Thermal Power Units Research Articles

Optimization of multi-energy complementary power generation system configuration based on particle swarm optimization

The multi-energy complementary power generation system, incorporating wind, solar, thermal, and storage energy sources, plays a crucial role in facilitating the coexistence and mutual reinforcement of conventional thermal power and renewable energy. Against the backdrop of evolving power systems and the increasing integration of wind, solar, thermal, and storage technologies, scientifically optimizing the configuration of multi-energy complementary power generation systems has become an essential prerequisite for their sustainable development. This study introduces a dual-layer optimization model for configuring multi-energy complementary power generation systems based on the particle swarm optimization algorithm. The outer layer optimization aims to maximize the net revenue from wind, solar, and storage power generation while the inner layer optimization focuses on minimizing carbon emissions from thermal power units. The proposed approach comprehensively considers both environmental benefits and economic gains of multi-energy complementary power generation systems. Simulation results demonstrate that this method effectively enhances annual net income while significantly reducing carbon emissions by 1.1058 million tons. It establishes a rational capacity configuration scheme that not only improves economic performance but also promotes efficient utilization of clean energy resources. Furthermore, it highlights the advantages of coordinated carbon electricity market trading over traditional modes.

Evaluation and Improvement of the Flexibility of Biomass Blended Burning Units in a Virtual Power Plant

Aiming at the problems of small thermal power units and biomass mixed combustion units with small generation loads and insufficient primary frequency modulation capability, which cannot be connected to the virtual power plant, this paper adopts a variety of flexibility retrofit methods for the units and explores the peak load capability of the units. Then, multiple units are coupled, and the unit coupling scheme with better economy and environmental protection is screened using comprehensive evaluation indexes. While evaluating the peaking load space of multiple unit coupling, the units’ primary frequency regulation capability and new energy consumption capability are improved. According to the calculation results, the low-pressure cylinder zero-output retrofit has the largest peaking potential among different technical paths, in which unit #3 has 27.55 MW of peaking space. The compression heat pump decoupling retrofit has the best economy, in which the daily profit of unit #3 increases from 0.93 to 1.02 million CNY with an increase of 0.09 million CNY. After the unit has been retrofitted with steam extraction, the three units can be coupled to meet the national feed-in standards. The multiple unit coupling can accommodate up to 203.44 MW of other energy sources while meeting the standard.

Dual-layer control strategy based on economic characterization of lifetime state and frequency regulation limit partition of hybrid energy storage

Compared with a single type of energy storage, hybrid energy storage system (HESS) has a better performance in improving the frequency safety of the grid. However, the combination of hybrid energy storage with different resource characteristics and thermal power units will significantly increase the difficulty of coordinated control. In view of the life decay of battery energy storage system (BESS) and the insufficient frequency regulation capability of the system, this paper proposes a dual-layer control strategy based on the economic characterization of hybrid energy storage life state and the frequency regulation limit partition. Real-time state of charge (SOC) is used to establish dynamic equilibrium quotation and energy storage performance characterization as the upper-layer model. Meanwhile, the optimal life evaluation of energy storage is proposed, and the charging and discharging switching model of energy storage is constructed to limit the frequent switching of energy storage and extend its life. The lower-layer model constructs the limit standard of frequency regulation of flywheel energy storage system (FESS), introduces multi-objective constraints, proposes a hybrid energy storage operation scheme suitable for the whole scene, and uses “two rules” as the evaluation index to evaluate the frequency regulation effect of the proposed frequency regulation control model from the regulation rate, accuracy and response time. Finally, taking the actual data of a local thermal power unit as an example, the validity and economy of the frequency regulation effect of the proposed model are verified.

Study of Flexibility Transformation in Thermal Power Enterprises under Multi-Factor Drivers: Application of Complex-Network Evolutionary Game Theory

With the increasing share of renewable energy in the grid and the enhanced flexibility of the future power system, it is imperative for thermal power companies to explore alternative strategies. The flexible transformation of thermal power units is an effective strategy to address the previously mentioned challenges; however, the factors influencing the diffusion of this technology merit further investigation, yet they have been seldom examined by scholars. To address this gap, this issue is examined using an evolutionary game model of multi-agent complex networks, and a more realistic group structure is established through heterogeneous group differentiation. With factors such as group relationships, diffusion paths, compensation electricity prices, and subsidy intensities as variables, several diffusion scenarios are developed for research purposes. The results indicate that when upper-level enterprises influence the decision-making of lower-level enterprises, technology diffusion is significantly accelerated, and enhanced communication among thermal power enterprises further promotes diffusion. Among thermal power enterprises, leveraging large and medium-sized enterprises to promote the flexibility transformation of units proves to be an effective strategy. With regard to factors like the compensation price for depth peak shaving, the initial application ratio of groups, and the intensity of government subsidies, the compensation price emerges as the key factor. Only with a high compensation price can the other two factors effectively contribute to promoting technology diffusion.

