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Chuanwen Jiang
Electrical Engineering, Shanghai Jiao Tong University, 12474 Shanghai, China

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Journal article
Published: 17 May 2021 in IEEE Transactions on Sustainable Energy
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Hybrid AC/DC microgrids allow the integration of diverse renewable energy resources. However, the security and the reliability of hybrid AC/DC microgrid systems are challenged by various contingencies. In this paper, we propose a BESS sizing and siting approach which uses a combined stochastic programming and robust optimization method to cope with uncertainties of loads, wind power generation, and BESS charging/discharging efficiency. The proposed iterative solution enhances voltage and frequency regulation performances in an islanded hybrid AC/DC microgrid which is subject to post-contingency corrective rescheduling. A successive linear power flow approximation method is adopted to simulate post-fault power flows and represent static frequency characteristics of loads and generators. The proposed iterative solution for the mixed-integer linear programming (MILP) formulation can achieve computational tractability for determining pre-fault and post-fault initial operation points. Case studies corroborate the effectiveness of the proposed model and the solution method.

ACS Style

Kai Gong; Xu Wang; Chuanwen Jiang; Mohammad Shahidehpour; Xiaolin Liu; Zean Zhu. Security-Constrained Optimal Sizing and Siting of BESS in Hybrid AC/DC Microgrid Considering Post-Contingency Corrective Rescheduling. IEEE Transactions on Sustainable Energy 2021, PP, 1 -1.

AMA Style

Kai Gong, Xu Wang, Chuanwen Jiang, Mohammad Shahidehpour, Xiaolin Liu, Zean Zhu. Security-Constrained Optimal Sizing and Siting of BESS in Hybrid AC/DC Microgrid Considering Post-Contingency Corrective Rescheduling. IEEE Transactions on Sustainable Energy. 2021; PP (99):1-1.

Chicago/Turabian Style

Kai Gong; Xu Wang; Chuanwen Jiang; Mohammad Shahidehpour; Xiaolin Liu; Zean Zhu. 2021. "Security-Constrained Optimal Sizing and Siting of BESS in Hybrid AC/DC Microgrid Considering Post-Contingency Corrective Rescheduling." IEEE Transactions on Sustainable Energy PP, no. 99: 1-1.

Conference paper
Published: 10 May 2021 in E3S Web of Conferences
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Integrated energy system (IES) is an effective way to realize the efficient utilization of energy. Under the deregulated electricity market, IES operator gains profits by providing customers with energy service, including electricity, heat or cooling energy. With the deepening of market reform, higher penetration rate of renewable energy, economic risks embed in the IES. Based on this, an optimal scheduling model of regional IES considering uncertainties is proposed, aiming at maximizing the profits. Scenario analysis method has been adopted to model the uncertainties: Markov-Chain-Monte-Carlo (MCMC) sampling method, which has a better performance in fitting the probability distribution, is utilized to generate scenarios; K-means clustering method is applied to narrow down the sampling sets. By replacing the parameters in the deterministic model with the sampling sets, a series of optimal results can be achieved. The case study shows that the cooling storage tank can improve the economic benefits about 4.97% by converting electricity to cooling energy at lower price period and releasing energy at peak hours. Besides, through the proposed optimization model, operators can have a straight understanding of the venture brought by the uncertainties and a more reliable scheduling result is formed for reference.

ACS Style

Shufeng Guan; Lingling Wang; Chuanwen Jiang. Optimal scheduling of regional integrated energy system considering multiple uncertainties. E3S Web of Conferences 2021, 256, 02027 .

AMA Style

Shufeng Guan, Lingling Wang, Chuanwen Jiang. Optimal scheduling of regional integrated energy system considering multiple uncertainties. E3S Web of Conferences. 2021; 256 ():02027.

Chicago/Turabian Style

Shufeng Guan; Lingling Wang; Chuanwen Jiang. 2021. "Optimal scheduling of regional integrated energy system considering multiple uncertainties." E3S Web of Conferences 256, no. : 02027.

