Qixin Chen

Power Generation Expansion Planning Model Towards Low-Carbon Economy and Its Application in China

Climate change poses a huge threat to human welfare. Hence, developing a low-carbon economy has become a prevailing and inevitable trend. Decarbonization of power generation, especially converting the current power mix into a low-carbon structure, will be a critical option for CO2 emission mitigation. In this paper, an integrated power generation expansion (PGE) planning model towards low-carbon economy is proposed, which properly integrates and formulates the impacts of various low-carbon factors on PGE models. In order to adapt to the characteristics of PGE models based on low-carbon scenario, a compromised modeling approach is presented, which reasonably decreases complexities of the model, while properly keeping the significant elements and maintaining moderate precision degree. In order to illustrate the proposed model and approach, a numerical case is studied based on the background of Chinas power sector, making decisions on the optimal PGE plans and revealing the prospects and potentials for CO2 emission reduction.

Optimal Bidding Strategy of Battery Storage in Power Markets Considering Performance-Based Regulation and Battery Cycle Life

Large-scale battery storage will become an essential part of the future smart grid. This paper investigates the optimal bidding strategy for battery storage in power markets. Battery storage could increase its profitability by providing fast regulation service under a performance-based regulation mechanism, which better exploits a batterys fast ramping capability. However, battery life might be decreased by frequent charge-discharge cycling, especially when providing fast regulation service. It is profitable for battery storage to extend its service life by limiting its operational strategy to some degree. Thus, we incorporate a battery cycle life model into a profit maximization model to determine the optimal bids in day-ahead energy, spinning reserve, and regulation markets. Then a decomposed online calculation method to compute cycle life under different operational strategies is proposed to reduce the complexity of the model. This novel bidding model would help investor-owned battery storages better decide their bidding and operational schedules and investors to estimate the battery storages economic viability. The validity of the proposed model is proven by case study results.

Load profiling and its application to demand response: A review

The smart grid has been revolutionizing electrical generation and consumption through a two-way flow of power and information. As an important information source from the demand side, Advanced Metering Infrastructure (AMI) has gained increasing popularity all over the world. By making full use of the data gathered by AMI, stakeholders of the electrical industry can have a better understanding of electrical consumption behavior. This is a significant strategy to improve operation efficiency and enhance power grid reliability. To implement this strategy, researchers have explored many data mining techniques for load profiling. This paper performs a state-of-the-art, comprehensive review of these data mining techniques from the perspectives of different technical approaches including direct clustering, indirect clustering, clustering evaluation criteria, and customer segmentation. On this basis, the prospects for implementing load profiling to demand response applications, price-based and incentive-based, are further summarized. Finally, challenges and opportunities of load profiling techniques in future power industry, especially in a demand response world, are discussed.

Modeling Flexible Operation Mechanism of

CO2 capture and storage (CCS) has been identified as a critical and promising option for power generation in a carbon-constrained world. Flexible-operation mechanism of CO2 capture power plant is of great significance no matter in enhancing economic returns of plant investment or in ensuring the secure operation of power system. In this paper, the feasibility, mechanism, and options of flexible operation in capture plant are first clarified. Then, based on a benchmark capture plant with postcombustion and solvent/sorbent separation technology, a generic quantitative model is established to formulate the process of CO2 capture and the interaction between capture system and generation system. Plant performances as well as its effects on power-system operation are examined, revealing the different characteristics between CO2 capture power plant and conventional noncapture plants. On this basis, typical operation modes of CO2-capture power plant are defined and identified. In the end, a numerical case is studied to testify the effectiveness of the proposed model.

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In a carbon-constrained world, CO2 emissions will become a new concern in power system dispatch. Meanwhile, carbon capture power plants (CCPPs), which are a critical low-carbon power generation option, will have a significant impact on power system operation and dispatch. This paper presents research on low-carbon power system dispatch (LCPSD) incorporating CCPPs. The operating mechanism of CCPPs is investigated first. Then, the operating characteristics of CCPPs in power system dispatch are analyzed, including feasible power output limits, ramping rates and relationships between the power outputs and the carbon emissions. A comprehensive LCPSD model is formulated, in which the carbon emissions of power plants are treated as a new set of decision variables, and low-carbon-related cost terms are considered. The dispatch features of CCPPs are elaborately formulated and incorporated into the LCPSD model. The effectiveness and the validity of the proposed LCPSD mode and model are demonstrated using numerical examples based on an IEEE 118-bus tested system.

