Modelling and Simulation of a Building Energy Hub ^†

Abstract

The development of technologies such as efficient multi-generation system, lead to realizing the benefits of integrated energy infrastructure such as electricity, natural gas, and heating networks, and thus a rapid movement toward multi-energy systems (MES). In such systems, different energy carriers and systems interact together in a synergistic way. An Energy hub (EH) can be defined as the place where the production, conversion, storage and consumption of different energy carriers takes place, is a promising option for integrated management of MES. In this work we present the hourly Schedule along a year of a building energy hub, with local generation of heat and power, energy storage and electrical and thermal loads. We include PVT systems and a CHP system in the local generation of heat and power, and a gas boiler. A battery is considered as electrical storage and a water tank as thermal storage. The system is connected to the mail grids of power and gas. The typical thermal and electrical load of a building has been considered, with a heat pump that is considered as a deferral load. The model for all the components has been developed, and a yearly simulation has been carried out in which prices of electricity and gas have been considered.

1. Introduction

An energy hub can be regarded as an input-output unit model integrating energy conversion, energy transport, energy storage and load dissipation, see Figure 1 [1].

Figure 1. Energy hub definition.

The basic mathematical model of energy hub system is

$$L=f \left(P\right)$$

(1)

In this formula, $L$ explicates the energy demand and $P$ demonstrates the power supply.

The basic matrix function of energy hub:

$$\left[\begin{array}{c}{L}_1\\ L_2\\ ⋮\\ L_n\end{array}\right]=\left[\begin{array}{ccc}{c}_{11} c_{12}& \cdots & c_{1m}\\ c_{12} c_{22}& \cdots & c_{2m}\\ {\begin{array}{c}⋮\\ c\end{array}}_{n1} {\begin{array}{c}⋮\\ c\end{array}}_{n2}& \ddots & {\begin{array}{c}⋮\\ c\end{array}}_{nm}\end{array}\right]\left[\begin{array}{c}{P}_1\\ P_2\\ ⋮\\ P_n\end{array}\right]$$

(2)

In this expression, cth is coupling factor, which represents the conversion efficiency between the ith form energy input and the jth form energy output.

Because energy hub has high abstract characteristics, no matter how heterogeneous a system is, it can be expressed in energy hub. In an energy hub model, there’s a lot of flexibility about input resource, such as electricity from conventional grid, renewable energy or nuclear. In order to explore what renewable energy can be involved in a distributed energy source system. It is reasonable that in [2,3,4,5], energy hub was designed by using grid electricity, natural gas or renewable energy such as solar and wind energy. Besides, the energy hub output side represents customers’ demand, which can be a known quantity. The energy saving, low economic cost and higher energy efficiency have been presented at the same time through running whole system under optimum operation rules [6,7,8].

2. Case Study

In this paper, a 3-storey residential building of 1660.73 m² with 5 apartments per floor located in the city of Zaragoza (Spain) has been modeled for simulation (see Figure 2). Climate parameters of Zaragoza, including ambient temperature, solar irradiation and wind speed, have been taken from PVGIS database.

Figure 2. Simulation model in Energy plus.

The daily average energy consumption of the building for each month is shown as Figure 3, where blue bars represent the electricity consumption and the red curve represents the heat demand. Electricity demand include air conditioning consumption and heat demand includes heating and hot water demand. As shown in Figure 3, in August, building has the most electricity consumption and the lowest heating demand. The highest electricity demand can approach 220 kWh per day and the highest heating demand is approximate 55 kWh per day.

Figure 3. Daily energy consumption of simulation building each month.

The electricity price is calculated by local actual-time price in Spain in 2017 (Figure 4). The gas price according to Spain actual gas price selected by 0.0667 Euro/kWh and 0.0865 Euro/kWh. To these values we have to add the taxes

Figure 4. Single Building energy hub model.

Table 1 shows the total energy cost, CO₂ emissions and consumptions of gas and electricity if we only rely on grid to satisfied electricity and heating demand of this building, the economic cost is 1.1713 × 10⁴ Euro/year, being the total CO₂ emissions 2.1711 × 10⁴ kg/year. In this way, it not only caused amount of economic costs and greenhouse gas emissions, but also caused a considerable impact on the power grid during the electricity consumption peak period, increasing power grid maintenance cost.