Optimal Bidding Strategies for Wind-Thermal Power Generation Rights Trading: A Game-Theoretic Approach Integrating Carbon Trading and Green Certificate Trading

In response to the challenges of low wind power consumption and high pollution emissions from thermal power, the implementation of wind-thermal power generation rights trading is a proactive attempt to reduce wind power curtailment and promote its consumption. This study first regards the alternating bidding process between the two parties as a dynamic game, using the Rubinstein bargaining game model to determine the incremental profit allocation and optimal bidding for both parties in power generation rights trading. Secondly, an energy conservation and emission reduction model is constructed to analyze the benefits from the perspectives of standard coal consumption saving and the carbon emission reduction caused by power generation rights trading. Finally, a combined trading revenue model is established to analyze the final profit of both parties involved in the trading. The results show that the combined trading of wind-thermal power generation rights, incorporating carbon trading and green certificate trading, can effectively promote coal consumption savings in thermal power units and reduce the carbon emissions of the power industry. Moreover, it significantly increases the final profit for both parties, stimulating the enthusiasm of generators for participating in power generation rights trading, and ultimately promoting wind power consumption.

Low carbon economic dispatch of power-gas interconnected systems considering carbon capture technologies

Abstract To address wind power curtailment and high carbon emissions in power systems, this paper proposes a low-carbon economic dispatch model for an electricity-gas system with carbon capture technology. It integrates a carbon storage system, thermal power, wind power, and P2G units, aiming to minimize daily operating costs while adhering to operational constraints. This interconnected approach enhances the system’s low-carbon and economic efficiency.

The optimization and dispatch of regional multi-energy complementary power system in green certificate Trading - Carbon emission trading

Abstract This proposal of the “double carbon” goal underscores the pressing need to reduce carbon emissions. To address this issue, the utilization of an optimal scheduling model for an integrated multi-energy complementary system, comprising wind, solar storage, and thermal power generation, is proposed. Two renewable energy generating units, wind and photovoltaic power, cooperate with thermal power units to generate electricity to meet urban base load requirements. Energy storage units compensate for the instability of power generation from renewable energy units. To significantly decrease system carbon emissions, a green certificate trading-carbon emission trading system is introduced. The carbon emission reduction facilitated by the green certificate can offset a portion of the carbon emissions, and the quantities of tradable green certificates and carbon emissions in their respective markets are adjusted accordingly. This model aims to maximize the system’s comprehensive operating earnings while considering the low-carbon economy aspect. The proposed model undergoes simulation analysis, and the results demonstrate its reasonableness and efficacy in terms of carbon reduction and economic viability.

Research on the evaluation index of thermal power unit optimization results adapted to the characteristics of generation capacity and reliability prediction

Research on the evaluation index of thermal power unit optimization results adapted to the characteristics of generation capacity and reliability prediction

Multi-timescale coupling optimization model and economic analysis for joint transmission of large-scale new energy power generation bases

Abstract Although the northwest of China is full of sand and desert, it is rich in wind, solar, and coal resources. It is an important way to solve the contradiction between new energy and load distribution by bundling “wind-solar-thermal-storage” power through ultra-high voltage channels. In this paper, the optimization model of large-scale new energy bases coupled with multiple time scales is constructed to determine the optimal output of thermal power units in the process of transmission. Then, the economy of thermal power in large new energy bases is analyzed. The results show that the bundling of “wind-solar-thermal-storage” reduces the rate of wind and solar abandonment of new energy and increases the environmental benefits of new energy transmission.

