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Sheng Chen
College of Energy and Electrical Engineering, Hohai University, 12462 Nanjing, China, 210098

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Journal article
Published: 17 March 2021 in IEEE Transactions on Power Systems
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We study the equilibria reached in electricity, natural-gas, and carbon-emission markets, where power producers simultaneously participate in these three markets. We use a conjectural-variations equilibrium model to represent both electricity and natural-gas markets, in which power/natural gas-producers play a quantity game and adjust their production decisions in reaction to the production levels of their rivals. We use a cap-and-trade mechanism to model the carbon-emission market. We develop a direct approach to identify equilibria involving the three markets, in which the optimality conditions of all players and market clearing conditions are gathered and solved jointly. Numerical results from two test systems illustrate the impact of carbon-emission trading and transmission constraints on the equilibria reached. Additionally, we compare equilibrium results under different types of competition.

ACS Style

Sheng Chen; Antonio J. Conejo; Zhinong Wei. Conjectural-Variations Equilibria in Electricity, Natural-Gas, and Carbon-Emission Markets. IEEE Transactions on Power Systems 2021, 36, 4161 -4171.

AMA Style

Sheng Chen, Antonio J. Conejo, Zhinong Wei. Conjectural-Variations Equilibria in Electricity, Natural-Gas, and Carbon-Emission Markets. IEEE Transactions on Power Systems. 2021; 36 (5):4161-4171.

Chicago/Turabian Style

Sheng Chen; Antonio J. Conejo; Zhinong Wei. 2021. "Conjectural-Variations Equilibria in Electricity, Natural-Gas, and Carbon-Emission Markets." IEEE Transactions on Power Systems 36, no. 5: 4161-4171.

Journal article
Published: 06 January 2021 in IEEE Transactions on Power Systems
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Extreme weather events pose a serious threat to energy distribution systems. We propose a distributionally robust optimization model for the resilient operation of the integrated electricity and heat energy distribution systems in extreme weather events. We develop a strengthened ambiguity set that incorporates both moment and Wasserstein metric information of uncertain contingencies, which provides a more accurate characterization of the true probability distribution. We first recast the proposed model into an equivalent framework which is similar to a conventional two-stage robust model and then utilize a modified column-and-constraint generation algorithm to solve the proposed model. Numerical results from two test systems validate the enhanced resilience of the proposed distributionally robust approach, the reduction in conservatism of the strengthened ambiguity set, and the computational efficiency of the proposed solution algorithm.

ACS Style

Yizhou Zhou; Zhinong Wei; Mohammad Shahidehpour; Sheng Chen. Distributionally Robust Resilient Operation of Integrated Energy Systems Using Moment and Wasserstein Metric for Contingencies. IEEE Transactions on Power Systems 2021, 36, 3574 -3584.

AMA Style

Yizhou Zhou, Zhinong Wei, Mohammad Shahidehpour, Sheng Chen. Distributionally Robust Resilient Operation of Integrated Energy Systems Using Moment and Wasserstein Metric for Contingencies. IEEE Transactions on Power Systems. 2021; 36 (4):3574-3584.

Chicago/Turabian Style

Yizhou Zhou; Zhinong Wei; Mohammad Shahidehpour; Sheng Chen. 2021. "Distributionally Robust Resilient Operation of Integrated Energy Systems Using Moment and Wasserstein Metric for Contingencies." IEEE Transactions on Power Systems 36, no. 4: 3574-3584.

Journal article
Published: 13 November 2020 in International Journal of Electrical Power & Energy Systems
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Regional electric power and natural gas systems have become increasingly interdependent in recent years, and have become subject to increasing supply and demand uncertainties associated with renewable energy sources. The present work addresses these issues by developing a multi-stage risk-averse operation model at the level of a regional integrated energy system that considers integrated demand response. Specifically, the developed multi-stage operation model can make flexible wait-and-see decisions, which are adaptive to newly observed uncertainties in the output of renewable energy sources, and the conditional value at risk approach is employed to achieve an economic operating cost at a given risk level. As a result, the multi-stage decision model outperforms conventional two-stage decision models in terms of operating costs. Test results indicate that the operation cost of the multi-stage operation model is reduced by 4.2% compared with a regular two-stage operation model. The impact of congestion in both the electricity and natural gas networks on system operations and energy prices is also investigated.

