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The mismatch between the rate of the new energy development and the system's peak-shaving capacity has resulted in severe wind abandonment. Based on the grid connection of wind power and natural gas peak-shaving, a model of unit commitment considering wind power consumption and natural gas peak-shaving and taking into account a combination of system economics and wind power consumption capability is designed. Natural gas peak-shaving is added to improve the system's peak-shaving capacity, and a wind abandonment penalty constraint is added to reduce the amount of wind abandoned by the system, and the model is solved by an improved genetic algorithm. Finally, to verify how wind power and natural gas peak-shaving impact unit commitment, the IEEE-30 node system is used. The results show that natural gas peak-shaving reduces system operating costs and improves the safety of the system. This model ensures the economics of system operation while positively promoting wind power consumption effectively and reasonably. [ABSTRACT FROM AUTHOR]

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Abstract The overall electricity consumption of electrolytic aluminum and ferroalloy loads is significant, and some of these loads have dispatch potential that can be used to locally absorb wind power while reducing dependence on conventional thermal power. To characterize the uncertainty of wind power, a fuzzy set of wind power forecasting error probability distribution based on the Wasserstein distance was first established, and the approximate radius of the fuzzy set was corrected under extreme scenarios. By introducing joint chance constraints, the inequalities of uncertain variables were established at the lowest confidence level to improve the reliability of the model. Next, a two-stage distributed robust optimal scheduling model for source-load coordination was developed. In the first stage, wind power forecasting information was fully utilized to schedule the electrolytic aluminum load and optimize unit commitment. In the second stage, the uncertainty of wind power output was considered to schedule the ferroalloy load and optimize unit output. The model was approximately transformed into a mixed-integer linear programming problem and solved using a sequential algorithm. The IEEE 24-bus system was used for case validation. The validation results show that the model can effectively improve wind power absorption capacity, reduce overall operating costs, and achieve a balance between low carbon emissions and robustness.

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. [ABSTRACT FROM AUTHOR]

The overall electricity consumption of electrolytic aluminum and ferroalloy loads is significant, and some of these loads have dispatch potential that can be used to locally absorb wind power while reducing dependence on conventional thermal power. To characterize the uncertainty of wind power, a fuzzy set of wind power forecasting error probability distribution based on the Wasserstein distance was first established, and the approximate radius of the fuzzy set was corrected under extreme scenarios. By introducing joint chance constraints, the inequalities of uncertain variables were established at the lowest confidence level to improve the reliability of the model. Next, a two-stage distributed robust optimal scheduling model for source-load coordination was developed. In the first stage, wind power forecasting information was fully utilized to schedule the electrolytic aluminum load and optimize unit commitment. In the second stage, the uncertainty of wind power output was considered to schedule the ferroalloy load and optimize unit output. The model was approximately transformed into a mixed-integer linear programming problem and solved using a sequential algorithm. The IEEE 24-bus system was used for case validation. The validation results show that the model can effectively improve wind power absorption capacity, reduce overall operating costs, and achieve a balance between low carbon emissions and robustness. [ABSTRACT FROM AUTHOR]

In recent years, the proportion of installed wind power in the three north regions where wind power bases are concentrated is increasing, but the peak regulation capacity of the power grid in the three north regions of China is limited, resulting in insufficient local wind power consumption capacity. Therefore, this paper proposes a two-layer optimal scheduling strategy based on wind power consumption benefits to improve the power grid's wind power consumption capacity. The objective of the upper model is to minimize the peak-valley difference of the system load, which is mainly to optimize the system load by using the demand response resources, and to reduce the peak-valley difference of the system load to improve the peak load regulation capacity of the grid. The lower scheduling model is aimed at maximizing the system operation benefit, and the scheduling model is selected based on the rolling scheduling method. The load-side scheduling model needs to reallocate the absorbed wind power according to the response speed, absorption benefit, and curtailment penalty cost of the two DR dispatching resources. Finally, the measured data of a power grid are simulated by MATLAB, and the results show that: the proposed strategy can improve the power grid's wind power consumption capacity and get a large wind power consumption benefit. [ABSTRACT FROM AUTHOR]

