8 research outputs found
Preemptive demand response management for buildings
A building energy management system (BEMS), which forms an integral part of a smart grid, enables building operators to monitor, manage, and control the energy utilized in their buildings, thus reducing the demand and consumption of energy. Building operators are responsible for the day-to-day maintenance and operation of their buildingsâ heating, cooling, mechanical, and electrical systems. This paper proposes an intelligent preemptive demand response management (DRM) using the BEMS to ensure contracted capacity or demand limit (CC/DL) is not exceeded and at the same time reduce energy consumption in buildings. In this paper, dynamic electric vehicle (EV) charge scheduling, speed control of air conditioning (AC) systemâs variable speed drive (VSD), and priority-based load shedding are considered in the DRM program. The performance of the proposed DRM program to keep the building power demand within the CC/DL and reduce the energy consumption is tested and analyzed using the BEMS.Accepted versio
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Sustainable Campus with PEV and Microgrid
Market penetration of electric vehicles (EVs) is gaining momentum, as is the move
towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a
significant portion of transportation energy use onto building electricity meters. Hence,
integration strategies for energy-efficiency in buildings and transport sectors are of increasing
importance. This paper focuses on a portion of that integration: the analysis of an optimal
interaction of EVs with a building-serving transformer, and coupling it to a microgrid that
includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang
Technological University (NTU), Singapore campus. The system under study is the Laboratory
of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy
Management System (MG-EMS) project. The paper analyses three different case scenarios to
estimate the number of EVs that can be supported by the building transformer serving LaCER.
An approximation of the actual load data collected for the building into different time intervals is
performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be
supported by the transformer with and without the microgrid are analyzed. The numbers of
possible EVs that can be charged at any given time under the three scenarios are also determined.
The possibility of using EV fleet at NTU campus to achieve demand response capability and
intermittent PV output leveling through vehicle to grid (V2G) technology and building energy
management systems is also explored
Recommended from our members
Sustainable Campus with PEV and Microgrid
Market penetration of electric vehicles (EVs) is gaining momentum, as is the move
towards increasingly distributed, clean and renewable electricity sources. EV charging shifts a
significant portion of transportation energy use onto building electricity meters. Hence,
integration strategies for energy-efficiency in buildings and transport sectors are of increasing
importance. This paper focuses on a portion of that integration: the analysis of an optimal
interaction of EVs with a building-serving transformer, and coupling it to a microgrid that
includes PV, a fuel cell and a natural gas micro-turbine. The test-case is the Nanyang
Technological University (NTU), Singapore campus. The system under study is the Laboratory
of Clean Energy Research (LaCER) Lab that houses the award winning Microgrid Energy
Management System (MG-EMS) project. The paper analyses three different case scenarios to
estimate the number of EVs that can be supported by the building transformer serving LaCER.
An approximation of the actual load data collected for the building into different time intervals is
performed for a transformer loss of life (LOL) calculation. The additional EV loads that can be
supported by the transformer with and without the microgrid are analyzed. The numbers of
possible EVs that can be charged at any given time under the three scenarios are also determined.
The possibility of using EV fleet at NTU campus to achieve demand response capability and
intermittent PV output leveling through vehicle to grid (V2G) technology and building energy
management systems is also explored