# Research on Coupled Cooperative Operation of Medium- and Long-Term and Spot Electricity Transaction for Multi-Energy System: A Case Study in China

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## Abstract

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## 1. Introduction

- (1)
- This research realizes the medium- and long-term electricity markets and the spot market to be coupled with a cooperative operation for a multi-energy hybrid system.
- (2)
- A new dispatching model to promote fresh energy consumption is proposed to deal with the uncertainty of power decomposition in medium- and long-term contracts and the incompleteness of the spot market pilot operation.
- (3)
- The MTCS model, based on the objective function of minimizing the operating cost of thermal power, can effectively dispatch thermal power and hydropower units to cut peaks and fill valleys and maximize renewable energy consumption.
- (4)
- A two-stage solution method that includes electricity decomposition and unit start and stop status is introduced to solve the complex multi-agent, multi-period, and multi-energy model.
- (5)
- Gansu province is China’s earliest pilot spot market region, and typical scenes are introduced to cross-validate the MTCS model.

## 2. Problem Statement and Study Area Description

#### 2.1. Study Area

#### 2.2. Data Source

#### 2.3. Problem Summary

## 3. The Development of Mid-Long-Term Spot Transaction Coordination Scheduling Model (MTCS)

#### 3.1. Basic Framework of the MTCS Model

#### 3.2. Mid-Long-Term Spot Transaction Coordination Scheduling Model

#### 3.2.1. Objective Function

#### 3.2.2. Constraint Condition

- Power balance constraint:$$\sum}_{i=1}^{{N}_{t}}{P}_{Ti}^{t}+{\displaystyle \sum}_{j=1}^{{N}_{H}}{P}_{Hh}^{t}+{\displaystyle \sum}_{k=1}^{{N}_{w}}{P}_{Wk}^{t}+{\displaystyle \sum}_{p=1}^{{N}_{p}}{P}_{Pm}^{t}={P}_{L}^{t$$
_{H}represents the whole number of hydropower units; N_{W}represents the total number of wind farms; N_{P}represents the total number of photovoltaic farms; and ${P}_{L}^{t}$ refers to the power grid at time t Load demand. - Output limit constraints:$$\begin{array}{c}{P}_{T\mathrm{min}i}{U}_{i}^{t}\le {P}_{Ti}^{t}\le {P}_{T\mathrm{max}i}{U}_{i}^{t}\hfill \\ {P}_{H\mathrm{min}i}{U}_{h}^{t}\le {P}_{Hh}^{t}\le {P}_{H\mathrm{max}i}{U}_{h}^{t}\hfill \end{array}$$
- System rotation and standby constraints:$$\sum}_{i=1}^{{N}_{T}}\left({P}_{T\mathrm{max}i}-{P}_{Ti}^{t}\right)+{\displaystyle \sum}_{i=1}^{{N}_{H}}\left({P}_{H\mathrm{max}h}-{P}_{Hh}^{t}\right)\ge {\overline{R}}_{L}^{t}+{\overline{R}}_{W}^{t}\phantom{\rule{0ex}{0ex}}{\displaystyle \sum}_{i=1}^{{N}_{T}}\left({P}_{Ti}^{t}-{P}_{T\mathrm{min}i}\right)+{\displaystyle \sum}_{i=1}^{{N}_{H}}\left({P}_{Hh}-{P}_{H\mathrm{min}h}^{t}\right)\ge {\underset{\_}{R}}_{L}^{t}+{\underset{\_}{R}}_{W}^{t$$
- Minimum start–stop time limit:$${U}_{i}^{t}=\{\begin{array}{cc}1\hfill & {T}_{\mathrm{on}\text{}i}^{t-1}{T}_{\mathrm{up}\text{}i}\hfill \\ 0\hfill & {T}_{\mathrm{off}\text{}i}^{t-1}{T}_{\mathrm{down}\text{}i}\hfill \\ 0\text{}\mathrm{or}\text{}1\hfill & \mathrm{other}\end{array}$$
- Climbing rate constraints:$$-{r}_{\mathrm{di}}{U}_{i}^{t}\le {P}_{Ti}^{t}-{P}_{Ti}^{t-1}\le {r}_{\mathrm{ui}}{U}_{i}^{t}$$
- Inventory water constraints:$${V}_{\mathrm{min}h}\le {V}_{h}^{t}\le {V}_{\mathrm{max}h}$$$${V}_{h}^{t}={V}_{h}^{0}+{\displaystyle \sum}_{{t}_{c}=1}^{t}{q}_{h}^{{t}_{c}}-{\displaystyle \sum}_{{t}_{c}=1}^{t-1}{Q}_{h}\left({P}_{Hh}^{{t}_{c}}\right)-{\displaystyle \sum}_{{t}_{c}=1}^{t}{\mathrm{d}}_{h}^{{t}_{c}}$$
_{c}; ${Q}_{h}\left({P}_{Hh}^{{t}_{c}}\right)$ is the quoted flow of the hydropower station h at the moment t_{c}; and ${\mathrm{d}}_{h}^{{t}_{c}}$ is the discarded water flow of the hydropower station h at the moment t_{c}.$${Q}_{h}^{t}=\mathrm{g}\left({P}_{Hh}^{t}/{H}_{h}^{t}\right)={\beta}_{0}+{\beta}_{1}{P}_{Hh}^{t}+{\beta}_{2}{\left({P}_{Hh}^{t}\right)}^{2}$$

