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| 1 | Artificial Intelligence Based Smart Energy Community Management: A Reinforcement Learning Approach显示文摘This paper presents a smart energy community management approach which is capable of implementing P2P trading and managing household energy storage systems.A smart residential community concept is proposed consisting of domestic users and a local energy pool,in which users are free to trade with the local energy pool and enjoy cheap renewable energy while avoiding the installation of new energy generation equipment.The local energy pool could harvest surplus energy from users and renewable resources,at the same time it sells energy at a higher price than Feed-in-Tariff(FIT)but lower than the retail price.In order to encourage the participation in local energy trading,the electricity price of the energy pool is determined by a real-time demand/supply ratio.Under this pricing mechanism,retail price,users and renewable energy could all affect the electricity price which leads to higher consumers’profits and more optimized utilization of renewable energy.The proposed energy trading process was modeled as a Markov Decision Process(MDP)and a reinforcement learning algorithm was adopted to find the optimal decision in the MDP because of its excellent performance in on-going and model-free tasks.In addition,the fuzzy inference system makes it possible to use Q-learning in continuous state-space problems(Fuzzy Q-learning)considering the infinite possibilities in the energy trading process.To evaluate the performance of the proposed demand side management system,a numerical analysis is conducted in a community comparing the electricity costs before and after using the proposed energy management system. | Suyang Zhou Zijian Hu Wei Gu Meng Jiang Xiao-Ping Zhang | 2019 | CSEE Journal of Power and Energy Systems2019，5，1： | 12 |
| 2 | Aggregator Service for PV and Battery Energy Storage Systems of Residential Building显示文摘Distributed energy resources(DERs),including photovoltaic(PV)systems,small wind turbines,and energy storage systems(ESSs)are being increasingly installed in many residential units and the industry sector at large.DER installations in apartment buildings,however,pose a more complex issue particularly in the context of property ownership and the distribution of DR benefits.In this paper,a novel aggregator service is proposed to provide centralized management services for residents and DER asset owners in apartment buildings.The proposed service consists of a business model for billing and benefits distribution,and a model predictive control(MPC)control algorithm for managing and optimizing DER operations.Both physical and communication structures are proposed to ensure the implementation of such aggregator services for buildings.Three billing tariffs,i.e.,flat rate,time-of-use(TOU),and real time pricing(RTP)are compared by way of case studies.The results indicate that the proposed aggregator service is compatible with the business model.It is shown to offer good performance in load shifting,bill savings,and energy trading of DERs.Overall,the aggregator service is expected to provide benefits in reducing the pay back periods of the investment. | Jianing Li Zhi Wu Suyang Zhou Hao Fu Xiao-Ping Zhang | 2015 | CSEE Journal of Power and Energy Systems2015，1，4： | 11 |
| 3 | Identification of Ebola virus microRNAs and their putative pathological function显示文摘Ebola virus(EBOV),a member of the filovirus family,is an enveloped negative-sense RNA virus that causes lethal infections in humans and primates.Recently,more than 1000 people have been killed by the Ebola virus disease in Africa,yet no specific treatment or diagnostic tests for EBOV are available.In this study,we identified two putative viral microRNA precursors(pre-miRNAs)and three putative mature microRNAs(miRNAs)derived from the EBOV genome.The production of the EBOV miRNAs was further validated in HEK293T cells transfected with a pcDNA6.2-GW/EmGFP-EBOV-pre-miRNA plasmid,indicating that EBOV miRNAs can be produced through the cellular miRNA processing machinery.We also predicted the potential target genes of these EBOV miRNAs and their possible biological functions.Overall,this study reports for the first time that EBOV may produce miRNAs,which could serve as non-invasive biomarkers for the diagnosis and prognosis of EBOV infection and as therapeutic targets for Ebola viral infection treatment. | LIANG HongWei ZHOU Zhen ZHANG SuYang ZEN Ke CHEN Xi ZHANG ChenYu | 2014 | Science China(Life Sciences)2014，57，10： | 5 |
| 4 | Optimal Operation of Micro-energy Grids Considering Shared Energy Storage Systems and Balanced Profit Allocations显示文摘Following the unprecedented generation of renewable energy,Energy Storage Systems(ESSs)have become essential for facilitating renewable consumption and maintaining reliability in energy networks.However,providing an individual ESS to a single customer is still a luxury.Thus,this paper aims to investigate whether the Shared-ESS can assist energy savings for multiple users through Peer-to-Peer(P2P)trading.Moreover,with the increasing number of market participants in the integrated energy system(IES),a benefit allocation scheme is necessary,ensuring reasonable benefits for every user in the network.Using the multiplayer cooperative game model,the nucleolus and the Shapley value methods are adopted to evaluate the benefit allocation between multiple users.Numerical analyses based on multiple micro-energy grids are performed,so as to assess the performance of the Shared-ESS and the proposed benefit allocation scheme.The results show that the micro-energy grid cluster can save as much as 38.15%of the total energy cost with Shared-ESS being equipped.The following conclusions can be drawn:the Shared-ESS can significantly reduce the operating costs of the micro-energy grid operator,promote the consumption of renewable energy,and play the role of peak-shaving and valley-filling during different energy usage periods.In addition,it is reflected that the multiplayer cooperative game model is effective in revealing the interaction between the micro-energy grids,which makes the distribution results more reasonable. | Hanlin Zhang Suyang Zhou Wei Gu Chengzhi Zhu X.G.Chen | 2023 | CSEE Journal of Power and Energy Systems2023，9，1： | 1 |