Table 1. Energy consumption only supply by net.

Cost (Euro/Year)	CO2 Emission (kg/Year)	Gas Consumption (kWh/Year)	Electricity Consumption (kWh/Year)
1.1713 × 104	2.1711 × 104	2.0518 × 104	6.2589 × 104

Accordingly, it is necessary to build an energy hub model according to this simulation building, which aim to decline the cost, decrease greenhouse gas emissions, and meanwhile relief grid’s pressure from peak load. In order to decrease economic cost of this building, heat pump (HP) and Photovoltaic plane (PV) introduced to constituent the energy hub HP is an equipment which can only take few electricity supply qualities of heating and cooling. Therefore, it’s often considered as a significant component introduce in energy hub. The HP mentioned in this paper selected COP as 3.2. In order to get the optimized result, multiple simulation experiments have been conducted on the different capacity combination of this two components. Each component parameter includes capacity, efficiency, capital cost, fixed cost and variable cost is shown in Table 2. And CO₂ emission from grid is shown in Table 3 respectively.

Table 2. Energy hub component parameters.

Component	Efficiency	Capìtal Cost	Lifetime
Gas Boiler	70%	800 Euro/kW	20
Heat Pump	3.2 (average COP)	1000 Euro/kW	20
PV	17%, PR = 0.8	1500 Euro/kW	30
PVT	variable	700 Euro/m2	30

Table 3. Other parameters.

Name	Value with Unit
CO2 emission from grid electricity	0.280 kg/kWh
CO2 emission from natural gas	0.204 kg/kWh

In a conventional photovoltaic system, the conversion efficiency is approximate 15–20% generally. Part of unused solar energy will heat up the panel, causing efficiency and lifetime decline. It is obviously beneficial to collect thermal energy from solar while generating electricity from sunlight. This hybird system, which produces electricity and hea simultaneously is called Photovoltaic/Thermal (PV/T system).

The thermal part of PV/T system efficiency$\mathsf{\eta }$is influenced by many factors, such as solar irradiation, pipe fluid temperature and so on, which can be represented as Equation (3).

$$\mathsf{\eta }={\mathsf{\eta }}_0-a_1\times \frac{\left(T_e-T_a\right)}{G}-a_2\times \frac{\left(T_e-T_a\right)}{G}$$

(3)

In this equation, ${\mathsf{\eta }}_0$ means the optical performance of the PV/T system. $a_1$ and $a_2$ are the thermal losses coefficients, in this paper set as 3.3 (W/m²)/K and 0.018(W/m²)/K² respectively. $I$ represents solar irradiation. $T_e$ is average value of pipe fluid temperature and $T_a$ is ambient temperature.

The annual cost of energy hub is comprised by 3 parts. Electricity from grid, gas from net and components cost, at the meantime components cost include average installation cost, operation and management annual fee, which shown as Equation (4).

$${\displaystyle \sum }_{t=1}^T\left[P_{ele}\left(t\right)\times electricityprice+P_{gas}\left(t\right)\times gasprice\right]+{\displaystyle \sum }_{n=1}^N(Componen{t}_{install}+Componen{t}_{o\&M}-Componen{t}_{discount})/years$$

(4)

The result shown as Table 4 and Table 5, while operating with 20 kW HP and 65 m² PV, the economic cost reach the minimum value 1.0727 × 10⁴ Euro/year. The CO₂ emission achieve 1.356 × 10⁴ kg/year at the meantime. Compared to supply all electricity and heating from grid, 8.42% economic cost will be saved and reduce 37.54% CO₂ emission. We can illustrate that introduce suitable capacity of HP and PV system can cut cost and reduce carbon emission simultaneously. With more renewable energy participant into the hub, the lower CO₂ emission energy hub system will achieve. So, the CO₂ emission can’t obtain the minimum value with economic cost at same time.

Table 4. Annual Cost for single building under Different PV and HP capacity (×10⁴ Euro/year).

