Search

In the current situation of the energy crisis, the mining industry has been identified as a promising area for application of demand side management (DSM) techniques. This paper investigates the potential for energy-cost savings and actual energy savings, by implementation of variable speed drives to ventilation fans in underground mines. In particular, ventilation on demand is considered in the study, i.e., air volume is adjusted according to the demand at varying times. Two DSM strategies, energy efficiency (EE) and load management (LM), are formulated and analysed. By modelling the network with the aid of Kirchhoff’s laws and Tellegen’s theorem, a nonlinear constrained minimization model is developed, with the objective of achieving EE. The model is also made to adhere to the fan laws, such that the fan power at its operating points is found to achieve realistic results. LM is achieved by finding the optimal starting time of the mining schedule, according to the time of use (TOU) tariff. A case study is shown to demonstrate the effects of the optimization model. The study suggests that by combining load shifting and energy efficiency techniques, an annual energy saving of 2 540 035 kW h is possible, leading to an annual cost saving of USD 277035. [ABSTRACT FROM AUTHOR]

Abstract: Electric lighting consumes 19% of total electricity production worldwide. Open-plan offices constitute the majority of office stock, in which most office workers perform their daily tasks, and hence the lighting in those offices has significant impact on, not only energy usage, but also occupants’ productivity. This paper presents a unique lighting optimization approach for open-plan offices that is capable of tuning task lighting to each occupant''s preference in the most energy-efficient fashion. Exploiting individual controllability of the advanced networked lighting systems, each luminaire can be dynamically actuated at a different level to realize various lighting configurations without any physical rewiring. This research formulates lighting actuation into a linear programming problem and finds the optimal light outputs for each of the luminaires that collaboratively deliver specified lighting to each workstation while using the least amount of energy. Simulations using our lighting optimization approach have shown its versatility in providing proper workstation-specific task lighting under different requirements compared to business-as-usual practices. Energy savings are generated from tuning the light levels to occupants’ needs as well as keeping unoccupied areas unlit or minimally lit with this approach. [Copyright &y& Elsevier]