Optimal Renewable Energy Configuration in Smart Cities Considering Shortened Annual Simulation

Abstract

In the world, the concentration of population in urban areas has led to the problem of increasing load on urban infrastructure and greenhouse gases. This paper presents the optimal operation and capacity planning of a smart city with renewable energy and combined cooling, heating and power system. In this study, clustering is applied to reduce the simulation time while maintaining the accuracy of the solution. Furthermore, the optimal capacity is examined by varying the price of renewable energy with the generation capacity. As a result, the simulation time is reduced from 4,960 [sec] to 2.66 [sec], and the error of the result is 0.4[%]. Compared to the case without renewable energy, the9 Electricity rate is reduced by 67.0[%] and the CO2 emission by 55.9[%]. To further reduce the CO2 emission, the price of renewable energy facilities needs to be reduced. In the last part of the paper, we vary the price of PV equipment and determine the PV equipment price that minimizes the operating cost and CO2 emissions to be less than 240 million yen. The simulations in this paper are performed using the optimization method Mixed integer linear programming (MILP) and the numerical analysis software MATLAB®.

Keywords: Smart city, Photovoltaic(PV) power, Wind power generation(WG), Storage Battery, clustering, Combined Cooling Heating and Power(CCHP)