The balance issue of the proportion between new energy and traditional thermal power: An important issue under today's low-carbon goal in developing countries

The stability of the new power system depends on the balance between controllable flexible resources and uncontrollable uncertain resources. For many developing countries and regions lacking advanced flexible resources, thermal power is the main force in solving the problem of new energy consumption. Finding the balance between new energy and traditional thermal power is the key for today's low-carbon goal. To solve this problem, this paper calculates the power range and climbing rate range of thermal power based on physical principles and actual data, and characterizes the characteristics of wind power, photovoltaic power, load and net load based on the five proposed volatility indicators. Then, a logically clear method for determining the required number of thermal power units based on the volatility indicators of new energy from the mechanism and principle perspective is proposed. Finally, under the premise of meeting the power balance and flexibility balance of the power system, the reasonable ratios between the installed capacity of new energy and the number of thermal power units are calculated in four seasons. The results indicate that the judgment system can provide guidance for the energy structure of developing regions.

A Low-carbon Dispatching Method for Cascade Hydropower via HVDC Flexible Delivery

Abstract As a country rich in hydropower resources, the transmission of Southwest hydropower through HVDC system can achieve a large range of optimal allocation of resources, but the traditional HVDC transmission plan is often operated in high and low binary value, which is difficult to give full play to the flexibility of HVDC transmission, and increase the carbon emission and operation cost of the power system. In order to fully explore the flexibility of HVDC transmission mode to reduce system carbon emissions, this paper builds a mixed integer programming model based on the scenario of hydropower being sent to the receiving system through the HVDC system, taking into account such factors as low operating costs and carbon dioxide emissions of thermal power units at the receiving end, overload capacity of the HVDC system, and reactive power compensation cost of the HVDC system. A low carbon scheduling method for cascade hydropower HVDC flexible delivery system is proposed. Finally, taking the cross-regional transmission system of cascade hydropower station as an example, the model proposed in this paper is compared with the high-low binary transmission of traditional HVDC system. The results show that the dispatch mode proposed in this paper and the flexible operation of the HVDC system can promote the consumption of new energy, reduce the CO2 emissions of the system and achieve the dispatch goal of both low carbon and economic operation.

Optimization Operation of Power Systems with Thermal Units and Energy Storage Considering Lifetime Loss and Thermal Units Deep Peaking

Deep peak shaving achieved through the integration of energy storage and thermal power units is a primary approach to enhance the peak shaving capability of a system. However, current research often tends to be overly optimistic in estimating the operational lifespan of energy storage and lacks clear quantification of the cost changes associated with system peak shaving. This study proposes an optimized operation model for the joint operation of thermal power and energy storage while considering the lifespan degradation of energy storage and the deep peak shaving of thermal power. This model measures the cost changes due to the participation of energy storage in thermal power unit peaking. It is able to reflect the value of economic externalities of energy storage in the power system and has a positive reference effect on energy storage investment planning and energy storage subsidy pricing. First, an energy storage lifespan degradation model based on equivalent cycle counts is constructed, along with a thermal power unit peak shaving cost model based on output fluctuations. Second, an optimized joint operation model is developed. Finally, the impact of changes in energy storage capacity and renewable energy output on the system peak shaving costs and energy storage lifespan is recorded. Simulation experiments are conducted based on actual operational parameters, and the results demonstrate that the participation of energy storage in deep peak shaving can indeed effectively reduce system peak shaving costs. Additionally, the actual operational lifespan of energy storage is significantly lower than the floating lifespan.

CO2 emission characteristics modeling and low-carbon scheduling of thermal power units under peak shaving conditions

To accommodate the high penetration of renewable power, the operational flexibility of thermal power units is highly required by the power system, so thermal power units frequently operate under peak shaving conditions. The CO2 emission characteristics of a thermal power unit are significantly influenced by the load factor, and also by the installed capacity and design parameters of the thermal power unit. Therefore, detailed CO2 emission characteristics of thermal power units should be modeled and considered in the low-carbon scheduling of the power system. In this study, thermal power units are classified by live steam parameters, installed capacities, reheat stages, cooling modes, and operation modes, and the models of detailed CO2 emission characteristics are developed and validated. The turbine isentropic efficiency, boiler thermal efficiency, and auxiliary power consumption are comprehensively considered in the CO2 emission model. A new indicator is defined to evaluate the reduction of carbon emissions in a power system when a TPU accommodates per unit of renewable power generation, and an optimization method for low-carbon scheduling based on it is proposed. Finally, a reference case study is conducted. Results show that the total carbon emissions for a day of the proposed low-carbon scheduling method are 0.06 %−0.20 % less than the efficiency priority method, and 1.53 %−2.36 % less than the capacity weighting method.

