Smart-Energy-Sharing Scenarios Based on Actual Usage in the Community

. The purpose of this study is to develop an energy sharing scenario for buildings within the community. This work developed an energy sharing scenario for buildings in a community consisting of several types of buildings. The community are mainly composed of low-rise building, including offices. Six buildings with energy usage measurement equipment installed in the community were selected and the energy use status of the building was measured. The electric energy consumption and electric energy production of buildings were predicted using a simulation program. Electrical energy was produced using photovoltaic panels installed in buildings. Energy consumption patterns of buildings were analysed. There are four scenarios in which the energy produced is shared with each building. The first scenario uses photovoltaic as much power as it generates, and does not use surplus power. The second scenario is to reverse transmission the surplus power to the source. The third scenario is to store surplus power in the ESS and use it for the next day's peak load. The fourth scenario is to collect surplus power into the Community's ESS and share it with the most energy-intensive buildings. After comparing the four developed scenarios, it was found the most efficient and optimal sharing scenario based on buildings in the community. Results can be used as a method for sharing electrical energy produced using photovoltaic system in a small-scale community.


Introduction
Global electricity energy usage is expected to increase by 2.1% annually by 2040 [1], and global energy usage is expected to increase by 19-24% by 2040 compared to 2018 [2]. According to the European Union (EU) Energy Usage Survey, the building sector accounts for 40% of the total energy use [3]. Therefore, in order to reduce energy use, efforts are needed in the building sector, which accounts for a large portion of energy use.
Recently, buildings are not simply the subject of energy consumption, but also the transition to prosumer who produces and sells energy in buildings [4]. The production of energy in buildings generates surplus power, and effective consumption of surplus power can be solved through energy sharing [5].In the recent study [5][6][7], studies that effectively share the energy and usage produced in buildings have been conducted.
However, when energy use and production are simultaneously carried out in buildings, research on sharing energy efficiently from an electricity bill system or cost perspective is insufficient. Therefore, in this study, a scenario for sharing energy between buildings was developed for a small community of 12 buildings. The energy consumption and production of each building were reviewed, and after developing a smart energy sharing scenario, the saving of electricity bills was analysed using the Electricity contract in Korea. In order to analyse the effect of Smart-Energy-Sharing Scenarios, a community of 12 buildings located in Siheung-si, Gyeonggi-do, Korea was targeted. Six buildings with energy usage measurement equipment installed in the community were selected and the energy use status of the building was measured. Energy usage was measured for the entire building. The measurement period is one year from January to December 2021. Fig. 1 shows the composition of the target community, and Fig. 2 shows the panoramic view of the buildings. Table 1 shows the current status of the target building. All six buildings are low-rise buildings with six stories or less, mainly offices, libraries, gym and auditoriums. The structure of all buildings is reinforced concrete.

Photovoltaic simulation
It was assumed that the energy production system for energy sharing generates energy using photovoltaic one of the new and renewable energy. Since photovoltaic capable of producing energy is not installed in the target building, energy production data were collected using simulations. The installation scale of photovoltaic facilities was modelled at a certain ratio compared to the roof area of the building described above. For the energy production of photovoltaic, production data for one year were generated using the EnergyPlus 9.3.0 program. Fig.  3 shows the modelling of buildings and photovoltaic for simulation. It was modelled using OpenStudio. Table 2 shows the installation ratio and installation area of the photovoltaic power generation system, and Table 3 shows the main input conditions of photovoltaic system for Energyplus simulation.   For the simulation, weather data from Seoul, which is closest to the area where the target community is located, was used. The Fig. 4 shows the results of analyzing the solar radiation data in Seoul.  Table 4 shows the energy sharing scenarios according to the energy usage and power generation developed in this study. Installation of ESS and CESS in each building, use for peak loads in each building, and share energy with the building with the highest electricity