Hydrogen energy plays a crucial role in meeting the “carbon peaking and carbon neutrality” goals, and the carbon capture technology is a vital technique for emission reduction in the energy industry. Blending hydrogen with natural gas to produce hydrogen-enriched compressed natural gas (HCNG) facilitates the transportation and utilization of hydrogen energy. At the same time, applying the carbon capture technology to retrofit thermal power units can effectively promote the large-scale consumption of renewable energy and reduce carbon emissions. For this purpose, a detailed model of hydrogen production equipment and fuel cells is established. Then, aimed at the problem of system carbon emissions, a carbon emission and output model of carbon capture thermal power units and a mathematical model of hydrogen doped cogeneration are established, and a stepped carbon trading mechanism is introduced to control carbon emissions. Based on this, an optimal scheduling model for hydrogen-enriched compressed natural gas integrated energy system is established with the goal of minimizing the sum of energy purchase cost, carbon emission cost, wind abandonment cost, and carbon sequestration cost, and taking into account the constraints such as hydrogen blending ratio and carbon capture in the pipeline network, which is solved by using the particle swarm optimization algorithm in conjunction with CPLEX. The analysis of the models built in different scenarios verifies the advantages of the proposed scheduling model in low-carbon economy.

The study proposes a simplified energy management system (EMS) that can be a useful tool for small towns with a majority of middle-class residents who are looking to improve their quality of life while lowering energy expenditures and having a smaller environmental effect. This article examines the advantages of setting up an EMS in a small community and offers guidance on how to do so. The system is composed of a wind turbine and a gas turbine. The latter can be fueled either from natural gas or from biogas. The system has been implemented in Matlab/Simulink and executed with real-world data that is publicly available. The research presented in this article can assist small towns in developing an environmentally friendly EMS that will improve citizens’ quality of life, where the results have shown continuity of service for the system over many hours with cheap or even free electricity.

To enhance the effectiveness of load-source coordinated control， it is essential to investigate how to allocate regulation tasks to load aggregators in a way that aligns with their regulating characteristics. This research identifies the inevitable breaches in the day-ahead scheduling process under the load aggregator model， arising from constraints imposed by the characteristics of load terminals. Building on this， an indicator for load aggregators is established to quantify their resource flexibility. Subsequently， a day-ahead scheduling method considering the resource flexibility of load aggregators is proposed. In this approach， the grid determines corresponding compensation prices based on the load aggregators’ resource flexibility. This allows for the allocation of regulation capacity while attempting to maintain the desired regulating curve for load aggregators with low flexibility. By doing so， it aims to reduce the inevitable default energy by load aggregators， while avoiding the potential large amount of default energy resulting from allocating regulation capacity based on breach rates. The effectiveness of the proposed method is validated through a case study.

In response to the current challenge of fixed time-of-use pricing strategies that struggle to incentivize electric vehicles （EVs） to participate in wind power consumption， an optimal scheduling strategy for wind-integrated systems considering the regulatory potential of large-scale electric vehicles. Firstly， based on schedulable time and space， assessment indicators of regulatory potential of EVs are developed to establish a potential assessment model for the large-scale involvement of electric vehicles in grid regulation. Subsequently， EVs are categorized based on the regulatory potential assessment results， and a clustering-based time-of-use pricing model is devised that considers the differences between wind power consumption and EV clusters. Moreover， with the objectives of minimizing the peak-valley difference in total load on grid side and minimizing charging costs for EV users， and charging and discharging states of EV clusters serving as decision variables， a model is established， taking into consideration interests of both grid and EV user. Ultimately， the feasibility and effectiveness of the proposed method are verified through example simulations.

Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Under the dual pressure of energy shortage and environmental pollution, relying only on increasing the installed capacity of units and line transmission capacity cannot cope with the conflict between the growth of power demand and the difficulty of grid expansion in the long run. Demand response conducts users to change their energy consumption habits through system-issued electricity prices or incentives, so that the demand of the load side can be adjusted flexibly, which can further enhance the consumption of wind power and improve system economics. Based on the background of diversified energy use, this paper proposes a day-ahead optimal scheduling strategy for integrated electricity and thermal system considering multiple types of demand response. Firstly, the dispatch framework of integrated electricity and thermal system with the situation awareness technology is constructed to address uncertainties of Renewable Energy Sources, thus helping system mitigate uncertain risks. Secondly, the demand response mechanism of power system and regional thermal inertia of thermal system are modeled, respectively, to uncover the principles of load regulation of different energy systems; Then, a day-ahead optimal scheduling model for the integrated thermal and electricity system is developed, and the consumption evaluation index is integrated to indicate energy utilization efficiency; Finally, a combined electric-heat system model with 39- node grid and 6-node heat network is developed, and the positive effects of considering multiple types of demand response and situation awareness technology on promoting the consumption of renewable energy and improving the energy efficiency of the system are verified through the case study. [ABSTRACT FROM AUTHOR]

In the context of carbon neutrality and carbon peaking, in order to achieve low carbon emissions and promote the efficient utilization of wind energy, hydrogen energy as an important energy carrier is proposed to mix hydrogen and natural gas to form hydrogen-enriched compressed natural gas (HCNG). It is also injected into the natural gas pipeline network to achieve the transmission and utilization of hydrogen energy. At the same time, the participation of demand response is considered, the load's peak and trough periods are adjusted, and the large-scale consumption of renewable energy and the reduction in carbon emissions are achieved. First of all, a fine model of hydrogen production and hydrogen use equipment is established to analyze the impact of adding hydrogen mixing on the economy and the low-carbon property of the system. With green certificates and demand response, the utilization rate of hydrogen energy is improved to further explore the energy utilization rate and emission reduction capacity of the system. Secondly, on the basis of modeling, the optimal scheduling strategy is proposed with the sum of energy purchase cost, equipment operation cost, carbon emission cost, wind curtailment cost, and green certificate income as the lowest objective function. Considering the constraints such as hydrogen blending ratio and flexible load ratio of the pipeline network, a low-carbon economic scheduling model of hydrogen mixed natural gas was established. The model was linearized and solved by using MATLAB 2021a and CPLEX solver. By comparing different scenarios, the superiority of the model and the effectiveness of the strategy are verified. [ABSTRACT FROM AUTHOR]

With the promotion of the dual carbon target, the scale of the wind power grid connection will significantly increase. However, wind power has characteristics such as randomness and volatility, and its grid connection challenges the pressure of system peak shaving, making it increasingly difficult to regulate the power system. To solve the problem of wind power abandonment, the positive and negative peak shaving characteristics of wind power were first analyzed. Based on this, it is proposed that demand response resources and energy storage with adjustable characteristics are used as the new means of wind power consumption. Together with the thermal power units, they participate in the optimization and scheduling of the power grid, forming a coordinated and optimized operation mode of source load storage. With the goal of minimizing system operating costs, a two-stage economic scheduling model was formed for the day-ahead and intra-day periods. Finally, optimization software was used to solve the problem, and the simulation results showed the effectiveness of the proposed economic scheduling model, which can improve the system's new energy consumption and reduce the system's operating costs. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Guangxi Normal University - Natural Science Edition is the property of Gai Kan Bian Wei Hui and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

To improve the renewable energy consumption capacity of integrated energy system (IES) and reduce the carbon emission level of the system, a low-carbon economic dispatch model of IES with coupled power-to-gas (P2G) and hydrogen-doped gas units (HGT) under the stepped carbon trading mechanism is proposed. On the premise of wind power output uncertainty, the operating characteristics of the coupled electricity-to-gas equipment in the system are used to improve the wind abandonment problem of IES and increase its renewable energy consumption capacity; HGT is introduced to replace the traditional combustion engine for energy supply, and on the basis of refined P2G, a part of the volume fraction of hydrogen obtained from the production is extracted and mixed with methane to form a gas mixture for HGT combustion, so as to improve the low-carbon economy of the system. The ladder type carbon trading mechanism is introduced into IES to guide the system to control carbon emission behavior and reduce the carbon emission level of IES. Based on this, an optimal dispatching strategy is constructed with the economic goal of minimizing the sum of system operation cost, wind abandonment cost, carbon trading cost and energy purchase cost. After linearization of the established model and comparison analysis by setting different scenarios, the wind power utilization rate of the proposed model is increased by 24.5%, and the wind abandonment cost and CO2 emission are reduced by 86.3% and 10.5%, respectively, compared with the traditional IES system, which achieves the improvement of renewable energy consumption level and low carbon economy.

