Abstract
This paper addresses an energy sharing strategy in a two-layer microgrid with the renewable distributed generation and hybrid energy storage system considered to minimize the total energy bill purchased from the utility grid and reduce the peak time consumption from the utility grid. This approach considers the energy operation management of thermal energy loads and electrical energy loads, in which the thermal energy loads are supplied by electrical energy and gas energy. Moreover, this energy sharing model is designed to allow the operation with different types of end-user modes, and the participants are divided into different layers based on their characteristics. Furthermore, the modified trading method is based on the trading model of stock opening with the maximum transaction volume. The proposed two-layer model is tested in 18-bus IEEE system with the real historical data in the Australia energy market. With the proposed two-layer energy sharing strategy, the simulation results show that the two-layer energy sharing model provides economic profits to participants and encourages load schedule.
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Abbreviations
- \( \beta_{n}^{bat,ch} \& \beta_{n}^{bat,dch} \) :
-
Charging and discharging coefficient of BESS
- \( \upbeta_{\text{n}}^{\text{bat}} \) :
-
Coefficient of BESS degradation cost
- \( \beta_{c}^{\text{th}} \& \beta_{l}^{\text{th}} \) :
-
Coefficients of the thermal energy capacity and loss
- \( \upgamma_{\text{n}}^{{{\text{bat}},{\text{loss}}}} \) :
-
Coefficient of BESS loss
- A:
-
Price of electrical and gas energy
- B:
-
Benefit and profit
- C:
-
Cost
- E:
-
Energy
- P:
-
Power
- t:
-
Time
- T:
-
Temperature
- bat:
-
Battery energy storage system (BESS)
- ch:
-
Energy charging of BESS
- dch:
-
Energy discharging of BESS
- ele:
-
Electrical energy
- rate:
-
Rate value of variable
- th:
-
Thermal energy
- \( A_{n,t}^{buy} ,A_{n,t}^{sell} \) :
-
Planning buying and selling price
- \( \varvec{A}_{t}^{buy} \& \varvec{A}_{t}^{sell} \) :
-
Sorted matrixes of buying price \( A_{n,t}^{buy} \) and selling price \( A_{n,t}^{sell} \)
- \( {\text{B}}_{{{\text{n}},{\text{t}}}}^{\text{ele}} \) :
-
Benefit from electrical energy sharing
- \( {\text{E}}_{{{\text{n}},}}^{{{\text{th}},{\text{loss}}}} \) :
-
Loss energy of thermal energy
- \( E_{n,t}^{rdg} \& E_{n,t}^{dem} \) :
-
DRG energy and demand energy for the n-th participant at time t
- \( E_{n,t}^{buy} \& E_{n,t}^{sell} \) :
-
Planning buying and selling energy
- \( E_{n,t}^{t - b} \& E_{n,t}^{t - s} \) :
-
Traded buying and selling energy for the n-th trading player at time t
- \( \varvec{E}_{t}^{buy} ,\varvec{E}_{t}^{sell} \) :
-
Sorted matrixes of buying energy \( E_{n,t}^{buy} \) and selling energy \( E_{n,t}^{sell} \)
- \( f_{{A_{n,t}^{buy} }} \left\{ {E_{n,t}^{buy} } \right\} \) :
-
Function to sort the buying energy \( E_{n,t}^{buy} \) by the same with the same sorting sequence of the buying price \( A_{n,t}^{buy} \)
- \( f_{{A_{n,t}^{buy} }}^{{\prime }} \left\{ {\varvec{E}_{t}^{{{\prime }buy}} } \right\} \) :
-
Function to sort the energy \( \varvec{E}_{t}^{{{\prime }buy}} \) with the inverse sequence of \( f_{{A_{n,t}^{buy} }} \left\{ {E_{n,t}^{buy} } \right\} \)
- \( M_{t}^{buy} \& M_{t}^{sell} \) :
-
Amount energy of the buying and selling energy
- \( {\text{N}}_{{{\text{n}},{\text{lc}}}}^{\text{bat}} \) :
-
Charging numbers during the battery lifetime
- \( {\text{P}}_{{{\text{n}},{\text{t}}}}^{\text{waste}} \) :
-
Waste energy generated by RDG
- \( {\text{P}}_{{{\text{n}},{\text{t}}}}^{\text{dem}} \) :
-
Demand energy of the n-th participant at time t
- \( P_{i} ,Q_{i} ,V_{i} \) :
-
Active power, reactive power and voltage in the i-th branch
- \( T_{amb}^{th} \) :
-
Ambient temperature
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AEMO: http://www.aemo.com.au
Acknowledgements
This work was supported by the National Key Research and Development Program of China (2017YFB0903205) and was also supported by the ARC Research Hub for Integrated Energy Storage Solutions (IH180100020), FEIT Early Career Researcher and Newly Appointed Staff Development Scheme, The University of Sydney and Sir William Tyree Foundation-Distributed Power Generation Research Fund.
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Han, X., Sun, L., Liu, G., Kang, L., Zheng, F., Qiu, J. (2020). Two-Layer Energy Sharing Strategy in Distribution Network with Hybrid Energy Storage System. In: Shahnia, F., Deilami, S. (eds) ICPES 2019. Lecture Notes in Electrical Engineering, vol 669. Springer, Singapore. https://doi.org/10.1007/978-981-15-5374-5_1
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DOI: https://doi.org/10.1007/978-981-15-5374-5_1
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