#### 3.3. Two-Stage Solution Process

#### 3.3.1. Medium- and Long-Term Contract Electricity Breakdown

_{1}is the daily power consumption on weekdays; and Q

_{2}is the daily power consumption on weekends, by million KWH.

#### 3.3.2. Dynamic Programming

- Dividing the stages to decompose the problem into multiple interconnected steps appropriately in order to solve them in a particular order;
- The state, which means the initial natural state or objective condition of each stage, is defined;
- Making the decision, which means different choices that can be made when the process is in a particular state at a specific stage;$${P}_{k,n}\left({s}_{k}\right)=\left\{{u}_{k}\left({s}_{k}\right),{u}_{k+1}\left({s}_{k+1}\right)\dots {u}_{n}\left({s}_{n}\right)\right\}$$
- A strategy is formulated to a set of decisions arranged in order. The state transition equation refers to the evolution process of the decision process from one state to another, generally the evolution of two adjacent states; the index function is a quantitative indicator used to measure the quality of the process achieved.$${V}_{k,n}={V}_{k,n}\left({s}_{k},{u}_{k},\dots {s}_{n},{u}_{n},{s}_{n+1}\right)\begin{array}{ccc}& & \end{array}k=0,1,2,\dots ,n$$

## 4. Case Analysis and Main Results

#### 4.1. Energy Type and Unit Parameter Setting

#### 4.2. Electric Quantity Decomposition Result

#### 4.3. Scheduling Model Results

## 5. Discussion

## 6. Conclusions

## Author Contributions

## Funding

## Institutional Review Board Statement

## Informed Consent Statement

## Data Availability Statement

## Acknowledgments

## Conflicts of Interest

## References

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**Figure 6.**Schematic diagram of the proportion of electricity generation in Gansu Province in each month of 2019.

**Figure 7.**Statistics of photovoltaic output by periods in Gansu Province: (

**a**) average, maximum, and minimum output; (

**b**) photovoltaic output on sunny, cloudy, and rainy days.

**Figure 10.**The start and stop states and output for thermal power units and hydropower units in the three scenes.

**Figure 12.**The output result of simulation scenes 1 (

**a**), 2 (

**b**), and 3 (

**c**); the power output of thermal power and hydropower units is depicted in (

**d**).

Functions | Description |
---|---|

${S}_{i}^{t}$ | Start-up cost of thermal power unit I. |

${N}_{T}$ | Total number of thermal power units |

T | Total scheduling time |

${P}_{Ti}^{t}$ | The output power of thermal power unit i at time t. [MW] |

${P}_{L}^{t}$ | The load demand at time t. [MW] |

${P}_{Ti}$ | The actual output power of thermal power unit T. [MW] |

${P}_{Hi}$ | The actual output power of hydropower unit H. [MW] |

${\overline{R}}_{L}^{t},{\underset{\_}{R}}_{L}^{t}$ | The positive and negative spinning reserve capacity required by the grid load at time t. [MW] |

${\overline{R}}_{w}^{t},{\underset{\_}{R}}_{w}^{t}$ | The positive and negative spinning reserve capacity required by the wind farm at time t. [MW] |