In order to improve the consumption capacity of wind power plants and deal with the problems of high cost, high risk and low efficiency in traditional demand response, this paper proposes a new optimal scheduling strategy of demand response based on blockchain and the priority of high-capacity enterprises. Based on the analysis of different high-energy load types, the load response dispatching priority and hierarchical electricity price strategy are first put forward. Then the transaction framework of load aggregator, wind power, high-energy enterprise based on blockchain is constructed. Furthermore, the optimization model of load aggregator participating in dispatching is established, which is optimized by multi-objective particle swarm optimization (MOPSO) algorithm. Finally, through the simulation of a certain day in a certain area, the income of aggregators and the cost of wind power plants participating in this dispatching transaction before and after adopting this demand response dispatching scheme are analyzed and compared. It is verified that the demand response scheduling scheme proposed in this paper can effectively guarantee the revenue of load aggregators and improve the wind power consumption level.

Under the dual pressure of energy shortage and environmental pollution, relying only on increasing the installed capacity of units and line transmission capacity cannot cope with the conflict between the growth of power demand and the difficulty of grid expansion in the long run. Demand response conducts users to change their energy consumption habits through system-issued electricity prices or incentives, so that the demand of the load side can be adjusted flexibly, which can further enhance the consumption of wind power and improve system economics. Based on the background of diversified energy use, this paper proposes a day-ahead optimal scheduling strategy for integrated electricity and thermal system considering multiple types of demand response. Firstly, the dispatch framework of integrated electricity and thermal system with the situation awareness technology is constructed to address uncertainties of Renewable Energy Sources, thus helping system mitigate uncertain risks. Secondly, the demand response mechanism of power system and regional thermal inertia of thermal system are modeled, respectively, to uncover the principles of load regulation of different energy systems; Then, a day-ahead optimal scheduling model for the integrated thermal and electricity system is developed, and the consumption evaluation index is integrated to indicate energy utilization efficiency; Finally, a combined electric-heat system model with 39-node grid and 6-node heat network is developed, and the positive effects of considering multiple types of demand response and situation awareness technology on promoting the consumption of renewable energy and improving the energy efficiency of the system are verified through the case study.

Aiming at the problem of wind curtailment caused by the lack of system flexibility, an optimal scheduling strategy for improving the flexibility of the electricity-gas- heat interconnection system by the coordinated operation of the gas network management and storage characteristics and the heat storage characteristics of the heat network is proposed. Firstly, the influence of gas network storage and heat network storage on improving flexibility is analyzed respectively. Then, an electricity-gas-heat interconnected system scheduling model considering the dynamic characteristics of gas network management and t the delay characteristics of heat storage in heat network, which greatly improves the imbalance between supply and demand of flexibility in space and time brought by the anti-peak regulation characteristics of wind power to the system. Finally, the IEEE-24 nodes power system, Belgium's 20-node natural gas network and 6- node thermal network are used, for example, analysis. The results show that the proposed scheduling scheme improves the flexibility of the system while its operating cost and wind curtailment cost are the lowest, which promotes the consumption of wind power. [ABSTRACT FROM AUTHOR]

To solve the problems of large thermoelectric coupling in combined heat and power, high carbon emission of thermal power units, and insufficient resource flexibility on the load side in cogeneration units, a low-carbon dispatching model is established for the electricity-heat system. First, heat storage and carbon capture equipment is added on the source side while the demand response of electricity price and the heat load inertia of heating buildings are considered on the load side. Then, the sum of unit operating cost, carbon transaction cost and wind abandonment penalty cost are taken as the objective function with relevant constraints and solved by calling Gurobi solver. Finally, a comparative analysis of the economic cost, wind power consumption, and carbon emission rate of the system in different cases is conducted, which shows that the dispatching strategy proposed in this paper can improve the wind power consumption capacity while taking economy and low carbon emission into account.