Journal article
Published: 25 September 2019 in Energies
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A virtual power plant is proposed to aggregate various distributed renewable resources with controllable resources to overcome the uncertainty and volatility of the renewables so as to improve market involvement. As the virtual power plant capacity becomes remarkable, it behaves as a strategic price maker rather than price taker in the market for higher profit. In this work, a two-stage bi-level bidding and scheduling model is proposed to study the virtual power plant strategic behaviors as a price maker. A mathematical problem with an equilibrium constraints-based method is applied to solve the problem by transforming the two level problem into a single level multi-integer linear problem. Considering the deficiency of computational burden and implausible assumptions of conventional stochastic optimization, we introduce interval numbers to represent the predicted output of uncertainty resources in a real-time stage. The pessimism degree-based method is utilized to order the preferences of profit intervals and tradeoff between expected profit and uncertainty. An imbalance cost mitigation mechanism is proposed in this pessimism degree-based interval optimization manner. Results show that the bidding price directly affects the cleared day ahead of the locational marginal price for higher profit. Interior conventional generators, energy storage and interruptible loads are comprehensively optimized to cover potential power shortage or profit from market. Moreover, controllable resources can decrease or even wipe out the uncertainty through the imbalance cost mitigation mechanism when the negative deviation charge is high. Finally, a sensitivity analysis reveals the effect of interval parameter setting upon optimization results. Moreover, a virtual power plant operator with a higher pessimism degree pursues higher profit with higher uncertainty.

ACS Style

Jiakai Hu; Chuanwen Jiang; Yangyang Liu. Short-Term Bidding Strategy for a Price-Maker Virtual Power Plant Based on Interval Optimization. Energies 2019, 12, 3662 .

AMA Style

Jiakai Hu, Chuanwen Jiang, Yangyang Liu. Short-Term Bidding Strategy for a Price-Maker Virtual Power Plant Based on Interval Optimization. Energies. 2019; 12 (19):3662.

Chicago/Turabian Style

Jiakai Hu; Chuanwen Jiang; Yangyang Liu. 2019. "Short-Term Bidding Strategy for a Price-Maker Virtual Power Plant Based on Interval Optimization." Energies 12, no. 19: 3662.

Journal article
Published: 23 April 2019 in Energies
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Capable of aggregating multiple energy resources, the energy service company (ESCO) has been regarded as a promising alternative for improving power system flexibility and facilitate the consumption of renewable resources in the energy market. However, the issues have become significantly more serious related to the privacy and security of the data in consumption and trading. In this paper, we address the problem by proposing a privacy-preserving energy scheduling (PPES) model based on energy blockchain network. A Lagrangian relaxation method is applied to decompose the model into several individual optimal scheduling problems, and the individual scheduling problems are solved by consensus algorithm and smart contracts in energy blockchain network. The performance of the proposed model and method is evaluated with several case studies based on multiple energy nodes. Simulation results show the rationality and validity of the proposed method, and the model is conducive to the protection of environment and transparent scheduling of energy service companies (ESCOs). In addition, it can reflect the information of energy demand and supply to improve the privacy and security of data.

ACS Style

Shengmin Tan; Xu Wang; Chuanwen Jiang. Privacy-Preserving Energy Scheduling for ESCOs Based on Energy Blockchain Network. Energies 2019, 12, 1530 .

AMA Style

Shengmin Tan, Xu Wang, Chuanwen Jiang. Privacy-Preserving Energy Scheduling for ESCOs Based on Energy Blockchain Network. Energies. 2019; 12 (8):1530.

Chicago/Turabian Style

Shengmin Tan; Xu Wang; Chuanwen Jiang. 2019. "Privacy-Preserving Energy Scheduling for ESCOs Based on Energy Blockchain Network." Energies 12, no. 8: 1530.

Journal article
Published: 18 March 2019 in Applied Sciences
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This paper proposes a coordinated active–reactive power optimization model for an active distribution network with energy storage systems, where the active and reactive resources are handled simultaneously. The model aims to minimize the power losses, the operation cost, and the voltage deviation of the distribution network. In particular, the reactive power capabilities of distributed generators and energy storage systems are fully utilized to minimize power losses and improve voltage profiles. The uncertainties pertaining to the forecasted values of renewable energy sources are modelled by scenario-based stochastic programming. The second-order cone programming relaxation method is used to deal with the nonlinear power flow constraints and transform the original mixed integer nonlinear programming problem into a tractable mixed integer second-order cone programming model, thus the difficulty of problem solving is significantly reduced. The 33-bus and 69-bus distribution networks are used to demonstrate the effectiveness of the proposed approach. Simulation results show that the proposed coordinated optimization approach helps improve the economic operation for active distribution network while improving the system security significantly.