${r}_{\mathrm{di}},{r}_{\mathrm{ui}}$ | The lower limit and upper limit of the climbing rate of thermal power unit i. [MW/h] |

${V}_{h}^{t}$ | The storage volume of hydropower station h at time t. [10^{3} m^{3}] |

${\beta}_{1},{\beta}_{2},{\beta}_{3}$ | The water consumption function coefficient of the output of the hydropower station unit and the quoted flow rate of the unit. |

${P}_{\begin{array}{c}Hh\\ \end{array}}^{t}$ | The output power of hydropower station h at time t. |

${H}_{h}^{t}$ | The reservoir head of hydropower station h at time t. |

Unit | T1 | T2 | T3 | T4 | T5 | T6 | H1 | H2 |
---|---|---|---|---|---|---|---|---|

${P}_{i,\mathrm{min}}/\mathrm{MW}$ | 250 | 250 | 110 | 110 | 100 | 100 | 0 | 0 |

${P}_{i,\mathrm{max}}/\mathrm{MW}$ | 600 | 600 | 330 | 330 | 300 | 300 | 225 | 30.4 |

Type of Power Supply | Should Generate Electricity | Proportion |
---|---|---|

Thermal power | 58.65 | 56.62% |

Hydropower | 17.22 | 16.63% |

Wind power | 18.56 | 17.91% |

Photoelectric | 9.16 | 8.84% |

Type of Power Supply | Workdays Power Generation | Weekends Power Generation |
---|---|---|

Thermal power | 2.03 | 1.73 |

Hydropower | 0.61 | 0.52 |

Wind Power | 0.64 | 0.55 |

Photoelectric | 0.32 | 0.27 |

Period | Wind Power | PV Power | |
---|---|---|---|

Sunny | Rainy | ||

1 | 204.8 | 0 | 0 |

2 | 204.8 | 0 | 0 |

3 | 217.6 | 0 | 0 |

4 | 236.8 | 0 | 0 |

5 | 268.8 | 0 | 0 |

6 | 307.2 | 0 | 0 |

7 | 326.4 | 0 | 6.98 |

8 | 352 | 54.4 | 13.8 |

9 | 358.4 | 108.8 | 55.4 |

10 | 377.6 | 233.6 | 27.6 |

11 | 377.6 | 345.6 | 138.4 |

12 | 358.4 | 384 | 214.6 |

13 | 332.8 | 412.8 | 228.4 |

14 | 307.2 | 412.8 | 166.2 |

15 | 249.6 | 400 | 200.8 |

16 | 236.8 | 345.6 | 186.9 |

17 | 230.4 | 262.8 | 83.1 |

18 | 224 | 150.4 | 110.8 |

19 | 217.6 | 70.4 | 20.8 |

20 | 217.6 | 19.2 | 0 |

21 | 204.8 | 0 | 0 |

22 | 198.4 | 0 | 0 |

23 | 198.4 | 0 | 0 |

24 | 192 | 0 | 0 |

Start–Stop Costs/RMB | Running Costs/RMB | Total Cost/RMB | |
---|---|---|---|

Scene 1 | 2830 | 229,893 | 232,723 |

Scene 2 | 2860 | 224,536 | 227,396 |

Scene 3 | 2830 | 248,578 | 251,408 |

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## Share and Cite

**MDPI and ACS Style**

Wang, K.; Wang, X.; Jia, R.; Dang, J.; Liang, Y.; Du, H.
Research on Coupled Cooperative Operation of Medium- and Long-Term and Spot Electricity Transaction for Multi-Energy System: A Case Study in China. *Sustainability* **2022**, *14*, 10473.
https://doi.org/10.3390/su141710473

**AMA Style**

Wang K, Wang X, Jia R, Dang J, Liang Y, Du H.
Research on Coupled Cooperative Operation of Medium- and Long-Term and Spot Electricity Transaction for Multi-Energy System: A Case Study in China. *Sustainability*. 2022; 14(17):10473.
https://doi.org/10.3390/su141710473

**Chicago/Turabian Style**

Wang, Kaiyan, Xueyan Wang, Rong Jia, Jian Dang, Yan Liang, and Haodong Du.
2022. "Research on Coupled Cooperative Operation of Medium- and Long-Term and Spot Electricity Transaction for Multi-Energy System: A Case Study in China" *Sustainability* 14, no. 17: 10473.
https://doi.org/10.3390/su141710473