Development of an integrated infrastructure simulator for sustainable urban energy optimization and its application

https://doi.org/10.1016/j.seta.2020.100710Get rights and content

Highlights

  • We developed an integrating infrastructure simulator which optimizes the energy planning.

  • The simulator considers supply, demand and network between supplier and user.

  • After verification of simulator, the simulator is applied to Hamamatsu city, Japan.

  • Several sustainable solutions which include the new business model to Hamamatsu city are found.

Abstract

We developed a comprehensive infrastructure simulator that optimizes the energy consumption of the city. The entire optimization of the simulator—including the planned network connecting the demand side to the supply side of the city—is a notable feature of the machine. The demand side equipment (air conditioning heat source type) and supply side infrastructure (system power, distributed power source, renewable energy, etc.) was prepared in advance considering the appropriate boundary conditions (electricity demand, weather, characteristics, etc.) of the city. Among these combinations, an optimal combination that maximizes an objective function (primary energy minimization, CO2 minimization, and cost minimization) that is an index for optimization is obtained by a genetic algorithm. Applying the developed simulator to Hamamatsu City, makes it possible to determine a new combination of photovoltaics (PV) + electrified air conditioning heat source as well as a typical combination of gas engine + exhaust heat recovery type air conditioning heat source. In the future, we propose applying the development simulator to more cases to verify its effectiveness.

Introduction

In Japan, due to population decline and aging, the productive labor force, tax revenues, and public infrastructure is deteriorating rapidly. Under these circumstances, local governments are expected to expand their duties, such as quasi-public services represented by welfare medicine, despite increasing social capital maintenance costs. Furthermore, they are prepared to confront the shrinking public services. As a measure to remedy this situation, the creation of smart communities that improve the energy balance of the region and revitalize industrial and civic activities (i.e., the creation of renewable energy suitable for the region) requires attention.

On the other hand, considering energy trends, it is assumed that oil and gas prices will continue to remain high, but it is also pointed out that the unit price of solar power generation may be lower than coal-fired power [2]. Considering these issues and energy trends, it is possible to achieve a healthy energy balance in the region by ensuring a proper distribution system while utilizing a wide variety of renewable energy sources and making optimal arrangements. Moreover, it is possible to build a sustainable community by redistributing income from the energy balance and expanding public services. To achieve this, the optimization of energy facilities is indispensable.

This report proposes development of integrating a simulator of infrastructures to facilitate the optimization of energy planning. Rational optimization of energy planning is a part of the most important topics. On the other hand, when we discuss the energy planning and its optimization in the city, energy supply, power consumption, and networks between suppliers and users should be included simultaneously. Nevertheless, energy planning has never been executed in such an integrating way. As far as the author knows, there were not any studies to discuss such an integrating simulator.

Many tools have been proposed to formulate future energy plans, especially renewable energy deployment scenarios [4], [8], [9], [14], [15], [20], [23], [25], [26]. Particularly, Zeng, Cai, Huang, and J. widely reviewed systems analysis and optimization modeling for low-carbon energy systems planning with the consideration of uncertain greenhouse gas (GHG) emission reduction. Future energy planning using these tools will bring very important insights and can be expected to make an important contribution to future smart city designs. Table 2.1 summarizes the existing optimization tool with proposed one.

Not only tools of energy planning, optimization of infrastructure networks topology is becoming common [12], [22], [24]. Each tool has own object functions and can contribute to the purpose. On the other hand, in the case of urban energy, particularly power, it is clearly composed of a demand side related to air conditioning and similar needs, the supply side related to system power and distributed power, and a network connecting them. Water, gas, and other infrastructure are also critical components of the supply, demand, and network. However, in the past, these three components have been individually optimized. We have developed a comprehensive infrastructure simulator with the following characteristics based on the hypothesis that overall optimization of the demand-supply network is a vital need. In this paper, we first introduce the features and structure of the simulator. Specifically, we applied the simulator to the core district including the city hall of Hamamatsu City and obtained interesting results. Further, the optimization of network topology in a green field is described.

Section snippets

Overall features

In this simulator, as shown in Fig. 2.1, thorough optimization of the demand-supply network is considered. For the boundary conditions, we considered power and heat demands, weather conditions (temperature, solar radiation, wind speed, etc.), community characteristics (commercial cities, industrial cities, rural areas, etc.; consider characteristics mainly through demand curves), domestic energy basic plan (primary energy of electricity, CO2 conversion factor), future vision (population, low

Application of simulator to Hamamatsu City

This comprehensive infrastructure simulator was implemented at the core district, which is the center of Hamamatsu city. The area includes essential facilities such as the Hamamatsu Joint Survey, Enshu Hospital, Shizuoka University of Culture and Arts, Higashi Elementary School, and a pumping station. The main facilities were investigated and analyzed considering their energy demand. The assumed conditions are summarized below.

The entire core area was optimized using a comprehensive

Optimization of network topology

As shown, the developed tool can optimize the energy utilities considering the demand and supply sides. This tool includes the optimization function of the network between supply and demand sides. In this paper, the example of water supply network on a green field is described. The nodal analysis of the water supply network is performed as follows:

The relationship between the inflow amount Qi of the node i and the outflow amount qij between the nodes i and j is as follows:-Qi=i=1mqijwhere

Conclusions

The features of this method are summarized as follows.

  • 1)

    The tool takes into account demand and supply, as well as the infrastructure networks that connect them, which are important in urban energy planning, and determines the optimal energy plan.

  • 2)

    The LCEM is used for the evaluation of the supply. The LCEM has many air conditioning options and distributed power sources such as diesel generators. In addition, a solar power generation model and a storage battery model are added.

  • 3)

    Genetic algorithm is

CRediT authorship contribution statement

Shinichi Inage: Conceptualization, Methodology, Validation, Writing - review & editing. Yoshiyuki Uchino: .

Acknowledgements

We received a great deal of guidance and support from the Energy Policy Division and the Hamamatsu City Office for this research. I would like to express my gratitude for those who have contributed to this study.

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