ACS Style

Guoqiang Sun; Jinghong Sun; Sheng Chen; Zhinong Wei. Multi-stage risk-averse operation of integrated electric power and natural gas systems. International Journal of Electrical Power & Energy Systems 2020, 126, 106614 .

AMA Style

Guoqiang Sun, Jinghong Sun, Sheng Chen, Zhinong Wei. Multi-stage risk-averse operation of integrated electric power and natural gas systems. International Journal of Electrical Power & Energy Systems. 2020; 126 ():106614.

Chicago/Turabian Style

Guoqiang Sun; Jinghong Sun; Sheng Chen; Zhinong Wei. 2020. "Multi-stage risk-averse operation of integrated electric power and natural gas systems." International Journal of Electrical Power & Energy Systems 126, no. : 106614.

Journal article
Published: 21 July 2020 in Electric Power Systems Research
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The urgent need for low-carbon societies calls for efficient energy management of smart buildings. This paper proposes a two-stage conditional value-at-risk (CVaR) model to determine the optimal day-ahead dispatch of smart buildings with heating, ventilation, and air-conditioning (HVAC) systems. A detailed physical model of HVAC systems with realistic working conditions is established. In the two-stage model, the first stage dispatch is to minimize the electricity consumption one day in advance and the second stage is to reduce power exchange fluctuations with external grids in the real-time dispatch. Besides, uncertainties in both photovoltaic power output and outdoor temperature are accommodated by the CVaR approach. Finally, the numerical results of an actual smart building validate the effectiveness and economy of the proposed approach.

ACS Style

Wei Feng; Zhinong Wei; Guoqiang Sun; Yizhou Zhou; Haixiang Zang; Sheng Chen. A conditional value-at-risk-based dispatch approach for the energy management of smart buildings with HVAC systems. Electric Power Systems Research 2020, 188, 106535 .

AMA Style

Wei Feng, Zhinong Wei, Guoqiang Sun, Yizhou Zhou, Haixiang Zang, Sheng Chen. A conditional value-at-risk-based dispatch approach for the energy management of smart buildings with HVAC systems. Electric Power Systems Research. 2020; 188 ():106535.

Chicago/Turabian Style

Wei Feng; Zhinong Wei; Guoqiang Sun; Yizhou Zhou; Haixiang Zang; Sheng Chen. 2020. "A conditional value-at-risk-based dispatch approach for the energy management of smart buildings with HVAC systems." Electric Power Systems Research 188, no. : 106535.

Conference paper
Published: 09 July 2020 in Proceedings of the IEEE
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Natural-gas and power systems are increasingly interdependent due to the integration of an increasing number of combined cycle gas turbines in the power generation mix. However, natural gas and power systems are generally independently operated. This is the result of history and the fact that natural gas has not been important for electricity production until recently. Adopting a power system perspective, this article reviews in a tutorial manner models for the operations and long-term expansion planning of interdependent but independently operated natural-gas and power systems.

ACS Style

By Antonio J. Conejo; Sheng Chen; Gonzalo E. Constante. Operations and Long-Term Expansion Planning of Natural-Gas and Power Systems: A Market Perspective. Proceedings of the IEEE 2020, 108, 1541 -1557.

AMA Style

By Antonio J. Conejo, Sheng Chen, Gonzalo E. Constante. Operations and Long-Term Expansion Planning of Natural-Gas and Power Systems: A Market Perspective. Proceedings of the IEEE. 2020; 108 (9):1541-1557.

Chicago/Turabian Style

By Antonio J. Conejo; Sheng Chen; Gonzalo E. Constante. 2020. "Operations and Long-Term Expansion Planning of Natural-Gas and Power Systems: A Market Perspective." Proceedings of the IEEE 108, no. 9: 1541-1557.

