Load scenario generation is the basis of studying energy measurement, operation scheduling and other fields, which is of great significance. Due to difficulty of data collection and multi-energy coupling of integrated energy system, it is still a big challenge to generate load data with diversity. A novel multi-load scenario generation method based on generative adversarial network (GAN) is proposed in this paper. Firstly, the Wasserstein generative adversarial network model with gradient penalty optimization is established to overcome the misconvergence and mode collapse caused by high randomness of load. Secondly, on the basis of the recurrent neural network with deep long-term and short-term memory, the generator and discriminator in the GAN are constructed to be more suitable for load data generation of complex integrated energy system. The result shows that the scenarios generated by proposed model achieves better results in probability distribution, curve signature features and correlation in cooling, heating and power load than original GAN and Monte Carlo method. The model can generate realistic load scenarios with diversity in different modes.
The park integrated energy system can significantly improve its operation economy through multi-energy complementary. However, the uncertainty of the controllable resource response will bring challenges to the formulation of the day-ahead dispatching strategy. Thus, a day-ahead optimal economic dispatching strategy considering the integrated demand response and its uncertainty is proposed for the park integrated energy system. Firstly, the uncertainty of photovoltaic and load forecast power and the uncertainty of flexible load response are described by triangular fuzzy number, and a day-ahead dispatching model considering uncertainty is established. Then, in order to minimize the total operation cost of the system, the controllable resources of the supply and demand sides of the system are optimized. According to the fuzzy scheduling theory, fuzzy expectation constraints and fuzzy chance constraints are equivalently converted into their certainty forms for easy solution. Finally, the case analysis shows that the proposed strategy can further reduce the operating cost through integrated demand response; and the impact of fuzzy chance constraint confidence level on the system operating cost is analyzed.
In order to build a low-carbon sustainable energy system and promote the transformation of energy system, this paper focuses on low-carbon and clean energy systems, and establishes a day-ahead dispatch model of an electricity-gas-heat-hydrogen integrated energy system that considers economy and carbon emissions. Firstly, in the integrated energy system network, the power flow model of the power grid and the dynamic power flow models of the heating network and the gas network are established considering the load uncertainty. Considering the advantages of clean, high-efficiency and safety of hydrogen energy in energy conversion equipment, power to hydrogen (P2H) equipment and hydrogen energy storage equipment are introduced. Taking into account the waste heat of gas turbines, fuel cells, etc., the organic Rankine cycle (ORC) waste heat power generation is introduced to convert the remaining heat energy into electric energy and improve energy utilization efficiency. Secondly, the system operating cost and environmental cost are considered as the objective functions. Then the optimal operation dispatching plan is put forward for the electricity-gas-heat-hydrogen integrated energy system. Finally, this paper conducts simulation analysis for multiple optimized operation modes. The simulation results show that the optimized operation strategy of the electricity-gas-heat-hydrogen integrated energy system proposed in this paper can effectively ensure the economic and environmental protection of operation.
For the problems of disloyalty and external attacks in the distributed energy interaction mode of the integrated energy system of district level, combined with the characteristics, structure and types of blockchains, the application feasibility of blockchain technology in the energy dispatch of the integrated energy system is analyzed. The paper proposes a distributed energy scheduling method for an integrated energy system applying blockchain technology, and establishes a two-layer structure of energy interaction, with the goal of minimizing the operating cost of each operator, and the cost increment value as a consistent variable, combining smart contracts, distributed accounting and digital signatures of blockchain technology. A decentralized energy scheduling model based on the Lagrange multiplier method on the physical layer of the structure, and an information transmission framework based on blockchain technology on the information layer are established. The method is verified through calculation examples, which guarantees the fairness, openness, safety and reliability of the distributed energy dispatch process of the heat-electricity integrated energy system of district level.
High proportion of new energy grid-connected brings new challenges to the dispatch and operation of power systems. In order to alleviate the reserve pressure of power systems, a stochastic optimal scheduling model considering multiple flexible reserve resources on both source and load sides is proposed. Firstly, a model of variable scenario is established on the basis of scenario generation method, which considers the influence of the capacity of grid-connected wind power and the area of grid-connected photovoltaic power on the uncertainty of new energy generation. Then, the reserve model of various flexible resources in the system is established. On the source side, the reserve models of conventional units, photovoltaic and wind power are established, respectively, and the uncertainty of wind power and photovoltaic reserve is considered; On the load side, the reserve model is established on the basis of the incentive demand response. Then, the reserve dispatching model is established on the basis of the two-stage stochastic optimization model. The model considers the day-ahead operation and reserve decisions, as well as wind power curtailment, photovoltaic power curtailment, and load shedding risks in uncertain scenarios within the day. Finally, the case studies based on the modified IEEE RTS-24 system verify the effectiveness of the proposed model.
