A method for distributed power consumption based on the combined heat and power system

With the development of the society and human progress, now resource problems has become one of the major problems faced by people all over the world, the development of new energy and clean energy is the priority now, is now the main power system. Winter heating is one of the main sources of pollution now, so it is very important to study the electric heating system.


Introduction
With escalation of the conflict between power supply and demand, and upgrade of the power use structure in recent years, the winter heating model has been transformed from the traditional coal-fired combined heat and power generation to the gas heating and the electric heating. Statistics show that, due to impact of low temperature and high moisture in winter, the electric boiler load is taking up an increasing percentage in the whole grid load. This poses a tremendous challenge against the grid planning and construction as well as normal operation of the grid. Meanwhile, the user-side distributed power switching-in is accelerating, the flexible load control methods become increasingly invasive, and the demand-side regulation methods are uncertain and diverse. All this necessitates seeking a determinable method for grid virtual peak regulation. Regulation of the credible capacity and the target combination is a core technology in this research field. Besides, the technology is applicable to the grid virtual peak regulation and the regional distributed photovoltaic power consumption of the user-side energy (including regional energy and micro-grid).

User type
Along with urban economic development and constant changes of urban construction models, four types of users in general have been found in the grid virtual peak regulation. They are the household decentralized residential users, large-scale centralized industrial and commercial users, large-scale single system industrial and commercial users, and interconnected reciprocal distributed energy aggregator users, respectively.

Resource management
Peak regulation resources are mainly for the purpose of balancing the grid peak value load output or virtualizing the load output equipment. In this paper, the distributed photovoltaic, virtual energy storage and actual energy storage have been combined to achieve mutual complementation and overall integration, and effectively smoothen the energy demand of the regional grid. That the output increases along with the increase of load and stays at a stable value after reaching its peak is a major distributed photovoltaic characteristic in summer. Virtual energy storage can be generally divided into two kinds. One is flexible load management, which mainly adopts the electric boiler with thermal storage for load reduction. There are four methods of load reduction, and the specific amount is identified according to the unit load in operation. Virtual energy storage of the kind is characterized by gradient load reduction, meaning that load cannot be reduced to the preferable level at once. The other is rigid load management, which mainly serves to realize direct control of nonproductive load, such as lighting. In contrast the above virtual energy storage, this virtual energy storage has more effective control, but its load capacity is small. The energy storage method, though responding to the grid peak frequency regulation instructions and strategies, has not yet found wide applications.

Regulation models
In terms of participation models, energy use of users is diagnosed to identify the adjustable load resources and types. They are further divided into adjustable control and interruptible control. Then, the regulation measurement terminal is installed for the purpose of statistically analyzing the load data. Finally, the big data intelligent analysis method is employed to analyze the demand-side electricity use based on a multi-time scale. response, and emergency demand response.

Fig. 2
Building large-scale air-conditioning load virtual peak regulation logic chart

Global optimization response
During global optimization of variables, the user "optimization algorithm" is built based on classification of regulation models. The optimization algorithm is used to screen user participation. Besides, the credible capacity boundary is built for the grid by setting up the global constrained optimization and controlling the mathematical model. Finally, the control objectives are identified via equipment calibration.

Fig. 3 Global optimization response schematic diagram
The constraint can be written as below: ,max 1 , Where, Particle swarm optimization (PSO) has advantages of easy realization, fast solution, strong global premium-seeking capacity and fewer parameters. These advantages enable PSO to efficiently realize power consumption by combining the boiler and the distributed power. To start with, an n-dimension data array can be built to represent multiple users. Then, the optimum-seeking method is adopted for screening. Next, the constraint and the optimization objective function are used to obtain the simulation results.

Conclusions
The boiler and air-conditioner regulation method aiming at realizing the grid peak transfer can contribute to friendly interaction between the grid and the users. It is an important method and critical link for the grid company to realize load regulation on the power use side of residents. Results suggest that the boiler load smart regulation method proposed in this paper can help reduce the grid peak load and cut the grid operation and construction input.
Therefore, influence of the boiler load on safety, stability and economical operation of the grid should not be ignored. The technological, economic and administrative methods of the power demand side should be combined to realize efficient management of the air-conditioning load, effectively alleviate the conflicts between power supply and demand, and ensure steady and safe operation of the