Journal article
Published: 10 March 2020 in IEEE Transactions on Sustainable Energy
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This study implements a rolling look-ahead unit commitment scheme in a combined PDN and DHN energy system to exploit the operational flexibility of rapid-response combined heat and power (CHP) units under significantly variable renewable energy source (RES) power output. The scheme is formulated as a multistage distributionally robust (DR) unit commitment model that respects the non-anticipativity of decision variables for sequential revelations of uncertainties. In contrast to the moment-based ambiguity sets employed in conventional DR models, the present framework constructs an ambiguity set based on probabilistic forecasts. In this regard, compatibility between DR approaches and probabilistic forecasts is achieved by incorporating probability measures of uncertain RES power output stemming from probabilistic forecasts. The computational challenge associated with the proposed multistage DR model is addressed by applying linear decision rules. Moreover, a new constraint reformulation approach is utilized to increase the computational speed and tractability. The pertinent model is cast into a tractable mixed-integer linear programming problem. The effectiveness of the proposed method in capturing the probabilistic forecast of RES power output and reducing system operation costs is demonstrated by case studies carried out on the Barry Island multi-carrier energy system.

ACS Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Guoqiang Sun; Sheng Chen. Multistage Robust Look-Ahead Unit Commitment with Probabilistic Forecasting in Multi-Carrier Energy Systems. IEEE Transactions on Sustainable Energy 2020, 12, 70 -82.

AMA Style

Yizhou Zhou, Mohammad Shahidehpour, Zhinong Wei, Guoqiang Sun, Sheng Chen. Multistage Robust Look-Ahead Unit Commitment with Probabilistic Forecasting in Multi-Carrier Energy Systems. IEEE Transactions on Sustainable Energy. 2020; 12 (1):70-82.

Chicago/Turabian Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Guoqiang Sun; Sheng Chen. 2020. "Multistage Robust Look-Ahead Unit Commitment with Probabilistic Forecasting in Multi-Carrier Energy Systems." IEEE Transactions on Sustainable Energy 12, no. 1: 70-82.

Journal article
Published: 17 February 2020 in Energies
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We consider strategic gas/power producers and strategic gas/power consumers operating in both gas and power markets. We build a flexible multi-period complementarity model to characterize day-ahead equilibria in those markets. This model is an equilibrium program with equilibrium constraints that characterizes the market behavior of all market agents. Using a realistic case study, we analyze equilibria under perfect and oligopolistic competition. We also analyze equilibria under different levels of information disclosure regarding market outcomes. We study as well equilibria under different ownership schemes: no hybrid agent, some hybrid agents, and only hybrid agents. Finally, we derive policy recommendations for the regulators of both the gas and the power markets.

ACS Style

Sheng Chen; Antonio J. Conejo. Strategic-Agent Equilibria in the Operation of Natural Gas and Power Markets. Energies 2020, 13, 868 .

AMA Style

Sheng Chen, Antonio J. Conejo. Strategic-Agent Equilibria in the Operation of Natural Gas and Power Markets. Energies. 2020; 13 (4):868.

Chicago/Turabian Style

Sheng Chen; Antonio J. Conejo. 2020. "Strategic-Agent Equilibria in the Operation of Natural Gas and Power Markets." Energies 13, no. 4: 868.

Journal article
Published: 29 January 2020 in IEEE Transactions on Power Systems
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We study investment equilibria in electricity and gas markets where electricity producers and natural gas suppliers behave strategically. We also consider hybrid producers that own both generating units and gas sources. Each strategic producer determines its investment decisions in gas-fired units, and its offering/bidding strategies to maximize its own profit, anticipating electricity and gas market clearing outcomes. Producers owning gas-fired units submit bids to the gas market to procure fuel and offers to the electricity market to sell electricity. The resulting model is recast as an equilibrium problem with equilibrium constraints that we solve using a direct approach. Numerical results from two test systems illustrate the proposed methodology.