			HP Capacity (kW)
PV Capacity (m2)		0.5	1	5	10	20	25	30
	5	1.1514	1.1378	1.1220	1.0984	1.0953	1.1005	1.1090
	10	1.1468	1.1333	1.1175	1.0939	1.0908	1.0960	1.1045
	20	1.1402	1.1266	1.1108	1.0872	1.0841	1.0893	1.0978
	30	1.1363	1.1226	1.1068	1.0832	1.0801	1.0853	1.0938
	50	1.1309	1.1173	1.1014	1.0778	1.0747	1.0799	1.0884
	60	1.1295	1.1158	1.0998	1.0762	1.0731	1.0783	1.0868
	65	1.1295	1.1157	1.0996	1.0758	1.0727	1.0778	1.0864
	70	1.1315	1.1175	1.1012	1.0772	1.0740	1.0792	1.0877

Table 5. Annual CO₂ emission for single building under Different PV and HP capacity (×10⁴ kg/year).

			HP Capacity (kW)
PV Capacity (m2)		0.5	1	5	10	20	25	30
	5	2.088	2.054	2.009	1.923	1.891	1.865	1.852
	10	2.041	2.008	1.963	1.876	1.845	1.818	1.806
	20	1.952	1.919	1.874	1.787	1.756	1.730	1.717
	30	1.869	1.836	1.791	1.704	1.673	1.647	1.634
	50	1.708	1.674	1.629	1.542	1.511	1.485	1.472
	60	1.630	1.596	1.551	1.464	1.432	1.406	1.393
	65	1.554	1.520	1.475	1.387	1.356	1.330	1.317
	70	1.482	1.448	1.402	1.315	1.283	1.257	1.244

In order to obtain an optimal value with the least amount of computation, around the global area of PV/T and PV system around 65 m², several different PV/T to PV proportions are calculated. The result is shown in Table 6. The optimal capacity of PV/T and PV system is when the capacity of PV is 36 m² and PV/T is 30 m². Compared to original system present in Table 4 and Table 5, 2.4% cost and 3.24% CO₂ emission will be saved this system.

Table 6. Energy hub Performance of different PV and PV/T capacity.

PV Capacity (m2)	PV/T Capacity (m2)	Global PV Area (m2)	Cost (×104 Euro/Year)	Electricity Consumption (×104 kWh/year)	CO2 Emissions (×104 kg/Year)	PVT Generation (kWh/Year)	HP Electricity Consumption (×103 kWh/Year)
28	20	48	1.0573	5.40	1.60	118.9	3.45
	24	52	1.0532	4.80	1.43	142.7	3.43
	30	58	1.0473	4.60	1.37	178.3	3.39
30	20	50	1.0567	4.85	1.44	118.9	3.45
	24	54	1.0528	4.72	1.41	142.7	3.43
	30	60	1.0471	4.52	1.35	178.3	3.39
36	20	56	1.056	4.71	1.40	118.9	3.45
	24	60	1.0523	4.58	1.37	142.7	3.43
	30	66	1.047	4.38	1.31	178.3	3.39
40	20	60	1.0556	4.54	1.36	118.9	3.45
	24	64	1.0521	4.41	1.32	142.7	3.43
	30	70	1.0475	4.22	1.27	178.3	3.39
42	20	62	1.0555	4.49	1.34	118.9	3.45
	24	66	1.0522	4.36	1.31	142.7	3.43
	30	72	1.0478	4.17	1.25	178.3	3.39
48	20	68	1.0556	4.38	1.31	118.9	3.45
	24	72	1.0526	4.26	1.28	142.7	3.43
	30	78	1.0488	4.07	1.23	178.3	3.39

3. Conclusions

In this work, a multi-variable energy hub model has been designed for a residential building. Besides the fundamental elements such as main grid, natural gas net and gas boiler, heat pump and photovoltaic panel are considered in the initial energy hub system. Secondly, next, the optimal proportion between PV system and PV/T system has been considered. The efficiency of the electrical and thermal generation of both systems (PV and PV/T) are considered variable. The results show that the optimal scheduling method is beneficial to improve energy utilization efficiency and the practical application of renewable energy, reducing greenhouse gas emissions.