Abstract
Application of local energy resources in the buildings encounters such systems with both uncertainties in the produced power and failures (events) of the resources. The energy planning excluding uncertainty and events may be economically efficient but it is not resilient and practical. This paper provides a platform for energy management in the building under a set of realistic failures and uncertainties. The energy resilience is improved and the energy cost is decreased at the same time while all events and uncertainties are modeled. A typical building integrated with solar-battery-grid is studied. The resilience index is to minimize the loss of demanded service following all possible events. Three objective functions are defined and compared including (i) resilience cost, (ii) energy cost, (ii) resilience and energy costs together. The stochastic mixed integer linear programming is implemented to minimize the objective functions. The results validate that the developed toolkit can cope with all events and uncertainties with minimum operating cost and maximum resilience. The optimal tradeoff between operating cost, resilience, and uncertainty is presented. The results demonstrate that the uncertainty and resilience increase the planning cost by 5.3% and 13.8%, respectively, and both of them together increase the cost by 19.5%.
Highlights
The proposed model by this paper studied the correlation of resilience and uncertainty in the building energy management
The uncertainty is modeled by set of scenarios and the resilience is modeled through set of failures
The results demonstrate that the third objective function finds the best solution and optimizes both the energy cost and resilience cost simultaneously
Summary
Csshce,tdh Cnsect,th Ebrate Pbrate Plosca,dfa,ts,th Pnreatte Pssocla, rfa,ts,th R fa Energy and resilience cost ($/year). Penalty cost for unsupplied load ($/kWh) Cost of electricity from grid ($/kWh) Rated capacity of storage unit (kWh) Rated power of storage unit (kW) Load power (kW) Rated power of line from building to grid (kW) Solar power (kW) Probability of fault
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