The connection of large-scale renewable energy to the power grid reduces the frequency stability of the power system, which brings new problems and challenges to the secondary frequency regulation of the power system. With a large cluster, the electric vehicles have become a new type of frequency-regulation resources due to its accurate and fast dynamic response capability. This paper first summarizes the system framework of numerous electric vehicles participating in frequency-regulation ancillary service and introduces two methods to quantify the adjustable capacity of aggregated electric vehicles. One method quantifies the adjustable capacity of the aggregated electric vehicles directly, and another one presents the energy feasible region of the aggregated electric vehicles. Then, the day-ahead optimal scheduling and the real-time control process of electric vehicles participating in secondary frequency regulation of the power system are reviewed from different aspects: model, method, and application. Finally, the future research direction and key technologies of numerous electric vehicles participating in secondary frequency regulation of the power system are prospected.
Voltage sag has become the most serious power quality problem. Since voltage sag is inevitable, risk assessment becomes the key link to reduce its impact. Firstly, three kinds of risk quantitative indicators for voltage sag are analyzed, and the risk assessment methods are divided into three categories: simulation-based, state estimation-based and data-driven risk assessment methods. The advantages, disadvantages and applicable scenarios of each method are summarized. Secondly, the paper points out the technical challenges faced by voltage sag risk assessment in the context of new power system. Finally, the future research direction of voltage sag risk assessment is prospected, in order to provide reference for related research.
The construction of the new power system dominated by new energy is a key driver to achieve the goal of carbon peaking and carbon neutrality. The traditional power supply structure dominated by controllable coal-fired power installations is transformed into a new power system dominated by new energy with strong uncertainty and weak controllability, which will face challenges such as shortage of flexibility resources. In order to improve the flexibility of the new power system, a two-stage scheduling optimization model of flexible resource aggregation is proposed in this paper. The first stage model considers time-of-price demand response, and takes the minimum net load fluctuation as the goal to smooth the load curve. The second stage model considers segmented incentive-based demand-response market trading mechanism, integrates flexibility resources such as electrochemical energy storage, pumped storage, and reformed thermal power, and designs the optimal operation scheme with the objective of minimizing system operation cost. Finally, the calculation result and scenario comparison show that demand response can fully exploit the interactive ability of load following system regulation. The reformed thermal power units can reduce coal consumption level, improve regulation ability, and enhance the spatial and temporal matching with system flexibility demand. Various types of energy storage actively respond to the power system peak regulation. Taking pumped storage power station as an example, the reservoir storage capacity presents the shape of "double peaks and double valleys" in the dispatching cycle.
The intermittence of high proportion of renewable energy further aggravates the insecure operation of power system, which makes flexible resources configuration more critical. Therefore, it is necessary to conduct research on flexible resources planning and configuration of power system. For the multi-energy microgrid, a bi-level collaborative optimization method of configuration and operation of flexible resources is proposed in this paper, considering the characteristics of storage battery and power to hydrogen (P2H) equipment. Taking the minimum total annual carbon emissions and the maximum comprehensive annual profit as the objective functions for the outer layer model, and choosing maximum daily operating profit for the inner layer model, a case study under electricity-hydrogen load is carried out. Then cost reduction scenarios of these two flexibility technologies is depicted, and economic, cleanliness and flexibility indices are designed to compare and evaluate the competitiveness of the two technologies in different conditions. The results show that the proposed optimal configuration method can prominently improve the environmental benefits of the microgrid with less economic cost. At present, compared with P2H technology, storage battery technology has overwhelming advantages, but the former will have greater profit margins and market potential in the future.
Cost-benefit research helps to understand the benefits and willingness to trade of various market players, so as to guide the market to formulate a more reasonable trading mechanism. This paper proposes a cost-benefit analysis method for multiple market players considering the coupling of electricity and carbon trading markets under demand response (DR). First, the unit carbon emission cost in carbon trading is included in the quotation function of each generating unit for unified clearing, which reflects the coupling of carbon trading and spot market operations. Secondly, the transactions of various entities in the electricity-carbon coupling market under demand response are considered. A cost-benefit analysis model for the generation side, the user side, the load aggregator, the energy storage operator and the grid side is proposed. Finally, an example analysis is carried out on an actual operation day of a certain provincial power grid in China. The results show that the operation of the carbon emission trading market will raise the clearing price of the electricity market and affect the cost and benefit of the relevant entities.