ACS Style

Lingling Wang; Xu Wang; Chuanwen Jiang; Shuo Yin; Meng Yang. Dynamic Coordinated Active–Reactive Power Optimization for Active Distribution Network with Energy Storage Systems. Applied Sciences 2019, 9, 1129 .

AMA Style

Lingling Wang, Xu Wang, Chuanwen Jiang, Shuo Yin, Meng Yang. Dynamic Coordinated Active–Reactive Power Optimization for Active Distribution Network with Energy Storage Systems. Applied Sciences. 2019; 9 (6):1129.

Chicago/Turabian Style

Lingling Wang; Xu Wang; Chuanwen Jiang; Shuo Yin; Meng Yang. 2019. "Dynamic Coordinated Active–Reactive Power Optimization for Active Distribution Network with Energy Storage Systems." Applied Sciences 9, no. 6: 1129.

Journal article
Published: 02 March 2019 in Applied Sciences
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Coordination of a hydropower, combined heat and power (CHP), and battery energy storage system (BESS) with multiple renewable energy sources (RES) can effectively reduce the adverse effects of large-scale renewable energy integration in power systems. This paper proposes a concept of a renewable-based hybrid energy system and puts forward an optimal scheduling model of this system, taking into account the cost of operation and risk. An optimization method is proposed based on Latin hypercube sampling, scene reduction, and piecewise linearization. Firstly, a large number of samples were generated with the Latin hypercube sampling method according to the uncertainties, including the renewable resources availability, the load demand, and the risk aversion coefficients, and the generated samples were reduced with a scene reduction method. Secondly, the piecewise linearization method was applied to convert nonlinear constraints into linear to obtain the best results of each scene. Finally, the performance of the proposed model and method was evaluated based on case studies with real-life data. Results showed that the renewable-based hybrid system can not only reduce the intermittent and volatility of renewable resources but also ensure the smooth of tie-line power as much as possible. The proposed model and method are universal, feasible, and effective.

ACS Style

Shengmin Tan; Xu Wang; Chuanwen Jiang. Optimal Scheduling of Hydro–PV–Wind Hybrid System Considering CHP and BESS Coordination. Applied Sciences 2019, 9, 892 .

AMA Style

Shengmin Tan, Xu Wang, Chuanwen Jiang. Optimal Scheduling of Hydro–PV–Wind Hybrid System Considering CHP and BESS Coordination. Applied Sciences. 2019; 9 (5):892.

Chicago/Turabian Style

Shengmin Tan; Xu Wang; Chuanwen Jiang. 2019. "Optimal Scheduling of Hydro–PV–Wind Hybrid System Considering CHP and BESS Coordination." Applied Sciences 9, no. 5: 892.

Journal article
Published: 01 November 2018 in International Journal of Electrical Power & Energy Systems
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Virtual power plant (VPP) technology is a promising solution to manage the uncertainties of renewable energy in demand side. Because of various uncertainties, VPPs’ dispatch models are always solved by stochastic optimization, robust optimization and interval optimization. However, these approaches always require high computational complexity, be over conservative or cannot describe VPPs’ profitability precisely. Thus, this paper combined interval and deterministic optimization together and adopted the combined approach to solve a VPP’s dispatch problem. The combined optimization not only maximized VPPs’ deterministic profits under forecasted scenarios to estimate the VPP’s most likely profits, but also maximized VPPs’ profit intervals to manage uncertainties. The proposed model was in a regulated electricity market environment, and the VPP’s traded energy was cleared by time-of-use prices. A case study from real world was adopted to prove the validity of this model. Comparison with other optimizations like stochastic and robust optimization was also studied. The combined optimization can manage the VPP’s uncertainties within limited computational time.

ACS Style

Yangyang Liu; Min Li; Hongbo Lian; Xiaowei Tang; Chuanquan Liu; Chuanwen Jiang. Optimal dispatch of virtual power plant using interval and deterministic combined optimization. International Journal of Electrical Power & Energy Systems 2018, 102, 235 -244.

