Energy Management of a Cluster of Buildings in a University Campus

Sima, Catalina Alexandra; Popescu, Mihai Octavian; Popescu, Claudia Laurenta; Alexandru, Monica; Popa, Luiza; Dumbrava, Virgil; Panait, Cornel

doi:10.1109/atee52255.2021.9425325

Cited by 8 publications

(8 citation statements)

References 10 publications

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“…The uncertainties in the production from renewable energy sources were investigated in Ref. [46], where different scenarios of the production of renewable energy source (photovoltaic installation) were considered. Thus, considering the large variations of the electricity prices in Europe occurring in the last years, a stochastic optimization model for accounting the variations, through statistical scenarios with certain probability, of the electricity prices which highly impact the administrative operation of a university campus was proposed and implemented.…”

Section: Optimization Model For the University Energy Communitymentioning

confidence: 99%

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Techno-economic assessment of university energy communities with on/off microgrid

Sima

Popescu

et al. 2022

Renewable Energy

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Section: Optimization Model For the University Energy Communitymentioning

confidence: 99%

“…The energy management of a university campus in Romania under various electricity market strategies was investigated in Ref. [36]. A hybrid energy system proposed for a college in India considering the on-grid and off-grid operation was modeled and simulated in Ref.…”

Section: Introductionmentioning

confidence: 99%

Techno-economic assessment of university energy communities with on/off microgrid

Sima

Popescu

et al. 2022

Renewable Energy

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“…• Constraints that model fuzziness Constraint (15) defines the cost satisfaction variable (λ_C). The cost of the equipment installed (left side of the inequality: wind turbines, PV panels, controllers, batteries, inverters, meters and LV lines) ranges between the minimum cost (C MIN , for full satisfaction λ_C = 1) and the maximum cost (C MAX = C MIN + ∆C, for null satisfaction λ_C = 0).…”

Section: Objective Functionmentioning

confidence: 99%

“…For instance, Raji and Luta [14] used HOMER to design a community microgrid in South Africa, obtaining a technically and economically viable solution. Other optimization methods, such as integer linear programming, have also been used to evaluate wind-PV systems [15]. On the other hand, the distribution of electricity from generators to end users has been less studied [16], with the particular context of medium-dispersed communities receiving even less attention.…”

Section: Introductionmentioning

confidence: 99%

Balancing Cost and Demand in Electricity Access Projects: Case Studies in Ecuador, Mexico and Peru

et al. 2022

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Rural areas in developing countries have the highest concentrations of unelectrified communities. There is a clear link between electricity consumption and the Human Development Index, as highlighted by the 7th Development Goal of the United Nations. Estimating the energy needs of the previously nonelectrified population is imprecise when designing rural electrification projects. Indeed, daily energy demand and peak power assessments are complex, since these values must be valid over the project’s lifetime, while tight budgets do not allow for the systems to be oversized. In order to assist project promoters, this study proposes a fuzzy mixed integer linear programming model (FMILP) for the design of wind–PV rural electrification systems including uncertainty in the demand requirements. Two different FMILP approaches were developed that maximized the minimum or the average satisfaction of the users. Next, the FMILP approaches were applied to six Latin American communities from three countries. Compared with the deterministic MILP (where the energy and peak power needs are considered as specific values), the FMILP results achieved a better balance between the project cost and the users’ satisfaction regarding the energy and peak power supplied. Regarding the two approaches, maximizing the users’ minimum satisfaction obtained globally better solutions.

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“…While effective in reducing energy costs, the study's focus on one case and lack of environmental impact assessment limit its broader applicability, indicating a need for further research on environmental implications and comparison with other strategies. Sima et al (2021) aimed to optimize energy consumption and reduce costs in educational buildings with photovoltaic installations and hybrid systems. Ullah et al (2021) developed an optimal energy management system for university campuses, utilizing a hybrid Firefly Lion Algorithm to schedule appliances and integrate renewable energy sources, effectively decreasing energy costs and consumer waiting times.…”

Section: Introductionmentioning

confidence: 99%

Eco-Friendly Energy Efficient Classrooms and Sustainable Campus Strategies: A Case Study on Energy Management and Carbon Footprint Reduction

Patil,

Tanavade

2024

IJEEP

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This research paper presents a comprehensive study on energy management and carbon footprint reduction in an educational institutional campus. It focuses on implementing energy-efficient technologies and practices to minimize energy consumption and environmental impact. The study encompasses four cases, each addressing different aspects of energy use in a university setting, including the installation of LED lighting, programmable remote switches, and high-efficiency air conditioning systems. The methodology involves a detailed analysis of energy consumption patterns, using smart energy meters and theoretical calculations. Case I establishes a baseline energy consumption, while subsequent cases implement energy-saving measures. Case II involves replacing traditional tube lights with energy-efficient LED lights, resulting in considerable energy savings. Case III extends these savings further by integrating programmable remote switches mapped with student timetables. Finally, Case IV proposes the replacement of older air conditioning units with 25 SEER models, leading to significant reductions in energy use. The results highlight the effectiveness of these interventions. Case II achieves a 66.67% energy saving, while Case III yields up to 77.78% energy saving in lighting and 33.34% in air conditioning. In Case IV, the adoption of high-efficiency air conditioners can result in a 52% energy saving during teaching weeks. The economic benefits of these measures are substantial, with cost savings per classroom ranging from 7.65% in Case II to 53.46% in Case IV. Moreover, the environmental impact of these energy conservation techniques is substantial. The study reports reductions in carbon emissions from 14.71metric tons of carbon dioxide equivalent (MT CO2e) in base Case I to 6.85 MT CO2e in Case IV. The overall carbon emission reductions for Cases II, III, and IV are 7.61%, 36.37%, and 53.43%, respectively. This study demonstrates the profound impact of integrated energy management strategies in reducing the carbon footprint and energy consumption in educational institutions, offering a model for sustainable and economically viable operations.

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Energy Management of a Cluster of Buildings in a University Campus

Cited by 8 publications

References 10 publications

Techno-economic assessment of university energy communities with on/off microgrid

Techno-economic assessment of university energy communities with on/off microgrid

Balancing Cost and Demand in Electricity Access Projects: Case Studies in Ecuador, Mexico and Peru

Eco-Friendly Energy Efficient Classrooms and Sustainable Campus Strategies: A Case Study on Energy Management and Carbon Footprint Reduction

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