Aiming at the problem of wind curtailment caused by the lack of system flexibility, an optimal scheduling strategy for improving the flexibility of the electricity-gas-heat interconnection system by the coordinated operation of the gas network management and storage characteristics and the heat storage characteristics of the heat network is proposed. Firstly, the influence of gas network storage and heat network storage on improving flexibility is analyzed respectively. Then, an electricity-gas-heat interconnected system scheduling model considering the dynamic characteristics of gas network management and t the delay characteristics of heat storage in heat network, which greatly improves the imbalance between supply and demand of flexibility in space and time brought by the anti-peak regulation characteristics of wind power to the system. Finally, the IEEE-24 nodes power system, Belgium’s 20-node natural gas network and 6-node thermal network are used, for example, analysis. The results show that the proposed scheduling scheme improves the flexibility of the system while its operating cost and wind curtailment cost are the lowest, which promotes the consumption of wind power.

In an electricity and heat integrated energy system, the transmission of thermal energy encounters significant delays, and the delays are often not integer multiples of the dispatch interval. This mismatch poses challenges for achieving coordinated dispatch with the electric power system. To address this problem, the fictitious node method is proposed in this paper, offering a novel approach to calculating the quasi-dynamic characteristics of the heating network. Furthermore, to enhance the local consumption capacity of wind power, the heat storage capacity of the heat supply network was taken into consideration in this study, and a combined energy supply model equipped with electric boilers, incorporating combined heat and power (CHP) units and gas turbine units, was developed. This model effectively expands the operational range of CHP units and enables the decoupling of electricity and heat operations in gas turbine units. The analysis conducted demonstrated the effectiveness of the proposed method and model in achieving the coordinated dispatch of electricity and heat. Moreover, it highlighted the positive impact on the overall economy of system operation and the promotion of wind power consumption. The optimal configuration presented in this paper resulted in an 8.2% improvement in system operating economics and a 38.3% enhancement in wind power integration. [ABSTRACT FROM AUTHOR]

The wind power (WP) has strong random volatility and is not coordinated with the load in time and space, resulting in serious wind abandonment. Based on this, an orderly charging and discharging strategy for electric vehicles (EVs) considering WP consumption is proposed in this paper. The strategy uses the vehicle-to-grid (V2G) technology to establish the maximum consumption of WP in the region, minimizes the peak–valley difference of the power grid and maximizes the electricity sales efficiency of the power company in the mountainous city. The dynamic electricity prices are set according to the predicted values and the true values of WP output, and the improved adaptive particle swarm optimization (APSO) and CVX toolbox are used to solve the problems. When the user responsiveness is 30%, 60% and 100%, the WP consumption is 72.1%, 81.04% and 92.69%, respectively. Meanwhile, the peak shaving and valley filling of the power grid are realized, and the power sales benefit of the power company is guaranteed. [ABSTRACT FROM AUTHOR]

The anti-peak shaving characteristics of wind power is an important factor that limits the consumption of wind power. The use of the space-time translation capability of a battery energy storage system is one of the effective means for promoting wind power consumption. Thus, this study proposes an energy storage system smoothing wind power fluctuation control strategy considering wind power consumption to improve the utilization level and economy of an energy storage system. First, the statistical characteristics of wind power are analyzed, and the scene division principle of a multiscenario regulation of an energy storage system is formulated using a correlation coefficient. On this basis, the charging and discharging intervals of the energy storage system in each scenario are determined by comprehensively considering the wind power and the time domain distribution law of load. Then, the control strategy of energy storage system based on inter-zone control is proposed based on the division of charging and discharging intervals. During the charging interval, smoothing the upward fluctuation of wind power or reducing the amount of abandoned wind power is aimed at storing electricity. During the discharge interval, electricity is released to smooth the downward fluctuation of wind power. Finally, considering the real-time state of charge and wind power consumption of the energy storage system, a method of charging and discharging power correction based on fuzzy control is proposed. Taking the actual data of a wind farm as an example, a test is performed on a simulation platform of a combined wind storage power generation system to verify the feasibility and superiority of the proposed control strategy.