AMA Style

Yangyang Liu, Min Li, Hongbo Lian, Xiaowei Tang, Chuanquan Liu, Chuanwen Jiang. Optimal dispatch of virtual power plant using interval and deterministic combined optimization. International Journal of Electrical Power & Energy Systems. 2018; 102 ():235-244.

Chicago/Turabian Style

Yangyang Liu; Min Li; Hongbo Lian; Xiaowei Tang; Chuanquan Liu; Chuanwen Jiang. 2018. "Optimal dispatch of virtual power plant using interval and deterministic combined optimization." International Journal of Electrical Power & Energy Systems 102, no. : 235-244.

Journal article
Published: 01 September 2018 in Renewable Energy
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ACS Style

Xu Wang; Chuanwen Jiang; Bosong Li. Retraction notice to “Active robust optimization for wind integrated power system economic dispatch considering hourly demand response” [Renew. Energy 97 (2016) 798–808]. Renewable Energy 2018, 125, 1061 .

AMA Style

Xu Wang, Chuanwen Jiang, Bosong Li. Retraction notice to “Active robust optimization for wind integrated power system economic dispatch considering hourly demand response” [Renew. Energy 97 (2016) 798–808]. Renewable Energy. 2018; 125 ():1061.

Chicago/Turabian Style

Xu Wang; Chuanwen Jiang; Bosong Li. 2018. "Retraction notice to “Active robust optimization for wind integrated power system economic dispatch considering hourly demand response” [Renew. Energy 97 (2016) 798–808]." Renewable Energy 125, no. : 1061.

Paper
Published: 06 June 2018 in IEEJ Transactions on Electrical and Electronic Engineering
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Virtual power plant (VPP) aggregates distributed energy resources (DER) as a single profile to overcome scale disadvantage and dispersed characteristics. A commercial virtual power plant (CVPP) especially operates to improve the power‐market involvement. In this article, the CVPP medium‐term bidding strategy is optimized to obtain the profit interval mostly preferred by the CVPP's decision maker. Because the medium‐term forecast of renewable power generation and day ahead (DA) market price is far more difficult than short term, interval optimization is proposed, which does not require uncertain variable‐distribution assumption. The pessimism degree is introduced to quantify the decision maker's risk acceptance and compare intervals so as to solve the interval‐optimization model. Within the interval‐optimization framework, the bidding strategy between the bilateral contract (BC) and the DA market is figured out. A combined DA market deal and gas turbine generator strategy is proposed to cope with power shortage. Finally, an in‐depth sensitivity analysis is applied, and the characteristics and caution of interval optimization are deduced. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

ACS Style

Jiakai Hu; Yangyang Liu; Chuanwen Jiang. An optimum bidding strategy of CVPP by interval optimization. IEEJ Transactions on Electrical and Electronic Engineering 2018, 13, 1568 -1577.

AMA Style

Jiakai Hu, Yangyang Liu, Chuanwen Jiang. An optimum bidding strategy of CVPP by interval optimization. IEEJ Transactions on Electrical and Electronic Engineering. 2018; 13 (11):1568-1577.

Chicago/Turabian Style

Jiakai Hu; Yangyang Liu; Chuanwen Jiang. 2018. "An optimum bidding strategy of CVPP by interval optimization." IEEJ Transactions on Electrical and Electronic Engineering 13, no. 11: 1568-1577.

Article
Published: 16 January 2018 in IEEJ Transactions on Electrical and Electronic Engineering
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The vast potential of demand-side resources (DSR)—including flexible loads and distributed energy resources—in the optimal operation of a power system is being increasingly recognized. Such potential can be fully realized through the access of a DSR aggregator to the power market. In this paper, a DSR aggregator is introduced for the collective management of DSRs in the power system. A bi-level optimization model consisting of power market clearing and DSR aggregator internal scheduling is formulated and solved through stochastic programing. A thorough evaluation of the DSR aggregator's performance under three different operation modes, namely energy consumer mode, energy prosumer mode, and eco-friendliness mode, is carried out to study its influence on system operation concerning social welfare, system purchase cost, carbon emission, and so on. Simulation results show that even though DSR acquires a segment of the market social welfare, it brings in benefits in economic and environmental operation of the system and contributes to DSR uncertainty alleviation.