ACS Style

Sheng Chen; Antonio Conejo; Ramteen Sioshansi; Zhinong Wei. Investment Equilibria Involving Gas-Fired Power Units in Electricity and Gas Markets. IEEE Transactions on Power Systems 2020, 35, 1 -1.

AMA Style

Sheng Chen, Antonio Conejo, Ramteen Sioshansi, Zhinong Wei. Investment Equilibria Involving Gas-Fired Power Units in Electricity and Gas Markets. IEEE Transactions on Power Systems. 2020; 35 (4):1-1.

Chicago/Turabian Style

Sheng Chen; Antonio Conejo; Ramteen Sioshansi; Zhinong Wei. 2020. "Investment Equilibria Involving Gas-Fired Power Units in Electricity and Gas Markets." IEEE Transactions on Power Systems 35, no. 4: 1-1.

Journal article
Published: 20 November 2019 in IEEE Transactions on Power Systems
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The combined operations of power distribution and district heating networks catalyze the ongoing transition to smart cities. This paper proposes a data-driven distributionally robust energy and reserve co-optimization approach for combined power distribution and district heating networks. In particular, smart buildings are modeled as equivalent storage devices as cost-effective resources to enhance operational flexibility and provide additional reserves in power systems. Uncertainties pertaining to renewable energy source (RES) power and ambient temperature are captured within an ambiguity set that comprises a variety of statistical characterizations (e.g., expected value, variance, covariance) to generate more trustworthy and less conservative solutions. Linear decision rules and the second-order cone duality are employed to enhance computational tractability by transforming the original problem into a second-order cone program. Finally, numerical results based on the real-world Barry Island system demonstrate the risk-reduction and economic benefits of the proposed approach.

ACS Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Zhiyi Li; Guoqiang Sun; Sheng Chen. Distributionally Robust Co-Optimization of Energy and Reserve for Combined Distribution Networks of Power and District Heating. IEEE Transactions on Power Systems 2019, 35, 2388 -2398.

AMA Style

Yizhou Zhou, Mohammad Shahidehpour, Zhinong Wei, Zhiyi Li, Guoqiang Sun, Sheng Chen. Distributionally Robust Co-Optimization of Energy and Reserve for Combined Distribution Networks of Power and District Heating. IEEE Transactions on Power Systems. 2019; 35 (3):2388-2398.

Chicago/Turabian Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Zhiyi Li; Guoqiang Sun; Sheng Chen. 2019. "Distributionally Robust Co-Optimization of Energy and Reserve for Combined Distribution Networks of Power and District Heating." IEEE Transactions on Power Systems 35, no. 3: 2388-2398.

Journal article
Published: 01 November 2019 in IEEE Transactions on Power Systems
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Coordinated operations of electricity and district heating networks offer a potential for mitigating inherent variability of renewable energy sources (RES) in the ongoing transition to smart grids. This paper proposes a two-stage distributionally robust optimization (DRO) approach to determine the optimal day-ahead unit commitment in coordinated electricity and district heating networks with variable RES power output. The proposed formulation is to minimize the worst-case expected total cost over an ambiguity set comprising a family of probability distributions with given support and moments of RES power output. As such, the proposed DRO approach can overcome the limitations of stochastic programming in its inherent dependence of exact probability distributions along with a huge computational burden, but also becomes less conservative than conventional robust optimization. The pertinent DRO model is eventually reformulated as a tractable mixed-integer second-order cone (SOC) programming after employing linear decision rules and the SOC duality. Simplified affine policies are utilized to further improve computational tractability and performance. Finally, case studies are conducted based on Barry Island electricity and district heating networks. The numerical results validate the computational improvement of the proposed approach by employing simplified affine policies.

ACS Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Zhiyi Li; Guoqiang Sun; Sheng Chen. Distributionally Robust Unit Commitment in Coordinated Electricity and District Heating Networks. IEEE Transactions on Power Systems 2019, 35, 2155 -2166.

