Abstract
The hybridization of two or more energy sources into a single power station is one of the widely discussed solutions to address the demand and supply havoc generated by renewable production (wind-solar/photovoltaic (PV), heating power, and cooling power) and its energy storage issues. Hybrid energy sources work based on the complementary existence of renewable sources. The combined cooling, heating, and power (CCHP) is one of the significant systems and shows a profit from its low environmental impact, high energy efficiency, low economic investment, and sustainability in the industry. This paper presents an economic model of a microgrid (MG) system containing the CCHP system and energy storage considering the energy coupling and conversion characteristics, the effective characteristics of each microsource, and energy storage unit is proposed. The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). The test results show that the GSA-RFR model improves prediction accuracy and reduces the generalization error. The detail of the MG network and the energy storage architecture connected to the other renewable energy sources is discussed. The mathematical formulation of energy coupling and energy flow of the MG network including wind turbines, photovoltaic (PV), CCHP system, fuel cell, and energy storage devices (batteries, cold storage, hot water tanks, and so on) are presented. The testing system has been analysed under load peak cutting and valley filling of energy utilization index, energy utilization rate, the heat pump, the natural gas consumption of the microgas turbine, and the energy storage unit. The energy efficiency costs were observed as 88.2% and 86.9% with heat pump and energy storage operation comparing with GSA-RFR-based operation costs as 93.2% and 93% in summer and winter season, respectively. The simulation results extended the rationality and economy of the proposed model.
Highlights
Muhammad Shahzad Nazir,1 Sami ud Din,2 Wahab Ali Shah,2 Majid Ali,2 Ali Yousaf Kharal,3 Ahmad N
The CCHP system can cool and heat during power supply and these energy sources cannot be absorbed in the system at the same time, resulting in low energy utilization or waste [23]. erefore, to meet the constraints of the distributed microsource and energy storage unit operating characteristics, energy supply, and demand balance, the advantage of the proposed gravitational search algorithm (GSA)-random forest regression (RFR) model is its generalization ability
This paper proposes the GSA-RFR approach in the CCHP operation scheduling model including heat pumps and energy storage units into the MG system. e detailed scheduling model for MGs with heat pumps and energy storage including wind turbines, photovoltaic cells, microgas turbines, ground source heat pumps, and energy storage units is presented
Summary
In grid-connected insulated modes, the characteristics of MG are flexible operating and can improve grid efficiency and safety [24]. Ese storage devices are connected to the upstream power generation grid using photovoltaic panels, wind farms, fuel cells, CCHP system, and microturbines (e.g., batteries or super-capacitor) [27]. As a part of the point of view of the customers, the MG can be designed carefully to meet the requirements for reliability as well as energy savings, improving efficiency, minimizing voltage sag, and powering a continuous current [28]. The system’s renewables do not supply a steady stream, matching supply needs as they change, and as a result, the MG system oscillators often do not lower loads or alter their frequency. When the supply of cold (heat) power is insufficient, it can be used to make up the shortage while the gas boiler is used as auxiliary supply equipment for cold (heat) load [31, 32]. e energy storage unit consists of three parts, battery, cold storage, and hot water storage tank. e voltage level of the MG system is 380 V, which is connected to the 10 kV medium-voltage distribution parameter through a common node
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