ACS Style

Bosong Li; Chuanwen Jiang; Gao Zhang; Yang He. Management and performance evaluation of DSR aggregator based on a bi-level optimization model. IEEJ Transactions on Electrical and Electronic Engineering 2018, 13, 432 -441.

AMA Style

Bosong Li, Chuanwen Jiang, Gao Zhang, Yang He. Management and performance evaluation of DSR aggregator based on a bi-level optimization model. IEEJ Transactions on Electrical and Electronic Engineering. 2018; 13 (3):432-441.

Chicago/Turabian Style

Bosong Li; Chuanwen Jiang; Gao Zhang; Yang He. 2018. "Management and performance evaluation of DSR aggregator based on a bi-level optimization model." IEEJ Transactions on Electrical and Electronic Engineering 13, no. 3: 432-441.

Journal article
Published: 01 January 2018 in Renewable Energy
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ACS Style

Gaiping Sun; Chuanwen Jiang; Pan Cheng; Yangyang Liu; Xu Wang; Yang Fu; Yang He. Short-term wind power forecasts by a synthetical similar time series data mining method. Renewable Energy 2018, 115, 575 -584.

AMA Style

Gaiping Sun, Chuanwen Jiang, Pan Cheng, Yangyang Liu, Xu Wang, Yang Fu, Yang He. Short-term wind power forecasts by a synthetical similar time series data mining method. Renewable Energy. 2018; 115 ():575-584.

Chicago/Turabian Style

Gaiping Sun; Chuanwen Jiang; Pan Cheng; Yangyang Liu; Xu Wang; Yang Fu; Yang He. 2018. "Short-term wind power forecasts by a synthetical similar time series data mining method." Renewable Energy 115, no. : 575-584.

Article
Published: 01 November 2017 in Journal of Modern Power Systems and Clean Energy
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With the large-scale development of distributed generations (DGs) and the connection into the main grid of active distribution networks (ADNs), traditional centralized dispatch of power system has encountered enormous challenge. In a bilateral electricity market, introducing ADN resources in the day-ahead generation schedule will not only enrich the dispatch patterns to the power system, but also reflect the initiative of ADNs. This paper proposes a coordinated scheduling model of power system with a plurality of ADNs based on multi-agent system where ADN agents are brought in the day-ahead market clearing. The process of market clearing and the dispatch of DGs in ADNs are independent with each other but linked together through the market clearing price (MCP) and bid volume. The optimal operating point of the whole system is achieved through multiple information exchange. In comparison with the dispatch without interaction between ADNs and the market operator (MO), the coordinated scheduling model is applied in a system with four ADNs to verify that the proposed method can improve the overall interests of ADNs. Finally, the effects of storage device and tie-line power limit are analyzed.

ACS Style

Jingzhe Hu; Hao Cong; Chuanwen Jiang. Coordinated scheduling model of power system with active distribution networks based on multi-agent system. Journal of Modern Power Systems and Clean Energy 2017, 6, 521 -531.

AMA Style

Jingzhe Hu, Hao Cong, Chuanwen Jiang. Coordinated scheduling model of power system with active distribution networks based on multi-agent system. Journal of Modern Power Systems and Clean Energy. 2017; 6 (3):521-531.

Chicago/Turabian Style

Jingzhe Hu; Hao Cong; Chuanwen Jiang. 2017. "Coordinated scheduling model of power system with active distribution networks based on multi-agent system." Journal of Modern Power Systems and Clean Energy 6, no. 3: 521-531.

Article
Published: 23 August 2017 in IEEJ Transactions on Electrical and Electronic Engineering
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Involvement of active distribution networks (ADNs) in emission management can give full play to the carbon-reduction potential of distributed generations (DGs) and demand response. With the development of smart grid, low-carbon coordinated scheduling of power system with ADNs will become a new trend. A bilevel dispatch model based on locational marginal emission (LME) is proposed to achieve carbon reduction from both generation and load sides. The main grid dispatch is a problem of dynamic optimal power flow aiming at reducing both the operating and emission costs, in which LME under AC condition is adopted to calculate the carbon emission produced by node power. The ADN level is the DG generation schedule with the objective of minimizing both the cost and system emission based on LME. The main grid and ADNs interact and cooperate with each other by locational marginal price (LMP) and LME to cut the carbon pollution. Simulation results in a modified IEEE 30-bus system and an IEEE 118-bus system show that compared with the traditional LMP-based coordinated scheduling, the bilevel dispatch model based on LME can reduce carbon emission effectively and promote ADNs' participation in system carbon emission management. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

ACS Style

Jingzhe Hu; Hao Cong; Chuanwen Jiang; Yang He. A low-carbon dispatch of power system incorporating active distribution networks based on locational marginal emission. IEEJ Transactions on Electrical and Electronic Engineering 2017, 13, 38 -46.