AMA Style

Yizhou Zhou, Mohammad Shahidehpour, Zhinong Wei, Zhiyi Li, Guoqiang Sun, Sheng Chen. Distributionally Robust Unit Commitment in Coordinated Electricity and District Heating Networks. IEEE Transactions on Power Systems. 2019; 35 (3):2155-2166.

Chicago/Turabian Style

Yizhou Zhou; Mohammad Shahidehpour; Zhinong Wei; Zhiyi Li; Guoqiang Sun; Sheng Chen. 2019. "Distributionally Robust Unit Commitment in Coordinated Electricity and District Heating Networks." IEEE Transactions on Power Systems 35, no. 3: 2155-2166.

Journal article
Published: 15 October 2019 in IEEE Transactions on Power Systems
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ACS Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. Equilibria in Electricity and Natural Gas Markets With Strategic Offers and Bids. IEEE Transactions on Power Systems 2019, 35, 1956 -1966.

AMA Style

Sheng Chen, Antonio J. Conejo, Ramteen Sioshansi, Zhinong Wei. Equilibria in Electricity and Natural Gas Markets With Strategic Offers and Bids. IEEE Transactions on Power Systems. 2019; 35 (3):1956-1966.

Chicago/Turabian Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. 2019. "Equilibria in Electricity and Natural Gas Markets With Strategic Offers and Bids." IEEE Transactions on Power Systems 35, no. 3: 1956-1966.

Journal article
Published: 26 September 2019 in IEEE Transactions on Smart Grid
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The increasing penetration of electric vehicles (EVs) and emerging dynamic wireless charging techniques have strengthened the coupling between traffic networks and power distribution networks. This increased coupling necessitates greater coordination between the two networks. This paper proposes a multi-period optimal traffic and power flow model that considers time-varying electricity and traffic demands. The distribution of traffic flow is represented by a semi-dynamic traffic assignment (SDTA) model, which considers flow propagation between adjacent periods. Combined second-order cone, convex hull, and McCormick envelope relaxations are employed to convexify the power and traffic flow model. Optimization-based bound tightening (OBBT) method combined with a heuristic sequential bound tightening (SBT) method is employed to improve the tightness of the relaxation. The modeling of multi-period scheduling provided by the SDTA model is thoroughly compared with that provided by the conventional static traffic assignment model. In addition, the proposed traffic and power flow model is employed to conduct congestion analysis of the coupled networks. Numerical results on two test systems demonstrate both the spatial and temporal impacts of congestion on each of the coupled networks. Moreover, numerical results verify that the proposed OBBT-SBT-based convex relaxation is sufficiently tight.

ACS Style

Si Lv; Zhinong Wei; Guoqiang Sun; Sheng Chen; Haixiang Zang. Optimal Power and Semi-Dynamic Traffic Flow in Urban Electrified Transportation Networks. IEEE Transactions on Smart Grid 2019, 11, 1854 -1865.

AMA Style

Si Lv, Zhinong Wei, Guoqiang Sun, Sheng Chen, Haixiang Zang. Optimal Power and Semi-Dynamic Traffic Flow in Urban Electrified Transportation Networks. IEEE Transactions on Smart Grid. 2019; 11 (3):1854-1865.

Chicago/Turabian Style

Si Lv; Zhinong Wei; Guoqiang Sun; Sheng Chen; Haixiang Zang. 2019. "Optimal Power and Semi-Dynamic Traffic Flow in Urban Electrified Transportation Networks." IEEE Transactions on Smart Grid 11, no. 3: 1854-1865.

Journal article
Published: 22 August 2019 in IEEE Access
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The establishment and development of an integrated energy market (IEM) contributes to the equitable distribution of electrical and thermal energy production resources. However, the application of conventional locational marginal price theory generally fails to promote the declaration of truthful marginal costs by market participants in the process of clearing and settlement of the IEM, which detracts from market fairness and may reduce market efficiency. Simultaneously, the continuous expansion in the scale of renewable energy sources (RESs) threatens the safe and stable operation of electrical power systems. Accordingly, the present study seeks to improve the efficiency of the IEM under large-scale RES penetration, and promote the truthful declarations of market participants by applying a Vickrey-Clarke-Groves (VCG) auction scheme to the IEM, and establishes a two-stage IEM model that promotes compatibility between the incentives of market participants to enhance market fairness. The present study also addresses the imbalance between market revenue and expenditure typically produced by the VCG auction scheme by designing an ex-post payment redistribution mechanism to ensure the equitable cost recovery of all market participants. Simulation results demonstrate that the application of the proposed VCG auction system to the IEM ensures maximum efficiency, cost recovery, and incentive compatibility as dominant strategies, and helps to integrate large-scale RES penetration with the IEM.