In recent years, global energy shortages and environmental pollution have intensified. With the large-scale development of new energy wind energy, there is also a major problem-insufficient absorption capacity. In order to promote large-scale wind power consumption, a model predictive control method based on wind hydrogen coupled power generation system is proposed. Firstly, the mathematical models of equivalent state of charge in wind power, hydrogen energy storage systems (HESS), and gas storage tanks are analyzed. Secondly, the optimization objective function is to maximize the local wind energy consumption and minimize the energy interaction between the main grid. Establish an SSM prediction model based on the MPC strategy. Genetic optimization algorithm is used for rolling solution. Aiming at the interference and prediction error generated during the operation of the system, a feedback mechanism is introduced to embed it into the MPC framework. Then, the rolling time domain method is used to compensate for system interference. Finally, a case study was conducted based on actual measurement data from a certain area in the Netherlands. By comparing the wind power dissipation effects of the system during operation, it is verified that the proposed method can effectively reduce interactive power consumption. Maximize the local consumption of wind power.

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Copyright of Journal of Shanghai Jiao Tong University (1006-2467) is the property of Journal of Shanghai Jiao Tong University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In order to select a more economical wind power consumption scheme for RIES （regional integrated energy system）， the electricity-gas multi-energy complementarity optimization models considering the reuse of waste heat from power to gas （P2G） reaction and the electric-thermal multi energy complementary optimization model of air source heat pump （ASHP） are established based on the principle of multi-energy complementarity. Taking account of the investment and maintenance cost of P2G and ASHP， the RIES multi-energy complementary economic dispatch model is established with the goal of minimizing the overall operating cost of the system. Constraints of energy supply and demand balance and various unit operation constraints are considered. The optimization software CPLEX is used to solve various models. The example calculation results show that the scheme considering the reuse of waste heat from P2G reaction can reduce the configuration capacity of P2G and increase the operation benefit of the system. On condition of the same consumption rate of wind power， the electric-thermal multi-energy complementary optimization model with ASHP is superior in economy and overall energy efficiency.

With the rapid development of our country, the construction and development of power system has shown the continuous growth of load, and the proportion of new generation energy has also expanded. The impact of these problems on our life cannot be underestimated. Therefore, the development of new energy has become a necessary way to realize the transformation of energy production to green and renewable energy, which is an important direction and necessary decision-making Energy and economy can achieve sustainable development goals all over the world. In order to improve the peak shaving capacity of the power system, this paper proposes to introduce the load side into high energy consuming enterprises to participate in the regulation, and carry out joint optimal dispatching with conventional thermal power units. The optimization goal is to minimize the sum of all day waste air volume of the next day, and the simulation software is used to optimize it. Compared with the regulation of a single thermal power unit, the effect is better, it plays a positive role in reducing wind abandonment, improves the utilization rate of wind power, and has high economic and environmental benefits.

In order to overcome the curtailment of wind energy caused by “power determined by heat” of combined heat and power units, this study proposes an integrated demand response strategy and optimization method for heat-electric energy dispatching in a regionally integrated energy system. Firstly, a scenario analysis algorithm based on Latin Hypercube Sampling (LHS) and Backward Reduction (BR) is applied to characterize the probability characteristics of wind power output. In addition, a novel integrated demand response scheduling model with the consideration of transmission characteristics of the heating network, aiming at minimizing the operation cost, is proposed for a regional integrated energy system. To solve this model, the thermos-electric coupling relationship is evaluated and the proportion of thermoelectric demand response is also weighted. The user satisfaction and economy will finally reach a more optimal level, and thereby is solved via CPLEX solver in MATLAB. The simulation results on a actual integrated energy system reveal that the proposed method is capable of optimizing energy consumption and lowering operational costs while maintaining user satisfaction with the uncertain wind generation by leveraging thermal inertia of the integrated energy system.