AMA Style

Jingzhe Hu, Hao Cong, Chuanwen Jiang, Yang He. A low-carbon dispatch of power system incorporating active distribution networks based on locational marginal emission. IEEJ Transactions on Electrical and Electronic Engineering. 2017; 13 (1):38-46.

Chicago/Turabian Style

Jingzhe Hu; Hao Cong; Chuanwen Jiang; Yang He. 2017. "A low-carbon dispatch of power system incorporating active distribution networks based on locational marginal emission." IEEJ Transactions on Electrical and Electronic Engineering 13, no. 1: 38-46.

Research article
Published: 24 July 2017 in IET Generation, Transmission & Distribution
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Due to the gradual exhaustion of petroleum-based energy resources and severe concern for environmental protection, renewable energy (RE) resources and demand response (DR) techniques have been wide deployed in power network. However, the insufficient management as well as technology bottleneck becomes the major obstacle in their further development. Based on the uniform clearing of electricity market, a centralised dispatch model of virtual power plant (VPP) is introduced to improve the competitiveness of distributed energy resources in electricity market. To neutralise the side effect of RE penetration, a bidding strategy optimisation model considering DR and the uncertainty of RE for VPP is proposed and numerical analysis is conducted to prove its applicability. In addition, scenario analysis method is applied to deal with the influence of elastic demand and potential risk, which are associated with utility users’ consumption patterns and VPP's bidding preference, respectively. The application of distributed algorithm into multi-players’ strategy optimisation problem accelerated the convergence of bidding procedure, which verifies the applicability and effectiveness of the proposed models. Furthermore, numerical case studies demonstrate the distinctive superiority of VPP in the integration and management of RE and DR resources, which in turn contribute to its advantage position in electricity market.

ACS Style

Gao Zhang; Chuanwen Jiang; Xu Wang; Bosong Li; Huagang Zhu. Bidding strategy analysis of virtual power plant considering demand response and uncertainty of renewable energy. IET Generation, Transmission & Distribution 2017, 11, 3268 -3277.

AMA Style

Gao Zhang, Chuanwen Jiang, Xu Wang, Bosong Li, Huagang Zhu. Bidding strategy analysis of virtual power plant considering demand response and uncertainty of renewable energy. IET Generation, Transmission & Distribution. 2017; 11 (13):3268-3277.

Chicago/Turabian Style

Gao Zhang; Chuanwen Jiang; Xu Wang; Bosong Li; Huagang Zhu. 2017. "Bidding strategy analysis of virtual power plant considering demand response and uncertainty of renewable energy." IET Generation, Transmission & Distribution 11, no. 13: 3268-3277.

Article
Published: 03 February 2017 in IEEJ Transactions on Electrical and Electronic Engineering
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Aiming at the effective management of distributed energy resources (DERs), we propose a bi-level optimization dispatch model which consists of a virtual power plant (VPP) and an independent system operator (ISO) in order to achieve a coordinated dispatch between the upper level objective function of minimizing system's operation cost and the lower level objective function of maximizing the VPP's net profit. However, the VPP's dispatch strategy is variable due to the threat from unavoidable uncertainties including unit outage, load forecast deviation, and renewable energy forecasting error. In order to evaluate the influences of these risks on VPP's dispatch strategy, a proper definition of expected energy not supplied (EENS) and its relationship with VPP's reserve capacity are provided. Also, chance-constrained programming (CCP) is adopted during the analysis. By including VPP's risk cost into the dispatch model, VPP's dispatch strategy is able to keep a balance between the potential risk and economic profit. In addition, a further discussion regarding the risk cost is conducted in view of renewable energy capacity proportion and the VPP capacity proportion. Based on the analysis results of the case study provided, the proposed model serves as a foundation for VPP's economic and risk-balanced dispatch.

