Optimal Configuration of the CHP System Using Stochastic Programming

Abstract

This study presents a reliability-constrained optimization approach to determine the number and size of combined heat and power (CHP) system components, including CHP units, auxiliary boilers, and heat-storage tanks. To this end, the loss-of-load expectation and the expected energy not supplied are considered since the reliability indices ensure the security of operation. The load forecasting inaccuracy and the random outages of CHP system components as well as the loss of mains are modeled as a scenario tree using the Monte Carlo sampling approach. The problem is formulated as two-stage stochastic mixed integer linear programming. A scenario reduction technique is also introduced to reduce the computational burden of the scenario-based planning problem. Finally, the proposed model is applied to a large residential complex in Tehran as a case study.

An Intelligent Hybrid Energy Management System for a Smart House Considering Bidirectional Power Flow and Various EV Charging Techniques

“…A HES consists of two or more energy resources operated together to obtain an improved efficiency and a better energy balance. Due to advanced technology, compact and high-efficiency micro-combined heat and power systems (micro-CHP) are gaining popularity at domestic level [2][3][4][5][6][7]. According to the American Council for an Energy-Efficient Economy's report, the modern CHP systems can work at an efficiency as high as 80% in contrast to the commonly prevailing methods of generating electricity and thermal power separately, which have a lower combined efficiency of 45% [8].…”

“…The application of micro-CHP systems for domestic use is reported to yield benefits such as reduced CO 2 emission [2], and an improved operational economy [3][4][5]. The study in [6] analyzes different design options of fuel cell (FC) working as micro-CHP systems in residential buildings.…”

“…However, a combined operation of HES and EVs in a bidirectional power network requires further attention as the present environmental and economic concerns call for their integrated operation at the SH level. The studies mentioned above do not address their combined role and/or do not present an optimized schedule of electrical and thermal loads (e.g., [3][4][5][6][7]10,11,14,[16][17][18][19][20][21][22]). Similarly, the increased role of EV loading and impact of its charging methods require special attention as the EVs make up a major part of the electric load in an SH.…”

Stochastic model predictive control for optimal energy management of district heating power plants

“…It is shown how thermal storage can significantly increase CHP flexibility to respond to real time market signals. In [17] a two-stage stochastic MILP model is designed to determine the optimal number and size of CHP system components. The authors in [18] propose a two-stage stochastic programming framework to optimize the use of a thermal energy storage in the form of hot water storage and/or storage in building material.…”

Optimization of Fluctuation Suppression in Photovoltaic Power Generation Using Gas Cogeneration System

“…On the other hand, the introduction of the controllable distributed power systems such as the gas cogeneration systems are also increasing in recent years. Cogeneration (cogen) comes from Combined Heat and Power, which is a simultaneous process of producing heat and electricity [4], [5]. Different kind of fuels can be used to facilitate cogeneration.…”