The Integrated Energy System (IES) that coordinates multiple energy sources can effectively improve energy utilization and is of great significance to achieving energy conservation and emission reduction goals. In this context, a low-carbon and economic dispatch model for IES is proposed. Firstly, a hydrogen energy-based IES (H2-IES) is constructed to refine the utilization process of hydrogen energy. Secondly, the carbon emissions of different energy chains throughout their life cycle are analyzed using the life cycle assessment method (LCA), and the carbon emissions of the entire energy supply and demand chain are considered. Finally, a staged carbon trading mechanism is adopted to promote energy conservation and emission reduction. Based on this, an IES low-carbon and economic dispatch model is constructed with the optimization goal of minimizing the sum of carbon trading costs, energy procurement costs, and hydrogen sales revenue, while considering network constraints and constraints on key equipment. By analyzing the model under different scenarios, the introduction of life cycle assessment, staged carbon trading, and hydrogen energy utilization is shown to promote low-carbon and economic development of the comprehensive energy system.

Copyright of Electric Drive is the property of Electric Drive Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Electric Power Automation Equipment / Dianli Zidonghua Shebei is the property of Electric Power Automation Equipment Press and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the projects of combined heat and power, the application of large capacity heat storage can improve the flexibility of power system operation control, so as to enhance the system ability to absorb wind power. To study the necessity of heat storage tank configuration, a cost-benefit model of heat storage tank configuration for thermal power plants was established, and the total revenue of heat storage tank configuration for thermal power plants was calculated by substituting the parameters obtained from the electrothermal comprehensive dispatching model of power systems with heat storage. The simulation example was solved by the mathematical programming solver GUROBI in MATLAB. The simulation results show that there is an optimal capacity of heat storage system to make the overall efficiency best and the model can effectively analyze the necessity of heat storage tank configuration in thermal power plants.

To solve the problem of the large gap in the regulation resources of the power system due to the large number of wind power connected to the grid and to help achieve the strategic energy goal of “carbon neutrality and carbon peaking,” the demand-side adjustable energy-intensive load is taken as the research object in this paper, and a two-stage low-carbon economic scheduling method of the wind power system with multi-form energy-intensive load (MEL) is proposed. First, the operating characteristics of the system with MEL are analyzed. At the same time, a refined mathematical model that conforms to the actual operation characteristics is established. Then, the complementary low-carbon characteristics of the source-charge side and the difference in the response characteristics of the demand-side MEL are considered. Meanwhile, combining with the energy storage system, a day-ahead and intra-day two-stage low-carbon economic scheduling model of the wind power system with MEL is constructed. Finally, an example of the improved IEEE-39 bus system is analyzed to verify the effectiveness of the proposed scheduling method in the low-carbon economic scheduling of wind power systems and to provide a reference for power grid scheduling.

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Bio-inspired computer modelling brings solutions fromthe living phenomena or biological systems to engineering domains. To overcome the obstruction problem of large-scale wind power consumption in Northwest China, this paper constructs a bio-inspired computer model. It is an optimal wind power consumption dispatching model of multi-time scale demand response that takes into account the involved high-energy load. First, the principle of wind power obstruction with the involvement of a high-energy load is examined in this work. In this step, highenergy load model with different regulation characteristics is established. Then, considering the multi-time scale characteristics of high-energy load and other demand-side resources response speed, a multi-time scale model of coordination optimization is built. An improved bio-inspired model incorporating particle swarm optimization is applied to minimize system operation and wind curtailment costs, as well as to find the most optimal energy configurationwithin the system. Lastly, we take an example of regional power grid in Gansu Province for simulation analysis. Results demonstrate that the suggested scheduling strategy can significantly enhance the wind power consumption level and minimize the system's operational cost. [ABSTRACT FROM AUTHOR]

As a high-quality secondary energy, hydrogen energy has great potential in energy storage and utilization. The development of power-to-hydrogen (P2H) technology has alleviated the problem of wind curtailment and improved the coupling between the power grid and the natural gas grid. Under the premise of ensuring safety, using P2H technology to mix the produced hydrogen into the natural gas network for long-distance transmission and power generation can not only promote the development of hydrogen energy but also reduce carbon emissions. This paper presents a new model for incorporating hydrogen into natural gas pipelines. To minimize the sum of wind curtailment cost, operation cost and carbon emission cost, an electric–gas integrated energy system (EGIES) model of hydrogen-compressed natural gas (HCNG) containing P2H for power generation is constructed. Aiming at the problem of global warming caused by a lot of abandoned wind and carbon emissions, the economy and environmental protection of the system model are analyzed. The results show that the model of EGIES considering HCNG can not only absorb excess wind power but also reduce carbon emission costs and system costs, which can reduce the total cost of the environmental economic dispatch of the EGIES by about 34.1%. In the context of the EGIES, the proposal of this model is of great significance to the economical and environmentally friendly operation of the system. [ABSTRACT FROM AUTHOR]