ACS Style

Gao Zhang; Chuanwen Jiang; Xu Wang; Bosong Li. Risk assessment and bi-level optimization dispatch of virtual power plants considering renewable energy uncertainty. IEEJ Transactions on Electrical and Electronic Engineering 2017, 12, 510 -518.

AMA Style

Gao Zhang, Chuanwen Jiang, Xu Wang, Bosong Li. Risk assessment and bi-level optimization dispatch of virtual power plants considering renewable energy uncertainty. IEEJ Transactions on Electrical and Electronic Engineering. 2017; 12 (4):510-518.

Chicago/Turabian Style

Gao Zhang; Chuanwen Jiang; Xu Wang; Bosong Li. 2017. "Risk assessment and bi-level optimization dispatch of virtual power plants considering renewable energy uncertainty." IEEJ Transactions on Electrical and Electronic Engineering 12, no. 4: 510-518.

Journal article
Published: 05 December 2016 in IET Renewable Power Generation
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Coordination of hydropower with multiple renewable sources can effectively reduce the adverse effects of large-scale renewable energy integration in power systems. A yearly scheduling model was proposed for a hydro-photovoltaic (PV)-wind hybrid system, maximising its generation interval and considering firm generation limits. Firm generation ensures reliable monthly generation and reduces generation fluctuations. Because the probability distributions of wind power, water inflow and solar radiation are difficult to predict precisely, interval optimisation is employed to solve this problem by considering only the possible intervals of random variables. It reduces errors introduced by distribution assumptions, acquires possible generation intervals and reduces computation burden. To handle the scheduling model using intervals, a pessimistic preference ordering of interval numbers is employed. The proposed interval optimal scheduling model is illustrated and analysed for a realistic case study in Yunnan.

ACS Style

Yangyang Liu; Shengmin Tan; Chuanwen Jiang. Interval optimal scheduling of hydro‐PV‐wind hybrid system considering firm generation coordination. IET Renewable Power Generation 2016, 11, 63 -72.

AMA Style

Yangyang Liu, Shengmin Tan, Chuanwen Jiang. Interval optimal scheduling of hydro‐PV‐wind hybrid system considering firm generation coordination. IET Renewable Power Generation. 2016; 11 (1):63-72.

Chicago/Turabian Style

Yangyang Liu; Shengmin Tan; Chuanwen Jiang. 2016. "Interval optimal scheduling of hydro‐PV‐wind hybrid system considering firm generation coordination." IET Renewable Power Generation 11, no. 1: 63-72.

Journal article
Published: 21 June 2016 in Electric Power Components and Systems
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ACS Style

Xu Wang; Chuanwen Jiang. Congestion Management in Modern Power System Containing Active Distribution Network Nodes. Electric Power Components and Systems 2016, 44, 1453 -1465.

AMA Style

Xu Wang, Chuanwen Jiang. Congestion Management in Modern Power System Containing Active Distribution Network Nodes. Electric Power Components and Systems. 2016; 44 (13):1453-1465.

Chicago/Turabian Style

Xu Wang; Chuanwen Jiang. 2016. "Congestion Management in Modern Power System Containing Active Distribution Network Nodes." Electric Power Components and Systems 44, no. 13: 1453-1465.

Original articles
Published: 08 April 2016 in Electric Power Components and Systems
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A microgrid that consists of distributed energy sources, such as micro turbines, wind turbines, fuel cells, and photovoltaic panels, storage devices and a group of radial load feeders are quickly rising in popularity in recent years. Because there are various controllable units in a microgrid, it has the potential to provide ancillary services (A/Ss) for the grid in the grid-connected mode. This article proposes a novel microgrid energy management strategy with demand response to provide peak shaving for the grid by using the peak-time rebate scheme. Under this scheme, various controllable units, such as controllable loads, battery storage, and diesel generators, participate voluntarily in the demand-response program to achieve maximum profit for the microgrid, so the microgrid can respond actively to the grid. The optimal energy management for the microgrid is achieved under this scheme. In addition, the main grid can benefit from the scheme with a lower cost compared with other traditional peak-shaving programs. Various incentive rewards of the peak-time rebate and demand-response levels of the controllable loads are discussed in the peak-time rebate scheme. The results demonstrate that the peak power of the grid tie-line is shaved markedly while achieving optimal energy management.

