Optimal Renewable Energy Configuration in Smart Cities Considering Shortened Annual Simulation Soichiro Ueda a,∗ , Ashraf Mohamed Hemeida b , Narayanan Krishna c , Shriram Srinvasarangan Rangarajan d,e , Edward Randolph Collins e , Alexey Mikhaylov f , Hiroshi Takahashi g and Tomonobu Senjyu a a Faculity of Engineering, University of the Ryukyus, Senbaru Nishihara-cho, Nakagami, 903-0213, Okinawa, Japan b Faculty of Energy Engineering, Aswan University, 82825, Aswan, Egypt c Department of Electrical and Electronics Engineering, SASTRA Deemed University, 613401, Thanjavur, India d Department of Electrical and Electronics Engineering, SR University, 506001, Warangal Telangana, India e Department of Electrical and Computer Engineering, Clemson University, 29634, Clemson South Carolina, USA f Financial Research Institute, Ministry of Finance of the Russian Federation, 127006, Moscow, Russia g Fuji Electric Co., Ltd., 141-0032, Tokyo, Japan ARTICLE INFO Keywords: Smart City Photovoltaic (PV) power Wind power generation(WG) Storage Battery Clustering Combined Cooling Heating and Power(CCHP) Mixed integer linear programming(MILP) 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. To solve this problem, cities are being converted into smart cities. 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®. 1. Introduction In recent years, the concentration of population in urban areas has become a problem in the world [1]. As Japan’s population shrinks, the concentration of the population in urban areas is increasing, and it will continue to grow in the future as people seek convenience. The concentration of population in urban areas can cause more people to have access to better education and medical care, while at the same time causing environmental degradation due to air pollution and other factors, increased vulnerability to natural disasters such as earthquakes and typhoons, and the need for huge power supply and infrastructure facilities. In order to solve these problems, cities are transitioning to smart cities. As an example of smart cities, smart cities are being promoted in cities such as Copenhagen in Denmark, Bologna in Italy and New York in the United States [2]. The smart city project is expected to continue to advance through public and private sector collaboration. Conventional large-scale thermal power generators do not use the waste heat effectively, which leads to deteriorated thermal efficiency and environmental impact. The construction of additional large-scale thermal power generators is not a viable option to supply enormous amounts of electricity because of the adverse effects of causing further environmental degradation. To counteract the above mentioned problems, efficient energy management, improved utilization and government services, environmental countermeasures are needed. As a measure to address environmental issues, renewable energy sources that do not emit carbon dioxide or other greenhouse gases when generating electricity energy is in the spotlight [3, 4, 5]. In addition, in order to solve the problems of fossil fuel depletion and global warming, renewable energy power generation facilities that do not depend on fossil fuels and do ∗ Corresponding author. Tel.:+89-98-895-8686 ∗∗ E-mail address: soichiro.55.ueda@gmail.com ORCID(s): 0000-0002-8734-162X (S. Ueda) Soichiro Ueda et al.: Preprint submitted to Elsevier Page 1 of 13 Electronic copy available at: https://ssrn.com/abstract=4164019