Development energy sharing scenarios
In Scenario 1, ESS (Energy Storage System) is not installed. Energy is generated using photovoltaic and used as much as the amount of power generated, and surplus power when the amount of power generated is higher than the amount used is discarded. In Scenario 2, ESS is not installed as in Scenario 1. However, if the amount of power generated is higher than the amount used, the surplus power is sold back to the energy source and electricity rate is charged. In Scenario 3, ESS is installed in each building and surplus power when the amount of power generated is higher than the amount of use is stored in the ESS. The stored electricity is used for the peak load the next day, and if the energy use stored in the ESS is higher than the use at the peak load, the electricity is used up to the mid-peak load. In Scenario 4, a Community Energy Storage System (CESS) is installed. At the peak load in each building, the remaining surplus power is transmitted to CESS. After that, CESS shares surplus power in the buildings with the highest energy consumption. At this time, the building with the highest energy consumption does not use the supplied power only for the peak load, but also uses it at a time when the consumption is higher than the power generation. Table 5 shows Electricity contract in Korea. Electricity contract in Korea was investigated to analyse the scenario of reselling surplus power to power suppliers and calculate the effect of energy sharing as cost. In Korea, electricity charges are imposed according to the characteristics of each building group by dividing it into five types of building groups.

Electricity contract in Korea
The six buildings selected in this study are originally charged for electricity based on the entire community. However, it is assumed that six buildings are charged individually for energy sharing effect analysis. In addition, since the electricity rates charged each year are different, the electricity rates charged were calculated based on the rate system implemented on July 1, 2022.
One of the characteristics of Korea's Electricity Contract is that the customer, that is, the user, generates power and sells the remaining surplus power back to the supplier. The rate of reverse transmission power is calculated by multiplying the unit price of the weighted average system marginal price (SMP) by the reverse transmission power of the corresponding month time zone as shown in eq.1.

Analysis of energy usage and power generation
The measured electric energy usage of each building and the power generation calculated through simulation were analysed. Fig 2 shows the seasonal energy usage and power generation of each building.
In all buildings, energy use was higher than the amount of power generated using PV. Building A was found to have much higher usage than power generation. In Building E, power generation was found to be higher than the usage in spring-summer, and Building E is a gym, which is believed to be due to the relatively shorter use time of the building compared to other buildings. In general, the power generation of each building was higher in spring and summer than in autumn and winter, and energy use was different depending on the type of building.  Fig. 6 and Fig. 7 show the results of analysing the energy sharing effect and the corresponding cost according to each scenario presented scenario. The building with the highest energy usage in Scenario 3 was selected as Building A, which was shown to have the highest energy usage in Fig. 5. A comparison of building electricity rates showed that Scenario 1, which does not produce surplus energy, had the highest rate at 118,608,524, followed by Scenario 2 -4 -3 in order of electricity rates.   Table 4. shows the electricity rate saving ratio for each building based on Scenario 1. As a result of applying Scenario 2 and 3 to Building A, which uses the most energy, the savings were 1.3% and 1.9%. This is because the usage is high compared to the amount of power generated, so the surplus power is low. As a result of applying Scenario 2 and 3 to all buildings except Building A, the saving rate was greater than that of Scenario 1, which showed that electricity rates could be saved by utilizing surplus power. In particular, when Scenario 2 is applied to Building D and E, electricity rates are saved by 64.1% and 78.0%, respectively, compared to Scenario 0, so it is very effective in saving electricity rates if the electricity used for peak and mid loads is covered with surplus power in buildings with large power production. In the case of Scenario 4, where energy sharing between buildings takes charge of the peak load of each building with surplus power and shares power with Building A, which uses the most energy through CESS, saving electricity rate compared to Scenario 2, but less than Scenario 3.

Analysis of Energy Sharing Effects
As a result of applying the Scenario proposed in this study, buildings with very large electric energy usage have less effect of reducing electricity bills by ESS installation, and buildings with similar electric energy usage and power generation have greater effect of saving electricity bills by ESS installation and sharing.

Conclusion
In this study, an energy sharing scenario was developed using the measured energy usage and the PV power generation calculated by the simulation, and the effect was analysed. The energy sharing scenario assumes that energy sharing takes place in six buildings in the community, and the electricity contract in Korea was reviewed to confirm the cost saving effect.
As a result of applying four types of energy sharing scenarios, it was found that sharing energy with buildings with less energy use is more cost effective than sharing energy with buildings with high energy use. In addition, for buildings with similar electric energy usage and power generation, it is considered an effective way to use the generated energy first for buildings and share the remaining surplus electricity with buildings with high use. Korea's Electricity Contract had little effect on saving electricity rates obtained according to reverse transmission power. In the future, more energy sharing scenarios and research through effective energy usage analysis are needed.