Deep Thermal Power Peak Shaving Compensation Considering Operating Costs and Electricity Revenue

Unlike traditional methods of electricity generation such as thermal power, renewable energy sources like wind power exhibit characteristics of randomness and volatility, leading to unstable power generation. With the continuous increase in grid-connected capacity of renewable energy sources like wind power, the demand for grid peak shaving is on the rise, highlighting the issue of inadequate peak shaving capacity in China’s power system. As a primary source for peak shaving in the country, thermal power units incur significant revenue losses when participating in deep peak shaving, and under the current mechanism, they cannot obtain sufficient compensation for deep peak shaving. In response to these issues, the paper proposes a method for compensating thermal power units for deep peak shaving. Firstly, considering the reduced efficiency of thermal power units during low-load operation, a cost model for the operation of thermal power units is established. Secondly, building upon the existing compensated peak shaving baseline, a method for compensating thermal power units for deep peak shaving is introduced. Finally, using a simulation of a local power grid in Liaoning Province as an example, an analysis of the compensation for thermal power peak shaving and overall profits under the existing mechanism and the proposed mechanism is conducted. The results obtained validate the rationality and effectiveness of the method proposed in the paper, offering insights for the development of a compensation mechanism for thermal power deep peak shaving.

Research on deep peaking cost allocation mechanism considering peaking demand subject and thermal power unit

The current peak-shaving auxiliary service cost allocation mechanism balances the revenue and expenditure of the power plant side, the peak-valley difference of the power grid is mainly caused by the peak-valley characteristics of the load and renewable energy. It is not reasonable that not reasonable the peak-shaving cost allocation mechanism does not consider user allocation. Therefore, this paper establishes a peak-shaving cost allocation mechanism that considers the peak-shaving demand subject, this article incorporates renewable energy power plants and loads into the peak-shaving demand subject. Firstly, this paper constructs an alternative scenario without peak-shaving demand through the mean line of load and available energy output and establishes an optimal scheduling model with deep peak-shaving and pumped storage power stations, this article takes the difference of system peak-shaving cost between two scenarios with and without peak-shaving demand as the marginal peak-shaving cost. Then, the Shapley value method in cooperative game is used to establish the peak-shaving cost allocation mechanism considering the main body of peak-shaving demand. In addition, It is used that the equal-kWh following load method constructed the equivalent output curve of renewable energy, following load method improves the existing allocation mechanism by comprehensive similarity. Finally, this paper analyzes and compares three different peaking cost allocation mechanisms. The example analysis shows that the peaking cost allocation mechanism considering peaking demand subjects. The example can reflect the peaking cost caused by different subjects and reduce the peaking pressure of thermal power units.

Costs versus revenues of flexibility enhancement techniques for thermal power units in electricity-carbon joint markets

Thermal power units (TPUs) are required to enhance operational flexibility to ensure power grids accommodate the increasing penetration of intermittent renewables. The flexibility enhancement includes increasing peak shaving depth, increasing ramp rate, or both. In electricity-carbon joint markets, increasing peak shaving depth means TPUs can generate less electricity during low-tariff periods while increasing ramp rate means TPUs can respond faster to changes in electricity tariffs. Flexibility enhancement brings additional revenues, but also additional investments. The tradeoff between costs and revenues is important for the construction of sustainable power systems mainly based on renewables, but limited literature models them. To address this gap, variable costs, fixed costs, revenues, and an optimization model for maximum profits are proposed and modeled. Then the economic applicability of different flexibility enhancement aspects is evaluated by comparing the maximum profit increase for a day before and after the flexibility enhancement of TPUs. Furthermore, the profitability of applying different flexibility technologies under the same investments is analyzed, obtaining the optimal flexibility enhancement route. The proposed method is applied to TPUs with different live steam parameters, installed capacities, and reheat stages. Numerical simulations provide detailed economic analysis and optimal flexibility enhancement routes for TPUs in electricity-carbon joint markets.