In order to solve the problems of rural energy efficiency, poor reliability of energy supply, and serious environmental pollution, this paper carries out a two-stage mode design for rural virtual energy systems that takes into account the uncertainty. First, starting from the characteristics of rural energy supply and rural energy demand, a virtual energy system framework that considers rural energy characteristics is designed. Secondly, by analyzing the participants of rural virtual energy systems, a multi-participating rural virtual energy system investment mode is designed; and starting from the government, enterprises, users and other subjects, an evaluation system is built to optimize the investment mode of rural virtual energy systems. Then, a two-stage robust optimization model is introduced to describe the uncertainty of the load, output and market price of the rural virtual energy system, and the operation mode of the rural virtual energy system is constructed. Finally, a calculation example is taken as an example in a rural area in northern China. The results of the calculation example show that the two-stage operation mode of the virtual energy system proposed in this paper is practical and scientific.
The inertia reduction caused by the integration of large-scale wind power, PV, and other renewable energy sources has brought new challenges to the safe operation of new type power systems, especially transient frequency safety. In this paper, on the basis of making full use of the frequency support of new energy sources, a two-layer optimization strategy for unit combinations with transient frequency constraints is proposed. A new frequency-response model of the power system considering the frequency support of the new energy station is constructed, and the analytical expression of the transient frequency characteristic quantity is deduced. Then, on the basis of the traditional unit combination model, a unit combination optimization model considering the dynamic frequency constraint is constructed. Introducing an atomic search algorithm, synergistically considering frequency support for optimal load shedding optimization of new energy sources, and unit combination optimization, a two-layer optimization strategy is established. Taking a 10-machine system including PV and wind power as an example, the calculation and analysis are carried out, and the results verify the effectiveness and feasibility of the method in this paper.
The large-scale penetration of wind power may cause serious wide-band oscillations. Wide-band oscillation is closely related to the capacity of the wind farm, the interface impedance, and the operating conditions of wind turbines generators (WTGs). In this paper, the impedance model method is adopted to analyze the wide-band oscillatory characteristics of the wind power system, so as to clarify the relationship between the penetration capacity of the wind farm and the grid impedance under the constraint of wide-band oscillation. Firstly, the full-operating-condition impedance model (FOCIM) of the WTG is established, which takes the voltage and output current at the terminal as variables. Then, on the basis of the FOCIM, the effects of output power and short-circuit ratio (SCR) on the wide-band oscillation are analyzed. Furthermore, how the practicable maximum capacity of the wind farm varies with the grid impedance is studied, which is of reference value for the construction and operation of the wind farm. Finally, the accuracy of the analysis results of the FOCIM is verified by time-domain simulations. The results show that the practicable maximum capacity of the wind farm considering the constraint of wide-band oscillation can be determined on the basis of the FOCIM under different grid conditions.
To cope with the high wind-speed shutdown (HWSS) events of offshore wind turbines, which could be induced by typhoons, a multi-time scale scheduling method is proposed for the power systems integrated with combined wind-storage systems. Firstly, combining the historical and current information, the time-varying hurricane track set is generated by the full-life simulation of the hurricane, which is then integrated into the proposed ambiguity set; Then, the impacts of wind generation fluctuation on various reserve requirements are considered to develop a scheduling framework with constraints of multiple types of reserves to avoid the step increment in power generation of units, which may result in an infeasible scheduling plan. The framework is reformulated as a solvable mixed-integer linear programming problem by deterministic formulation. Finally, a simulated experiment is conducted on the modified IEEE RTS system with 2 offshore wind farms. The experimental result reveals that the proposed scheduling strategy can take full advantage of the flexibility of the combined wind-storage power generation system to enhance the resilience of the power system by preventive scheduling under the extreme hurricane events.
Due to the difference of wind resource distribution, different units in the wind farm have different de-loading reserve capacity. When reserving de-loading reserve, the wind farm should consider the difference of de-loading reserve capacity of different units. In order to solve this problem, the available frequency-regulation capacity model of doubly-fed induction generator is constructed in this paper. According to this model, a coordinated control of frequency-regulation reserve capacity for wind farm considering wind speed difference is proposed. In this strategy, the frequency-regulation resources of wind farms are coordinated according to the differences of available frequency-regulation capacity of different wind turbines, and the kinetic energy of the rotor is fully utilized while the reserve capacity is satisfied. Usually, only part of the wind turbines are controlled, which simplifies the complexity of the control system. The system simulation model is built in DIgSILENT/PowerFactory. The simulation results show that the proposed strategy can coordinate the units with different wind speeds in the wind farm, improve the frequency-regulation capability of the system and alleviate the frequency-regulation pressure of the synchronous machine when load disturbance occurs.