ACS Style

ManYun Huang; Zhinong Wei; Ping Ju; Jinran Wang; Sheng Chen. Incentive-Compatible Market Clearing for a Two-Stage Integrated Electricity-Gas-Heat Market. IEEE Access 2019, 7, 120984 -120996.

AMA Style

ManYun Huang, Zhinong Wei, Ping Ju, Jinran Wang, Sheng Chen. Incentive-Compatible Market Clearing for a Two-Stage Integrated Electricity-Gas-Heat Market. IEEE Access. 2019; 7 (99):120984-120996.

Chicago/Turabian Style

ManYun Huang; Zhinong Wei; Ping Ju; Jinran Wang; Sheng Chen. 2019. "Incentive-Compatible Market Clearing for a Two-Stage Integrated Electricity-Gas-Heat Market." IEEE Access 7, no. 99: 120984-120996.

Journal article
Published: 06 August 2019 in IEEE Access
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State estimation has been widely used in power system energy management systems. However, the application of state estimation for integrated electrical and heating networks (IEHNs) remains in a preliminary stage. This paper addresses this issue by proposing a robust state estimation method for IEHNs based on the weighted least absolute value in conjunction with equality constraints. The robust performance of the proposed estimator resolves the disadvantages of existing combined state estimators. A heating load pseudo-measurement model based on an artificial neural network and real-time measurements is developed to suppress the negative effects of measurements that contain bad data, and thereby ensure an adequate basis for accurate state estimation and guarantee the observability of the heating network. The effectiveness of the proposed state estimation method and its robustness to bad data are verified by comparison with the performance of the conventional largest normalized residual test based on the equality-constrained weighted least squares state estimation of IEHNs in numerical simulations employing a simple IEHN and/or the Barry Island IEHN as case studies.

ACS Style

Haixiang Zang; Minghao Geng; Mingfeng Xue; Xiaobo Mao; ManYun Huang; Sheng Chen; Zhinong Wei; Guoqiang Sun. A Robust State Estimator for Integrated Electrical and Heating Networks. IEEE Access 2019, 7, 109990 -110001.

AMA Style

Haixiang Zang, Minghao Geng, Mingfeng Xue, Xiaobo Mao, ManYun Huang, Sheng Chen, Zhinong Wei, Guoqiang Sun. A Robust State Estimator for Integrated Electrical and Heating Networks. IEEE Access. 2019; 7 ():109990-110001.

Chicago/Turabian Style

Haixiang Zang; Minghao Geng; Mingfeng Xue; Xiaobo Mao; ManYun Huang; Sheng Chen; Zhinong Wei; Guoqiang Sun. 2019. "A Robust State Estimator for Integrated Electrical and Heating Networks." IEEE Access 7, no. : 109990-110001.

Journal article
Published: 15 July 2019 in IEEE Transactions on Power Systems
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Electric power and natural gas systems are typically operated independently. However, their operations are interrelated due to the proliferation of natural gas-fired generating units. We analyze the independent but interrelated day-ahead operation of the two systems. We use a direct approach to identify operational equilibria involving these two systems, in which the Karush-Kuhn-Tucker conditions of both electric power and natural gas operational models are gathered and solved jointly. We characterize the equilibria that are obtained under different levels of temporal and spatial granularity in conveying information between the two system operators. Numerical results from the Belgian system are used to examine the impacts of different levels of information interchange on prices, operational costs, decisions in the two systems.