Study on primary frequency modulation control strategy based on wind-fire cooperation

Abstract Due to the increasing proportion of wind power in the power system, the wind turbine should have the ability of primary frequency modulation when integrated into the power system. At the wind turbine level, different methods are adopted according to different wind speeds, which can get the wind turbine fully joined in the system. Secondly, this paper gives full consideration to the characteristics of thermal and wind power units and proposes a joint primary frequency modulation method between the thermal and wind farms. The output of wind and thermal power is determined by adding a frequency divider. The system stability and reaction speed are effectively enhanced.

Neural network predictive controller based on the improved TPA-LSTM model for ultra-supercritical units

To mitigate the impact of large-scale renewable energy power on the national grid in China, it is imperative to enhance the flexible peaking capability of coal-fired thermal power units. The coordinated control system, central to the load control of coal-fired units, faces challenges such as multivariable coupling, sluggish response, and uncertain coal quality parameters. This paper introduces a neural network predictive controller based on the improved TPA-LSTM model, aimed at addressing these issues. Initially, a data-driven control model is established to break through the limitations of traditional linear predictive control and effectively handle disturbance uncertainties. Then, a multivariable coordinated control strategy based on the neural network controller is designed, achieving effective decoupling of multiple parameters and ensuring high adaptability across all load conditions. Additionally, by integrating an automatic model updating mechanism, the system can recalibrate in real-time when model mismatches occur due to equipment aging, maintenance, or changes in coal quality, thereby enhancing overall control performance. Simulation results demonstrate that this strategy has excellent control effectiveness, meeting the flexible peaking demands of 1000 MW ultra-supercritical units. The calibration feature of the data-driven model significantly improves control performance following model mismatches.

Integrating phase-change thermal storage into the indirect dry-cooling system of a thermal power unit and optimal operation strategy

Extreme conditions (high ambient temperature and crosswind speed) reduce the cooling efficiency of dry cooling towers, consequently impairing the thermal performance of thermal power units (TPUs). Phase-change material thermal storage equipment (PCMTSE) is integrated into an indirect dry-cooling system of the TPU to realize a partial cooling load of the cooling tower, thereby stabilizing and improving the thermal performance of the TPU. A model of the TPU and numerical model of the hybrid indirect dry-cooling system are established and coupled, with the inlet cooling water temperature of the condenser serving as the iterative criterion. Two integration schemes are proposed, one with the PCMTSE downstream (Scheme A) and the other with it upstream (Scheme B) of the dry cooling tower. The results show that Scheme A is recommended owing to its superior efficiency in terms of coal savings. The effects of the unit power load on the coal-savings efficiency of the PCMTSE during its charging and discharging processes have been revealed. Operating the PCMTSE at higher power loads aids in improving the thermal efficiency of the TPU during the PCMTSE charging and discharging processes. The charging process should be started at the “three high” working conditions: a high ambient temperature, crosswind speed, and unit power load. The working conditions that allow only one cooling water pump to operate should first be considered for the discharging process, and the “three high” working conditions should then be selected. The TPU equipped with the PCMTSE can save 11.42 tons and 12.74 tons of coal in two typical extreme daily conditions with the implementation of the proposed operating strategy.

Peak-shaving cost of power system in the key scenarios of renewable energy development in China: Ningxia case study

Renewable energy has developed rapidly in Ningxia, and it has become the first provincial power system in China whose renewable energy power generation output exceeds the power load of the whole region. The access of a high proportion of renewable energy puts forward higher requirements for the peak-shaving capacity of the Ningxia power system. In order to solve the problem of calculating the peak-shaving cost in the key scenarios of renewable energy development in Ningxia, a quantitative model of the peak-shaving cost of the power system considering time-of-use price is proposed. We take Ningxia power system as an example to study. First, the key scenarios of the Ningxia power system peak-shaving are obtained, and the technical cost characteristic boundaries of various peak-shaving resources are determined. Second, according to the characteristics of typical daily renewable energy and load in Ningxia, the quantification model of the power system peak-shaving cost is established. The model takes the minimum total cost of the power system as the objective function and considers the constraints such as technical output of thermal power units, charge-discharge characteristics of energy storage and time-of-use price mechanism. Finally, the model is solved and the peak-shaving cost and unit output under the optimal scheme are obtained. This example shows that the model can effectively evaluate the peak-shaving cost and unit output of the Ningxia power system under the key scenarios of peak-shaving.