Time-Domain Modeling of Grid-Connected CHP for Its Interaction With the Power Grid

Abstract

This paper presents a nonlinear dynamic model of grid-connected combined heat and power system (CHP) that can effectively simulate the thermoelectric interaction and examine the impact of the CHP on the power grid. Based on the theorems of mass balance and energy balance, this paper studies and analyses the principles and dynamic characteristics of the main CHP components, including gas internal combustion engine, synchronous generator, waste heat exchanger, water storage tank, exhaust-heat boiler, and gas fired boiler. Then, the nonlinear time domain models for each component are built against input and output parameters in order to facilitate the study of CHP operation under various conditions. Subsequently, a simulation method that can deal with the coupling of all models with different time constants is proposed. Finally, dynamic simulation analysis of the developed CHP model is carried out on the MATLAB/Simulink. Extensive demonstration results show that the developed models are accurate to represent the thermoelectric interactions in the gird-connected CHP and capture the impact of this gird-connected CHPs on the power grid. This study is particularly beneficial to the design of new control strategies for CHPs to maximise its efficiency and stability value to the grid.

A Comprehensive Review and Qualitative Analysis of Micro-Combined Heat and Power Modeling Approaches

“…Time domain modelling and dynamic analysis of CHP connected to the power grid was performed by Xie et al [30]. Based on the mass and energy balance, this paper analyzed the principles and dynamic characteristics of the main CHP components, including gas internal combustion engine, synchronous generator, waste heat exchanger, water storage tank, exhaust-heat boiler, and gas fired boiler.…”

“…For the case of micro-CHP, the key governing equations of interest, representing the thermal availability are provided below: dθ represent rate of recoverable thermal loss from exhaust, cooling system and non-recoverable thermal loss to surrounding, respectively. Annand heat transfer model was used to calculate the heat transfer between cylinder wall and gas, as shown in Equation ( 28), the convective heat transfer coefficient (h c ) according Equation (29), and radiative heat transfer coefficient (h r ) according to Equation (30):…”

Robust Optimal Scheduling of EHG-IES Based on Uncertainty of Wind Power and PV Output

“…In [18], the role of HS in the optimal expansion for multienergy systems is analyzed. Also, the work in [19,20] develops a model of the thermoelectric components in CHP to accurately respond to thermoelectric interactions and improved efficiency and stability. e work in [21] introduces a microgrid scheduling model containing different energy sources under different scenarios to enhance energy scheduling.…”

Modeling of integrated heat‐electricity systems considering integrated demand response and dynamic behaviors of district heating network

“…Through the cascade utilization of various types of energy, grid connection of a large number of renewable energy, and energy interconnection, IESs can fully use the advantages of different kinds of energy and realize the improvement of energy efficiency 1‐2 . Specifically, compared with the traditional energy systems, which supply power and heat separately, with efficiency 30% ~ 35%, the energy efficiency of integrated heat‐electricity systems (IHESs) can exceed 80% 3‐4 . So, energetically developing combined electricity‐heat is one of the important directions for promoting high‐efficiency heating.…”