Environmentally Constrained Optimal Dispatch Method for Combined Cooling, Heating, and Power Systems Using Two-Stage Optimization

Abstract

The reliance on coal-fired power generation has gradually reduced with the growing interest in the environment and safety, and the environmental effects of power generation are now being considered. However, it can be difficult to provide stable power to end-users while minimizing environmental pollution by replacing coal-fired systems with combined cooling, heat, and power (CCHP) systems that use natural gas, because CCHP systems have various power output vulnerabilities. Therefore, purchasing power from external electric grids is essential in areas where CCHP systems are built; hence, optimal CCHP controls should also consider energy purchased from external grids. This study proposes a two-stage algorithm to optimally control CCHP systems. In Stage One, the optimal energy mix using the Lagrange multiplier method for state-wide grids from which CCHP systems purchase deficient electricity was calculated. In Stage Two, the purchased volumes from these grids were used as inputs to the proposed optimization algorithm to optimize CCHP systems suitable for metropolitan areas. We used case studies to identify the accurate energy efficiency, costs, and minimal emissions. We chose the Atlanta area to analyze the CCHP system’s impact on energy efficiency, cost variation, and emission savings. Then, we calculated an energy mix suitable for the region for each simulation period. The case study results confirm that deploying an optimized CCHP system can reduce purchased volumes from the grid while reducing total emissions. We also analyzed the impact of the CCHP system on emissions and cost savings.

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“…When integrating heterogeneous data of power grid operation logs, some common heterogeneous data source systems can be used. Common in this paper, virtual view technology is used to obtain users' data query requests [17][18][19][20] to generate an effective heterogeneous data integration system of power grid operation logs. At this point, it is necessary to calculate the aggregation processing probability of heterogeneous information , as shown in (1) below…”

Research on real-time storage of hybrid data for multi-task dispatching of power grid supported by new mining method

“…Research indicates several critical issues in the current multi-task hybrid data storage and scheduling of the smart grid. Firstly, there is a low integration of power grid data and information, leading to information islands and hindering data sharing and interaction, resulting in abnormal data storage processes [11][12][13]. Secondly, power grid data is rapidly expanding, while existing storage media is struggling to keep up, leading to the risk of data overflow.…”

The Selection of the Most Cost-Efficient Distributed Generation Type for a Combined Cooling Heat and Power System Used for Metropolitan Residential Customers

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