arXiv subjects

Chao Luo

Publications and source records attributed to Chao Luo.

24 records · Page 2Linked to original sources

arXiv2018

Partial Template Based Receiver in Impulse Radio Ultra-Wideband Communication Systems

For high speed ultra-wideband (UWB) communication systems, the multipath interference exhibits a primary obstacle to improve transmission performance. In order to enhance the signal to interference plus noise ratio (SINR) in the receiver, a partial template receiver is proposed in this paper. Instead of using the conventional template, the model in this paper adopts a partial template to demodulate signals. To analyze the performance of the proposed receiver, bit error rate (BER) formulation of IR-UWB systems in the presence of multipath interference, multiuser interference and addictive white Gaussian noise (AWGN) is derived in IEEE 802.15.4a channel models. Simulation results show that, compared with the conventional correlation receiver, the proposed receiver can achieve a better BER performance for high Eb/N0, which falls in the conventional used Eb/N0 range.

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arXiv2018

Performance Analysis of UWB Based Wireless Sensor Networks in Indoor Office LOS Environment

With the fast development of wireless sensor networks (WSN), more attentions are paid to high data rate transmission of WSN, and hence, in IEEE 802.15.4a standard, ultra-wideband (UWB) is introduced as one of the physical layer technique to support high transmission data rate and precisie locationing applications. In order to analyze the bit error rate (BER) performance of UWB based WSN, a system model considering intra-symbol interference (IASI), inter-symbol interference (ISI), multiuser interference (MUI) and addictive white Gaussian noise (AWGN) is proposed in this paper, and then verified using simulation results. Moreover, the pulse waveforms complying with the spectrum requirement of IEEE 802.15.4a standard are given, and based on such obtained pulses, the effect of transmission data rate and user number is also shown. Results show that with the increase of SNR, the intra-symbol interference will decrease the system performance significantly, and system performance can be improve by using pulse waveforms with little intra-symbol interference.

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arXiv2018

Placement of EV Charging Stations --- Balancing Benefits among Multiple Entities

This paper studies the problem of multi-stage placement of electric vehicle (EV) charging stations with incremental EV penetration rates. A nested logit model is employed to analyze the charging preference of the individual consumer (EV owner), and predict the aggregated charging demand at the charging stations. The EV charging industry is modeled as an oligopoly where the entire market is dominated by a few charging service providers (oligopolists). At the beginning of each planning stage, an optimal placement policy for each service provider is obtained through analyzing strategic interactions in a Bayesian game. To derive the optimal placement policy, we consider both the transportation network graph and the electric power network graph. A simulation software --- The EV Virtual City 1.0 --- is developed using Java to investigate the interactions among the consumers (EV owner), the transportation network graph, the electric power network graph, and the charging stations. Through a series of experiments using the geographic and demographic data from the city of San Pedro District of Los Angeles, we show that the charging station placement is highly consistent with the heatmap of the traffic flow. In addition, we observe a spatial economic phenomenon that service providers prefer clustering instead of separation in the EV charging market.

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arXiv2018

Stochastic Dynamic Pricing for EV Charging Stations with Renewables Integration and Energy Storage

This paper studies the problem of stochastic dynamic pricing and energy management policy for electric vehicle (EV) charging service providers. In the presence of renewable energy integration and energy storage system, EV charging service providers must deal with multiple uncertainties --- charging demand volatility, inherent intermittency of renewable energy generation, and wholesale electricity price fluctuation. The motivation behind our work is to offer guidelines for charging service providers to determine proper charging prices and manage electricity to balance the competing objectives of improving profitability, enhancing customer satisfaction, and reducing impact on power grid in spite of these uncertainties. We propose a new metric to assess the impact on power grid without solving complete power flow equations. To protect service providers from severe financial losses, a safeguard of profit is incorporated in the model. Two algorithms --- stochastic dynamic programming (SDP) algorithm and greedy algorithm (benchmark algorithm) --- are applied to derive the pricing and electricity procurement policy. A Pareto front of the multiobjective optimization is derived. Simulation results show that using SDP algorithm can achieve up to 7% profit gain over using greedy algorithm. Additionally, we observe that the charging service provider is able to reshape spatial-temporal charging demands to reduce the impact on power grid via pricing signals.

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arXiv2018

A Consumer Behavior Based Approach to Multi-Stage EV Charging Station Placement

This paper presents a multi-stage approach to the placement of charging stations under the scenarios of different electric vehicle (EV) penetration rates. The EV charging market is modeled as the oligopoly. A consumer behavior based approach is applied to forecast the charging demand of the charging stations using a nested logit model. The impacts of both the urban road network and the power grid network on charging station planning are also considered. At each planning stage, the optimal station placement strategy is derived through solving a Bayesian game among the service providers. To investigate the interplay of the travel pattern, the consumer behavior, urban road network, power grid network, and the charging station placement, a simulation platform (The EV Virtual City 1.0) is developed using Java on Repast.We conduct a case study in the San Pedro District of Los Angeles by importing the geographic and demographic data of that region into the platform. The simulation results demonstrate a strong consistency between the charging station placement and the traffic flow of EVs. The results also reveal an interesting phenomenon that service providers prefer clustering instead of spatial separation in this oligopoly market.

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arXiv2017

Identify Critical Branches with Cascading Failure Chain Statistics and Hypertext-Induced Topic Search Algorithm

An effective way to suppress the cascading failure risk is the branch capacity upgrade, whose optimal decision making, however, may incur high computational burden. A practical way is to find out some critical branches as the candidates in advance. This paper proposes a simulation data oriented approach to identify the critical branches with higher importance in cascading failure propagation. First, a concept of cascading failure chain (CFC) is introduced and numerous samples of CFC are generated with an AC power flow based cascading failure simulator. Then, a directed weighted graph is constructed, whose edges denotes the severities of branch interactions. Third, the weighted hypertext-induced topic search (HITS) algorithm is used to rate and rank this graph's vertices,through which the critical branches can be identified accordingly. Validations on IEEE 118bus and RTS96 systems show that the proposed approach can identify critical branches whose capacity upgrades suppress cascading failure risk more greatly. Moreover, it is also shown that structural importance of a branch does not agree with its importance in cascading failure, which indicates the effectiveness of the proposed approach compared with structure vulnerabilities based identifying methods.

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