In view of the large output of wind power during the load trough time, the peak regulation cost may increase sharply, and the traditional hourly dispatch may not be able to accurately track the load fluctuation due to the fluctuation of renewable energy. In this paper, based on different time granularities, an adaptive segmented double-layer economic scheduling model of the net load curve considering reasonable wind abandonment is constructed. The model can better cope with net load changes while reducing the load peak-to-valley difference. First, a reasonable wind abandonment model is established under different time granularities of 5 min, 15 min, 30 min, and 1 h; Then, based on the static thinking of the net load curve by time period, the load change in the hourly scale is fully considered without changing the total number of dispatching periods so that each dispatching period can adaptively select the duration according to the change of net load gradient, and a self-adaptive subsection model of the net load curve is established to minimize the total running cost. Finally, taking IEEE-30 nodes as the example system, the NSGA-II algorithm and CPLEX solver are used to solve the model. The results verify the economy and feasibility of the proposed model.

In the context of Chinese efforts to achieve the goal of “carbon peaking and carbon neutrality” for the “Three North” area heating season, thermal power units, due to their unique operation mode of “fixing electricity by heat” and the resulting problem of insufficient wind power consumption by the night system, were proposed as an optimization method for wind power consumption based on thermal storage tanks in the context of stepped carbon trading. The optimization method is applied to thermal power plants and considers the constraints of cogeneration unit thermoelectric coupling, electrical power balance, and thermal power balance. Taking the lowest total cost of thermal power plants as the objective function, the Cplex solver in Matlab is used to solve the objective function. The wind power consumption by the system, the CO2 emissions of thermal power plants, and the economy of the system are analyzed in different scenarios. The calculation example results show that the model proposed in this article not only improves the wind power consumption rate of the system and reduces the CO2 emission of the thermal power plant but also improves the economy.

Copyright of Zhejiang Electric Power is the property of Zhejiang Electric Power Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a method of energy storage capacity planning for improving offshore wind power consumption. Firstly, an optimization model of offshore wind power storage capacity planning is established, which takes into account the annual load development demand, the uncertainty of offshore wind power, various types of power sources and line structure. The model aims at the lowest cost of investment, operation and maintenance of the system, and takes lower than a certain abandoned wind level as the strict constraint to obtain two parameters of power capacity and energy capacity of energy storage on the source side. Secondly, taking a coastal power grid as a typical case, the energy storage capacity planning method is verified. Finally, the key factors affecting offshore wind power consumption are summarized, and the sensitivity analysis is carried out from the point of view of the transmission protocol of the transmission lines outside the province and the capacity allocation of the tie lines in the province. This study will be helpful for the planning and operation of the high-proportion of offshore wind energy power systems. [ABSTRACT FROM AUTHOR]

Due to the insufficient consideration of medium and long-term wind power contract power in short-term dispatch, long-term planning and real-time consumption of wind power cannot be effectively undertaken, resulting in a large amount of abandoned wind power. A way to improve the wind power absorption capacity has become an urgent problem to be studied. According to the characteristics of the market and dispatching in the process of wind-fire integration construction, this paper constructs a wind power consumption model that connects the mid- and long-term transaction power decomposition and short-term dispatch. Considering the unit output characteristics and maintenance, the monthly contract electricity is decomposed into daily electricity, and the nesting of medium and long-term transactions and short-term scheduling is realized; the second stage is a short-term multi-objective optimal scheduling model considering the decomposition of contract electricity and the output of non-bidding units to improve the real-time consumption of wind power. Finally, a province in northwest China is taken as an example to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]