function Value-Based Multi-Objective Optimisation of Reheating Furnace Operations Using Hooke-Jeeves Algorithm." Energies 11, no. 9: 2324.

Journal article
Published: 08 June 2018 in Energies
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Reasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost.

ACS Style

Peng Wang; Chunsheng Wang; Yukun Hu; Liz Varga; Wei Wang. Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China. Energies 2018, 11, 1498 .

AMA Style

Peng Wang, Chunsheng Wang, Yukun Hu, Liz Varga, Wei Wang. Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China. Energies. 2018; 11 (6):1498.

Chicago/Turabian Style

Peng Wang; Chunsheng Wang; Yukun Hu; Liz Varga; Wei Wang. 2018. "Power Generation Expansion Optimization Model Considering Multi-Scenario Electricity Demand Constraints: A Case Study of Zhejiang Province, China." Energies 11, no. 6: 1498.

Article
Published: 01 February 2017 in Journal of Central South University
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An improved ensemble empirical mode decomposition (EEMD) algorithm is described in this work, in which the sifting and ensemble number are self-adaptive. In particular, the new algorithm can effectively avoid the mode mixing problem. The algorithm has been validated with a simulation signal and locomotive bearing vibration signal. The results show that the proposed self-adaptive EEMD algorithm has a better filtering performance compared with the conventional EEMD. The filter results further show that the feature of the signal can be distinguished clearly with the proposed algorithm, which implies that the fault characteristics of the locomotive bearing can be detected successfully.

ACS Style

Chun-Sheng Wang; Chun-Yang Sha; Mei Su; Yu-Kun Hu. An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter. Journal of Central South University 2017, 24, 478 -488.

AMA Style

Chun-Sheng Wang, Chun-Yang Sha, Mei Su, Yu-Kun Hu. An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter. Journal of Central South University. 2017; 24 (2):478-488.

Chicago/Turabian Style

Chun-Sheng Wang; Chun-Yang Sha; Mei Su; Yu-Kun Hu. 2017. "An algorithm to remove noise from locomotive bearing vibration signal based on self-adaptive EEMD filter." Journal of Central South University 24, no. 2: 478-488.