ACS Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. Operational Equilibria of Electric and Natural Gas Systems With Limited Information Interchange. IEEE Transactions on Power Systems 2019, 35, 662 -671.

AMA Style

Sheng Chen, Antonio J. Conejo, Ramteen Sioshansi, Zhinong Wei. Operational Equilibria of Electric and Natural Gas Systems With Limited Information Interchange. IEEE Transactions on Power Systems. 2019; 35 (1):662-671.

Chicago/Turabian Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. 2019. "Operational Equilibria of Electric and Natural Gas Systems With Limited Information Interchange." IEEE Transactions on Power Systems 35, no. 1: 662-671.

Journal article
Published: 20 May 2019 in Energies
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The present study establishes a stochastic adaptive robust dispatch model for virtual power plants (VPPs) to address the risks associated with uncertainties in electricity market prices and photovoltaic (PV) power outputs. The model consists of distributed components, such as the central air-conditioning system (CACS) and PV power plant, aggregated by the VPP. The uncertainty in the electricity market price is addressed using a stochastic programming approach, and the uncertainty in PV output is addressed using an adaptive robust approach. The model is decomposed into a master problem and a sub-problem using the binding scenario identification approach. The binding scenario subset is identified in the sub-problem, which greatly reduces the number of iterations required for solving the model, and thereby increases the computational efficiency. Finally, the validity of the VPP model and the solution algorithm is verified using a simulated case study. The simulation results demonstrate that the operating profit of a VPP with a CACS and other aggregated units can be increased effectively by participating in multiple market transactions. In addition, the results demonstrate that the binding scenario identification algorithm is accurate, and its computation time increases slowly with increasing scenario set size, so the approach is adaptable to large-scale scenarios.

ACS Style

Guoqiang Sun; Weihang Qian; Wenjin Huang; Zheng Xu; Zhongxing Fu; Zhinong Wei; Sheng Chen. Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach. Energies 2019, 12, 1918 .

AMA Style

Guoqiang Sun, Weihang Qian, Wenjin Huang, Zheng Xu, Zhongxing Fu, Zhinong Wei, Sheng Chen. Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach. Energies. 2019; 12 (10):1918.

Chicago/Turabian Style

Guoqiang Sun; Weihang Qian; Wenjin Huang; Zheng Xu; Zhongxing Fu; Zhinong Wei; Sheng Chen. 2019. "Stochastic Adaptive Robust Dispatch for Virtual Power Plants Using the Binding Scenario Identification Approach." Energies 12, no. 10: 1918.

Journal article
Published: 15 May 2019 in IEEE Transactions on Sustainable Energy
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Increasing interdependency between electric power and gas systems results in tremendous operational challenges. This paper proposes an N-1 security-constrained optimal power and gas flow (SCOPGF) framework that includes contingencies in both energy systems. A bi-directional gas flow model is employed to provide more flexibility for addressing gas system contingencies. We further propose an iterative algorithm to identify binding contingency subsets, which contributes toward ensuring a tractable SCOPGF model. Test results on an integrated IEEE 39-node power system and Belgian 20-node gas system verify the computational advantages of the proposed SCOPGF model employing a reduced binding contingency subset. The necessity of adopting a bi-direction gas flow model under post-contingency conditions is also discussed.

ACS Style

Guoqiang Sun; Sheng Chen; Zhinong Wei; Kwok Cheung; Haixiang Zang. Corrective Security-Constrained Optimal Power and Gas Flow With Binding Contingency Identification. IEEE Transactions on Sustainable Energy 2019, 11, 1033 -1042.

AMA Style

Guoqiang Sun, Sheng Chen, Zhinong Wei, Kwok Cheung, Haixiang Zang. Corrective Security-Constrained Optimal Power and Gas Flow With Binding Contingency Identification. IEEE Transactions on Sustainable Energy. 2019; 11 (2):1033-1042.

Chicago/Turabian Style

Guoqiang Sun; Sheng Chen; Zhinong Wei; Kwok Cheung; Haixiang Zang. 2019. "Corrective Security-Constrained Optimal Power and Gas Flow With Binding Contingency Identification." IEEE Transactions on Sustainable Energy 11, no. 2: 1033-1042.

