Stochastic Optimization for Integration of Renewable Energy Technologies in District Energy Systems for Cost-Effective Use

Abstract

Stochastic optimization of a district energy system (DES) is investigated with renewable energy systems integration and uncertainty analysis to meet all three major types of energy consumption: electricity, heating, and cooling. A district of buildings on the campus of the University of Utah is used as a case study for the analysis. The proposed DES incorporates solar photovoltaics (PV) and wind turbines for power generation along with using the existing electrical grid. A combined heat and power (CHP) system provides the DES with power generation and thermal energy for heating. Natural gas boilers supply the remaining heating demand and electricity is used to run all of the cooling equipment. A Monte Carlo study is used to analyze the stochastic power generation from the renewable energy resources in the DES. The optimization of the DES is performed with the Particle Swarm Optimization (PSO) algorithm based on a day-ahead model. The objective of the optimization is to minimize the operating cost of the DES. The results of the study suggest that the proposed DES can achieve operating cost reductions (approximately 10% reduction with respect to the current system). The uncertainty of energy loads and power generation from renewable energy resources heavily affects the operating cost. The statistical approach shows the potential to identify probable operating costs at different time periods, which can be useful for facility managers to evaluate the operating costs of their DES.

Sustainable Solar Energy in Mexican Universities. Case Study: The National School of Higher Studies Juriquilla (UNAM)

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“…Karasmanaki and Tsantopoulos [9] researched the attitude of RES students in the Department of Forestry and Management of the Environmental and Natural Resources at the Democritus University of Thrace in Greece since they are possible experts in RES, and the results show that students support renewables and have awareness about current polluting energy systems. Tran and Smith [10] developed an analysis on renewable energy systems integration and uncertainty to meet the three major types of energy consumption: Electricity (solar photovoltaic and wind), heating (combined heat and power) and cooling (electricity) at facilities on the campus of the University of Utah. They found that the uncertainty of energy loads and power generation from renewable energy heavily affects the operating cost of the district energy system.…”

A Graph Theory-Based Method for Regional Integrated Energy Network Planning: A Case Study of a China–U.S. Low-Carbon Demonstration City

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Optimum Choice of Energy System Configuration and Storages for a Proper Match between Energy Conversion and Demands

“…Tran and Smith [7] propose a stochastic approach to minimize the operating cost of a district energy system (DES), including a CHP system, natural gas boilers, solar photovoltaics (PV), and wind turbines for generation of power, heating, and cooling. A district of buildings on a university campus is used as a case study.…”