The use of energy storage quasi-Z-source inverter (qZSI) in photovoltaic power generation can reduce power fluctuations, but for nonlinear energy storage qZSI, linear PI control strategy is often used, which is difficult to achieve the ideal control performance. Therefore, an energy storage qZSI control system based on nonlinear Lyapunov control is proposed in this paper. Firstly, the energy management system of energy storage unit is designed to meet load power requirement. Then, according to Lyapunov theory, the energy storage function and control law are designed for energy storage qZSI system, and the appropriate Lyapunov control gain is selected. Finally, on Matlab/Simulink simulation platform, the performance of Lyapunov control system and traditional PI control system are simulated and compared under four different working conditions. The results show that Lyapunov control system has faster response, higher control accuracy and stronger robustness.
Aiming at the problem that photovoltaic clusters are not considered in the traditional evaluation method of carrying capacity of distribution network for distributed photovoltaic power, a two-layer model of carrying capacity with photovoltaic clusters as the evaluation unit is constructed. In the outer layer of the model, PSO algorithm is used to describe the change of load demand through price elasticity coefficient, and the time-of-use price is optimized with the goal of maximizing the income of E-seller. In the inner layer, taking no reverse power transmission to the main network as the index, considering the voltage deviation and equipment thermal stability constraints, a sensitivity ranking method is proposed to calculate the carrying capacity for photovoltaic power. In the actual distribution network of a county in China, the impact of a single photovoltaic cluster on the carrying capacity of the distribution network is calculated, and the carrying capacity of the distribution network for the photovoltaic cluster is calculated to verify the effectiveness of the proposed model and algorithm.
Distributed transactions between multiple microgrids can promote the consumption of new energy and improve the safety of distribution network operation. Nevertheless, the problems such as strong individual profit-seeking and output uncertainty may cause serious breaches of contract and affect the economics of distributed transactions. Therefore, this paper puts forward a distributed energy transaction blockchain model considering reputation value and electrical distance. Firstly, the reputation value evaluation model based on the historical contract completion rate is proposed, and the transaction order of buyers and sellers is adjusted according to the quotation and reputation value. Secondly, in order to promote transaction subjects to choose nearby transactions and improve transaction efficiency, a transaction matching mechanism based on electrical distance is designed in smart contracts. And an adaptive quotation update strategy based on market progress and its own reputation are proposed. Thirdly, a real-time dynamic network security checking method is introduced to realize the safety of distribution network operation. Finally, the smart contract is simulated and analyzed with Matlab and IDE-Remix platform, and the results verify the feasibility and effectiveness of the proposed distributed transaction mechanism.
Consisting of distributed energy resources (DERs), parks with self-generated capacity are participating in the process of market-oriented distribution network coordinated operation. How to achieve the equilibrium between distribution network operator (DNO) and multiple parks under the assurance of safe operation and enthusiasm incentive is an important issue. To solve this problem, this paper introduces the distribution locational marginal price (DLMP) to achieve the optimal guidance of multiple parks on the basis of the price-based incentive mechanism. First, DNO is responsible for the coordinated operation of multiple parks, the DLMP is calculated and used to incentive the demand response process of multiple parks. Then, the multi-agent model of DERs in multiple parks is established, and an interactive benefits priority (IBP) principle is proposed to find the optimal coordinated operation strategy of DERs in each park according to the incentive price from DNO. Finally, the effectiveness of proposed method is illustrated by simulation results. Comparative experiments are carried out between the traditional strategy and the proposed strategy. Experiments show that the proposed strategy can find the optimal combination of DERs more quickly, and DLMP can better guide the coordinated operation of multiple parks in the distribution networks.
With the reform of China's power market and the promotion of energy conservation and emission reduction policies, there are more and more market-oriented policies for the power generation industry. From the perspective of coal-fired power generation enterprises participating in carbon-emission right market and power generation right market, aiming at maximizing enterprise profits, this paper studies five combined trading strategies of power producers in the power market, and uses the fmincon function in Matlab to optimize the power generation plan of power generation enterprises, so as to maximize their own economy under many policy backgrounds. The results show that for large capacity units with environmental protection and energy conservation, the profits obtained by trading generation rights and carbon-emission rights at the same time are significantly higher than those obtained by trading generation rights or carbon-emission rights alone; For some units with high power generation cost, all their power-generation rights can be sold to obtain certain profits. At the same time, the effects of auction proportion and power-generation right price on enterprise profits and carbon emissions are analyzed.