Journal article
Published: 02 April 2019 in IEEE Transactions on Power Systems
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The interdependency of electric power and natural gas systems requires co-ordinated operational planning. We propose a unit commitment model that integrates a secondorder- cone relaxation of a non-convex nonlinear natural gas flow model that considers pipeline line-pack. The model is enhanced by using convex envelopes of bilinear terms, which tighten the relaxation. By fixing the binary variables at their optimal values and linearizing the natural gas-flow-balance equations around the solution that is obtained, we obtain electricity and natural gas locational marginal prices as the dual variables of electricity- and natural gas-flow-balance equations, respectively. The interdependence between these sets of prices is discussed. Numerical results from two test systems validate the solutionquality and computational-efficiency benefits of the proposed modeling methodology.

ACS Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. Unit Commitment With an Enhanced Natural Gas-Flow Model. IEEE Transactions on Power Systems 2019, 34, 3729 -3738.

AMA Style

Sheng Chen, Antonio J. Conejo, Ramteen Sioshansi, Zhinong Wei. Unit Commitment With an Enhanced Natural Gas-Flow Model. IEEE Transactions on Power Systems. 2019; 34 (5):3729-3738.

Chicago/Turabian Style

Sheng Chen; Antonio J. Conejo; Ramteen Sioshansi; Zhinong Wei. 2019. "Unit Commitment With an Enhanced Natural Gas-Flow Model." IEEE Transactions on Power Systems 34, no. 5: 3729-3738.

Journal article
Published: 28 March 2019 in Energies
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This paper develops a nonlinear analytical algorithm for predicting the probabilistic mass flow of radial district heating networks based on the principle of heat transfer and basic pipe network theory. The use of a nonlinear mass flow model provides more accurate probabilistic operation information for district heating networks with stochastic heat demands than existing probabilistic power flow analytical algorithms based on a linear mass flow model. Moreover, the computation is efficient because our approach does not require repeated nonlinear mass flow calculations. Test results on a 23-node district heating network case indicate that the proposed approach provides an accurate and efficient estimation of probabilistic operation conditions.

ACS Style

Guoqiang Sun; Wenxue Wang; Yi Wu; Wei Hu; Zijun Yang; Zhinong Wei; Haixiang Zang; Sheng Chen. A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network. Energies 2019, 12, 1215 .

AMA Style

Guoqiang Sun, Wenxue Wang, Yi Wu, Wei Hu, Zijun Yang, Zhinong Wei, Haixiang Zang, Sheng Chen. A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network. Energies. 2019; 12 (7):1215.

Chicago/Turabian Style

Guoqiang Sun; Wenxue Wang; Yi Wu; Wei Hu; Zijun Yang; Zhinong Wei; Haixiang Zang; Sheng Chen. 2019. "A Nonlinear Analytical Algorithm for Predicting the Probabilistic Mass Flow of a Radial District Heating Network." Energies 12, no. 7: 1215.

Journal article
Published: 19 December 2018 in IEEE Transactions on Power Systems
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ACS Style

Sheng Chen; Zhinong Wei; Guoqiang Sun; Wei Wei; Dan Wang. Convex Hull Based Robust Security Region for Electricity-Gas Integrated Energy Systems. IEEE Transactions on Power Systems 2018, 34, 1740 -1748.

AMA Style

Sheng Chen, Zhinong Wei, Guoqiang Sun, Wei Wei, Dan Wang. Convex Hull Based Robust Security Region for Electricity-Gas Integrated Energy Systems. IEEE Transactions on Power Systems. 2018; 34 (3):1740-1748.

Chicago/Turabian Style

Sheng Chen; Zhinong Wei; Guoqiang Sun; Wei Wei; Dan Wang. 2018. "Convex Hull Based Robust Security Region for Electricity-Gas Integrated Energy Systems." IEEE Transactions on Power Systems 34, no. 3: 1740-1748.