Aiming at the problem of sub-synchronous oscillation (SSO) when multiple PV generation units are merged into the weak AC power grid, three small signal models of PV generation units merged into the weak AC power grid system is established in this paper. Through the analysis of eigenvalue method, the SSO mode existing in the system is obtained, and the participation factor of each SSO mode is calculated. The result shows that there are two inside-plant SSO mode and one plant-grid SSO modes in the system. The inside-plant SSO mode is generated by the interaction among the three power generation units inside the PV plant. The dominant factors are the DC-side capacitance and the parameters of the inverter current inner loop controller; the plant-grid SSO mode is generated by the interaction between the three PV generation units and the AC power grid. The dominant factors are the DC-side capacitance, the inverter current inner loop controller parameters and the AC power grid. Meanwile, by analyzing the damping coupling characteristics of the dominant factors in inside-plant and plant-grid SSO mode, it is concluded that the influence of the PV unit’s generating capacity, DC-side capacitance, and current inner loop controller parameter changes on the damping of the two SSO modes is convergent. Finally, a time-domain simulation model was built in PSCAD/EMTDC to verify the correctness of the theoretical analysis results.
Doubly-fed induction generators (DFIGs), because of their operating characteristics, lose inertial response ability like synchronous generators, which will weaken the inertial response ability of the power system after the large-scale grid-connection of DFIGs. During system disturbance, it will not be able to maintain the frequency in the allowable range, which will affect the stability of the system with wind power in different degrees. This paper derives the inertia control model of DFIG with stator-flux oriented vector control, and proposes a cooperative control strategy based on virtual inertia control and rotor speed control. Then the paper establishes modules of virtual inertia control and rotor speed control in Matlab/Simulink platform to simulate and analyze the influence of the inertia response of the grid-connected DFIG system under cooperative inertia control and the influence of the control strategy on the inertia support and system frequency. The simulation results show that, under different working conditions, the cooperative inertia control can provide a certain inertia support for the wind power grid-connection system, which can improve the stability of the system while effectively preventing the system frequency from falling deeply. The research results can provide theoretical guidance for actual engineering.
Large scale development of offshore wind power will become an important way to achieve the national energy structure adjustment and energy conservation and emission reduction goals. Flexible DC transmission is an important technology for large-scale centralized development of offshore wind power. In order to ensure the high-reliability operation of the off-shore flexible transmission project, a series of tests must be carried out to check the correctness of the converter valve design before it is delivered to the offshore site. For modular multilevel converter with symmetrical monopole topology in an offshore flexible DC transmission project, this paper analyzes the mechanism of abnormal DC partial discharge during dielectric tests on multi-valve unit. Referring to the relevant standards and the experience of previous projects, this paper studies and proposes a test method to solve the abnormal DC partial discharge measurement. On the premise of meeting the standards and specifications, this method can effectively verify the voltage withstand ability and partial discharge level of the multi-valve units with the same topology, and provide reference for the smooth development of dielectric tests on multi-valve unit with higher voltage level in the future.
Distributed optical fiber lines are often exposed to complex terrain conditions and suffer from natural factors such as lightning strike for a long time. In the process of optical fiber signal transmission, with disturbance signal and noise interference, the actual operation state of transmission line cannot be accurately monitored and the fault cannot be accurately located. Aiming at the low accuracy of lightning location in distributed optical network, a new smoothing threshold function is constructed. The threshold function is smooth, continuous and differentiable, which improves the quality of the de manic signal. Through this function, the temperature signal of transmission line monitoring is de-noised by wavelet, the accurate temperature value along the line is obtained, and the fault location is located accurately. The simulation results show that, compared with the traditional threshold function, the smooth threshold function can obtain better de-noising effect, improve the signal-to-noise ratio of the transmission signal, and reduce the root mean square error. The method can improve the detection accuracy of lightning fault location, improve the accuracy of lightning fault removal line and reduce the time of fault location.
Electric vehicles (EVs) can balance grid voltage through V2G (vehicle-to-grid) technology as mobile storage, but their temporal-spatial dual uncertainty will affect the safe operation of the grid. To solve this problem, considering the uncertainty of EVs, this paper proposes an evaluation method for V2G response-ability and energy storage capacity of EVs. The temporal-spatial behavior of the EVs is simulated by Monte Carlo method using the random travel chain. On the basis of the Gaussian mixture model, the probability model of the charging station load and the SOC (state of charge) of the EVs in the station are established. The voltage regulation ability index and the V2G response capacity index of EVs are then proposed to assess the response-ability of EVs in different periods. The simulation compares the dispatchable capacity of EVs and the recovery effect on grid voltage in different periods. Finally, the results verify the effectiveness of the proposed evaluation method.
