Multi-stage optimal design of energy systems for urban districts

Optimal design of regional integrated energy systems (RIES) offers great potential for better managing energy sources, lower costs and reducing environmental impact. To capture the transition process from fossil fuel to renewable energy, a flexible RIES, including the traditional energy system (TES) based on the coal and biomass based distributed energy system (BDES), was designed to meet a regional multiple energy demand. In this paper, we analyze multiple scenarios based on a new rural community in Dalian (China) to capture the relationship among the energy supply cost, increased share of biomass, system configuration transformation, and renewable subsidy according to regional CO2 emission abatement control targets. A mixed integer linear programming (MILP) model was developed to find the optimal solutions. The results indicated that a 40.58% increase in the share of biomass in the RIES was the most cost-effective way as compared to the separate TES and BDES. Based on the RIES with minimal cost, by setting a CO2 emission reduction control within 40%, the RIES could ensure a competitive total annual cost as compared to the TES. In addition, when the reduction control exceeds 40%, a subsidy of 53.83 to 261.26 RMB/t of biomass would be needed to cover the extra cost to further increase the share of biomass resource and decrease the CO2 emission.

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Implementing Data Reduction Strategies for the Optimal Design of Renewable Energy Systems

Process Integration and Optimization for Sustainability ◽

10.1007/s41660-021-00196-1 ◽

2021 ◽

Author(s):

Jorge Luis Tena-García ◽

Luis Miguel García-Alcala ◽

Dulce Celeste López-Díaz ◽

Luis Fabián Fuentes-Cortés

Keyword(s):

Renewable Energy ◽

Optimal Design ◽

Data Reduction ◽

Energy Systems ◽

Renewable Energy Systems ◽

Reduction Strategies

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Design and Optimization of Integrated Distributed Energy Systems for Off-grid Buildings

Journal of Energy Resources Technology ◽

10.1115/1.4052619 ◽

2021 ◽

pp. 1-27

Author(s):

Jian Zhang ◽

Heejin Cho ◽

Pedro Mago

Keyword(s):

Energy Storage ◽

Optimal Design ◽

Power Systems ◽

Thermal Energy ◽

Waste Heat ◽

Carbon Dioxide Emission ◽

Energy Systems ◽

Solar Thermal ◽

Solar Thermal Energy ◽

Distributed Energy

Abstract Off-grid concepts for homes and buildings have been a fast-growing trend worldwide in the last few years because of the rapidly dropping cost of renewable energy systems and their self-sufficient nature. Off-grid homes/buildings can be enabled with various energy generation and storage technologies, however, design optimization and integration issues have not been explored sufficiently. This paper applies a multi-objective genetic algorithm (MOGA) optimization to obtain an optimal design of integrated distributed energy systems for off-grid homes in various climate regions. Distributed energy systems consisting of renewable and non-renewable power generation technologies with energy storage are employed to enable off-grid homes/buildings and meet required building electricity demands. In this study, the building types under investigation are residential homes. Multiple distributed energy resources are considered such as combined heat and power systems (CHP), solar photovoltaic (PV), solar thermal collector (STC), wind turbine (WT), as well as battery energy storage (BES) and thermal energy storage (TES). Among those technologies, CHP, PV, and WT are used to generate electricity, which satisfies the building's electric load, including electricity consumed for space heating and cooling. Solar thermal energy and waste heat recovered from CHP are used to partly supply the building's thermal load. Excess electricity and thermal energy can be stored in the BES and TES for later use. The MOGA is applied to determine the best combination of DERs and each component's size to reduce the system cost and carbon dioxide emission for different locations. Results show that the proposed optimization method can be effectively and widely applied to design integrated distributed energy systems for off-grid homes resulting in an optimal design and operation based on a trade-off between economic and environmental performance.

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