Capture Power Plant and Its Effects on Power-System Operation

Since CO2 capture and storage (CCS) is a viable CO2 abatement option, CO2 capture power plants (CCPPs) could become a significant part of the future generation mix. This paper investigates the flexibility of the operation of a representative post-combustion CCPP with ancillary facilities. A mathematical model of the operation of such a plant is developed. This model quantifies the relation between the major operating characteristics of a CCPP, including efficiency penalty, capacity penalty, net power output, and net CO2 emission. On this basis, a profit maximization model is proposed. This model would help a CCPP decide its power output schedule, CO2 capture schedule, and bidding strategies in response of volatile power and carbon prices in a day-ahead energy market and a cap-and-trade carbon emission market. The validity and the usefulness of the proposed model are demonstrated using numerical results.

Low-Carbon Power System Dispatch Incorporating Carbon Capture Power Plants

As the human population increases and production expands, energy demand and anthropogenic carbon emission rates have been growing rapidly, and the need to decrease carbon emission levels has drawn increasing attention. The link between energy production and consumption has required the large-scale transport of energy within energy transmission networks. Within this energy flow, there is a virtual circulation of carbon emissions. To understand this circulation and account for the relationship between energy consumption and carbon emissions, this paper introduces the concept of “carbon emission flow in networks” and establishes a method to calculate carbon emission flow in networks. Using an actual analysis of Chinas energy pattern, the authors discuss the significance of this new concept, not only as a feasible approach but also as an innovative theoretical perspective.

Optimal Flexible Operation of a CO

Energy storage systems (ESSs) are of great value to realize energy management and to support large-scale renewable generation. The combined operation of ESSs and renewables is one way to achieve output levelling and to improve the integration of sustainable energy. However, in a market-based environment, ESSs would make strategic decisions on self-schedules and arbitrage in energy and ancillary service markets, maximizing the overall profits. Will the strategic operation of ESSs promote renewable generation integration? To explicitly answer this question, this paper proposes a multi-period Nash-Cournot equilibrium model for joint energy and ancillary service markets to evaluate the contribution of the ESSs for supporting renewable generation. Then, a reformulation approach based on the potential function is proposed, which can transform the bi-level equilibrium model into an integrated single-level optimization problem to enhance the computation efficiency. Numerical examples are implemented to validate the effectiveness of the reformulation technique. The results of the case study indicate that the ESSs indirectly but substantially provide improved flexibilities while pursuing individual profit maximization.

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In the future power system with high penetration of renewables, renewable energy is expected to undertake part of the responsibility for frequency regulation, just as the conventional generators. Wind power and battery storage are complementary in accuracy and durability when providing frequency regulation. Therefore, it would be profitable to combine wind power and battery storage as a physically connected entity or a virtual power plant to provide both energy and frequency regulation in the markets. This paper proposes a real-time cooperation scheme to exploit their complementary characteristics and an optimal bidding strategy for them in joint energy and regulation markets, considering battery cycle life. The proposed cooperation scheme is adopted in a real-time battery operating simulation and then incorporated into the optimal bidding model. The scheme could improve the wind regulation performance score and allow for more regulation bids without affecting the battery life, thus significantly increasing the overall revenue. The validity of the proposed scheme and strategy are proved by the case study.

Capture Power Plant in a Combined Energy and Carbon Emission Market

Because the power industry makes a significant contribution to air pollution, a variety of air pollution control technologies have been adopted to reduce emissions of nitrogen oxides, sulfur dioxide, and particulate matters. However, the deployment of these technologies affects the operation of the power plants and of the power system. This paper first discusses the emissions of multiple pollutants by coal- and gas-fired generators equipped with different emission control devices. It then presents the formulation of an environmental power generation scheduling (EnPGS) model, which coordinates the operating cost and the emissions of these pollutants, including the emissions during the startup and shutdown processes. This model considers the air quality index and how this index is affected by the weather, and optimizes the spatial distribution of generation between regions. It also takes into account the operating characteristics of various emission control devices, such as the deactivation of selective catalytic reduction at low output, and the burn mode switching of combined cycle gas turbines. A case study covering several Chinese provinces demonstrates the potential effectiveness of the EnPGS at reducing multiple air pollutants.