ACS Style

Jingshuang Shen; Chuanwen Jiang; Yangyang Liu; Jie Qian. A Microgrid Energy Management System with Demand Response for Providing Grid Peak Shaving. Electric Power Components and Systems 2016, 44, 843 -852.

AMA Style

Jingshuang Shen, Chuanwen Jiang, Yangyang Liu, Jie Qian. A Microgrid Energy Management System with Demand Response for Providing Grid Peak Shaving. Electric Power Components and Systems. 2016; 44 (8):843-852.

Chicago/Turabian Style

Jingshuang Shen; Chuanwen Jiang; Yangyang Liu; Jie Qian. 2016. "A Microgrid Energy Management System with Demand Response for Providing Grid Peak Shaving." Electric Power Components and Systems 44, no. 8: 843-852.

Journal article
Published: 23 March 2016 in International Transactions on Electrical Energy Systems
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This paper presents a novel multi-objective energy management method for a microgrid that includes renewable energy, diesel generators, battery storage, and various loads. The fluctuation of the grid tie-line power flow is regarded as one of the optimal objectives in order to decrease the power exchange between the microgrid and the main grid caused by intermittent and variable renewable resources. The uncertainty of renewable energy and loads is also considered in this paper. Stochastic optimization method is implemented for the output of renewable resources and controllable loads. Using the ε-constrained and weighted sum method, the multi-objective operation optimization problem, which includes the minimum microgrid operation costs, fluctuations of the grid tie-line power, and the risk management, is converted to a single-objective mixed-integer linear optimization problem. The scheduling is achieved for controllable units such as diesel generators, batteries, controllable loads, and grid tie-line power under various weights. The main contribution of the study is to achieve the energy management for a microgrid with regulation of the grid tie-line power fluctuations and peak shaving. Copyright © 2016 John Wiley & Sons, Ltd.

ACS Style

Jingshuang Shen; Chuanwen Jiang; Yangyang Liu; Xu Wang; Jie Qian. Microgrid operation optimization with regulation of grid tie-line power fluctuations and risk management. International Transactions on Electrical Energy Systems 2016, 26, 2308 -2321.

AMA Style

Jingshuang Shen, Chuanwen Jiang, Yangyang Liu, Xu Wang, Jie Qian. Microgrid operation optimization with regulation of grid tie-line power fluctuations and risk management. International Transactions on Electrical Energy Systems. 2016; 26 (11):2308-2321.

Chicago/Turabian Style

Jingshuang Shen; Chuanwen Jiang; Yangyang Liu; Xu Wang; Jie Qian. 2016. "Microgrid operation optimization with regulation of grid tie-line power fluctuations and risk management." International Transactions on Electrical Energy Systems 26, no. 11: 2308-2321.

Journal article
Published: 18 February 2016 in Journal of Modern Power Systems and Clean Energy
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Initial allocation modes and schemes are studied in this paper to provide guidelines for allocation of carbon emission permits in power system. We first introduce different allocation modes and the need to apply free allocation to assignability of emission permits. Then, we compare two different allocation schemes, which are based on historical emissions and generation performance standard. Further, a new allocation scheme based on Boltzmann distribution is proposed. Finally, a case study on Shanghai power grid in China is conducted to compare the allocation effects of these schemes respectively. The analytical results show that Boltzmann distribution based scheme has the best performance and should be adopted when developing initial allocation of carbon emission permits in Chinese power systems.

ACS Style

Tan Wang; Xu Wang; Yu Gong; Chuanwen Jiang; Fengjia Xiong; Lei Li; Yan Zhao. Initial allocation of carbon emission permits in power systems. Journal of Modern Power Systems and Clean Energy 2016, 5, 239 -247.

AMA Style

Tan Wang, Xu Wang, Yu Gong, Chuanwen Jiang, Fengjia Xiong, Lei Li, Yan Zhao. Initial allocation of carbon emission permits in power systems. Journal of Modern Power Systems and Clean Energy. 2016; 5 (2):239-247.

Chicago/Turabian Style

Tan Wang; Xu Wang; Yu Gong; Chuanwen Jiang; Fengjia Xiong; Lei Li; Yan Zhao. 2016. "Initial allocation of carbon emission permits in power systems." Journal of Modern Power Systems and Clean Energy 5, no. 2: 239-247.