| 5 | Network Modeling and Operation Optimization of Electricity-HCNG-Integrated Energy System显示文摘Hydrogen-enriched compressed natural gas(HCNG)has great potential for renewable energy and hydrogen utilization.However,injecting hydrogen into the natural gas network will change original fluid dynamics and complicate compressed gas's physical properties,threatening operational safety of the electricity-HCNG-integrated energy system(E-HCNG-IES).To resolve such problem,this paper investigates effect of HCNG on gas network dynamics and presents an improved HCNG network model,which embodies the influence of blending hydrogen on the pressure drop equation and line pack equation.In addition,an optimal dispatch model for the E-HCNG-IES,considering the“production-storage-blending-transportation-utilization”link of the HCNG supply chain,is also proposed.The dispatch model is converted into a mixed-integer second-order conic programming(MISOCP)problem using the second-order cone(SOC)relaxation and piecewise linearization techniques.An iterative algorithm is proposed based on the convex-concave procedure and bound-tightening method to obtain a tight solution.Finally,the proposed methodology is evaluated through two E-HCNGIES numerical testbeds with different hydrogen volume fractions.Detailed operation analysis reveals that E-HCNG-IES can benefit from economic and environmental improvement with increased hydrogen volume fraction,despite declining energy delivery capacityand line pack flexibility. | Yue Qiu Suyang Zhou Wei Gu Yuping Lu Xiao-Ping Zhang Gaoyan Han Kang Zhang Hongkun Lyu | 2023 | CSEE Journal of Power and Energy Systems2023，9，4： | 0 |
| 6 | Mutation Breeding of Aspergillus Niger for Citric Acid Irradiated by Heavy Ion Beam显示文摘 | Chen Jihong Hu Wei Liu Jing Wang Suyang Li Wenjian Zhou Lin | 2011 | IMP & HIRFL Annual Report2011，，1： | 0 |
| 7 | Planning and Real-time Pricing of EV Charging Stations Considering Social Welfare and Profitability Balance显示文摘This paper presents a planning and real-time pricing approach for EV charging stations(CSs).The approach takes the form of a bi-level model to fully consider the interest of both the government and EV charging station operators in the planning process.From the perspective of maximizing social welfare,the government acts as the decision-maker of the upper level that optimizes the charging price matrix,and uses it as a transfer variable to indirectly influence the decisions of the lower level operators.Then each operator at the lower level determines their scale according to the goal of maximizing their own revenue,and feeds the scale matrix back to the upper level.A Logit model is applied to predict the drivers’preference when selecting a CS.Furthermore,an improved particle swarm optimization(PSO)with the utilization of a penalty function is introduced to solve the nonlinear nonconvex bi-level model.The paper applies the proposed Bi-level planning model to a singlecenter small/medium-sized city with three scenarios to evaluate its performance,including the equipment utilization rate,payback period,traffic attraction ability,etc.The result verifies that the model performs very well in typical CS distribution scenarios with a reasonable station payback period(average 6.5 years),and relatively high equipment utilization rate,44.32%. | Suyang Zhou Yuxuan Zhuang Zhi Wu Wei Gu Peng Yu Jinqiao Du Xiner Luo | 2021 | CSEE Journal of Power and Energy Systems2021，7，6： | 0 |
| 8 | Optimal Micro-PMU Placement for Improving State Estimation Accuracy via Mixed-integer Semidefinite Programming显示文摘Micro-phasor measurement units(μPMUs)with a micro-second resolution and milli-degree accuracy capability are expected to play an important role in improving the state estimation accuracy in the distribution network with increasing penetration of distributed generations.Therefore,this paper investigates the problem of how to place a limited number ofμPMUs to improve the state estimation accuracy.Combined with pseudo-measurements and supervisory control and data acquisition(SCADA)measurements,an optimalμPMU placement model is proposed based on a two-step state estimation method.The E-optimal experimental criterion is utilized to measure the state estimation accuracy.The nonlinear optimization problem is transformed into a mixed-integer semidefinite programming(MISDP)problem,whose optimal solution can be obtained by using the improved Benders decomposition method.Simulations on several systems are carried out to evaluate the effective performance of the proposed model. | Yang Peng Zhi Wu Wei Gu Suyang Zhou Pengxiang Liu | 2023 | Journal of Modern Power Systems and Clean Energy2023，11，2： | 0 |
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