In order to solve the problem of trust between charging transaction subjects caused by the large-scale development of electric vehicles, this paper proposes a two-stage transaction optimization method for electric vehicle charging piles applying blockchain technology. Firstly, a two-stage transaction optimization framework for electric vehicle charging piles is designed. Then, in order to avoid the impact of overload on the safe and stable operation of the grid, the two-way trading market and P2P trading market are introduced with the capacity margin of the power grid as the constraint. The method performs charging rights transactions between charging stations, and builds an optimization model for the grid and electric vehicle charging pile transactions. Secondly, in order to reduce the deviation penalty cost of charging stations and guide electric vehicle owners to charge in an orderly manner, an optimization model based on demand response is built for the transactions between charging piles and the users. Finally, a simulation scenario is taken as an example to verify the validity of the model. The results of calculation examples show that the two-stage transaction optimization model based on blockchain technology can increase the revenue of the charging station and reduce the peak-to-valley difference of the system.
Since the current research on charging and discharging service mode only considers EV load guidance from the perspective of time-shifting, a “reservation/on-demand” mode is established incorporating the consideration of the regularity of users’ grid-access behaviors. In this mode, electric vehicle aggregator (EVA) can predict the charging needs of users with regular grid-access behaviors through service reservations, thereby improving the guidance effect of EVAs. Firstly, the business process of “reservation/on-demand” service is elaborated. Secondly, considering the comprehensive economic effect and convenience effect, with the goal of maximizing user’s utility, the EVAs can construct optimal service purchase strategies for various users and analyze purchase intentions. Finally, from the perspective of EVA, this paper constructs a utility-based user service selection behavior analysis model to help EVA grasp the influence of different user choices, and uses the Stackelberg game method to process EVA price guidance strategy. Analysis shows that, compared with the existing simplistic service model, the “reservation/on-demand” service mode can not only improve service quality, but also further reduce the power purchase cost of EVA.
With the opening of the power market on the distribution grid side, the power trading participants are diversified, and the power trading strategies are also different. Aiming at the problems in the existing research on multi-microgrid power trading, such as no complete transaction process and mostly on centralized transaction, this paper proposes a smart transaction strategy based on blockchain for multiple microgrids. Firstly, we establish a multi-microgrid intelligent transaction architecture based on blockchain to provide a decentralized transaction platform. Secondly, we establish a multi-microgrid electricity-trading strategy. In the first round of trading, microgrid nodes make quotations considering transaction risk factors, and then clear the market according to the clearing strategy considering the reputation through two-stage bidding match. In the next round of trading, the risk factor can be adjusted adaptively to obtain higher benefits. Finally, a reputation consensus mechanism is used to achieve data consistency. The simulation results prove the effectiveness of the trading strategy and reputation consensus mechanism.
The early exploration of the energy blockchain has provided good technical support for the construction of the energy internet. However, as the continuous influx of large-scale participants, the safety, fairness and efficiency of energy transactions once again face new challenges. Game theory considers the advantages of strategic interaction and interest dependence between transaction subjects, and is expected to provide new solutions. Firstly, the objective function of maximizing the benefits of energy trading is to construct a multi-energy trading strategy game model. According to energy supply and demand and quotation, the Nash equilibrium value of the strategy game between energy users and energy providers is solved, which provides a price reference for the trading mechanism. Combining the characteristics of the energy internet, this paper builds a weakly centralized multi-agent energy transaction mechanism based on the alliance chain, and improves the energy block structure and consensus mechanism to achieve an efficient and reliable transaction process. Simulation results show that the secure transaction mechanism not only protects the interests of buyers and sellers, but also speeds up the consensus of the block, with a view to provide help for the construction of the energy trading platform.
Offshore wind power has become an important field for the development and utilization of wind power due to abundant resources and wide area. However, the strong randomness and intermittent nature of offshore wind power bring many problems to the safe and reliable consumption of offshore wind power. Hydrogen production from wind power is an effective means to improve wind power utilization and alleviate wind curtailment, and it has become a focusing application in the development and research of offshore wind power. This paper comprehensively considers the scheme, equipment investment cost, operation and maintenance cost of hydrogen production technology, and gives the economic evaluation method of the domestic hydrogen production technology from offshore wind power; This paper establishes three technical schemes and economic models for hydrogen production on shore, hydrogen production on offshore platform with hydrogen transported through pipeline and hydrogen production from offshore platform with hydrogen transported by ships. According to relevant research and literature data, taking a 300 MW offshore wind farm as an example, three kinds of hydrogen production technical schemes at different offshore distances are compared in terms of economic efficiency. The results show that among the three technical schemes, hydrogen production from offshore platform with hydrogen transported by ships is the most economic; and the offshore distance increases, the uniform annual value of this scheme is basically unchanged. But with the offshore distance increases, the uniform annual value of the hydrogen production on shore and hydrogen production from offshore platform with hydrogen transported through pipeline schemes increase in different degrees.
