Optimal Clearing Model of Centralized Market Considering Path Constraints

China’s electricity market is now still in the mode of “Unified market and two-tier operation” including provincial and inter-provincial market. The inter-provincial market is divided into the medium and long-term market and spot market. This study takes the inter provincial spot market as the research object, and proposes a unified optimization clearing algorithm for inter provincial spot market considering path constraints. The proposed method is able to handle AC-DC hybrid electricity network, and sort and determine the trading pairs using power flow tracing algorithm. The power market software PLEXOS and practical market data are used to simulate the proposed model, and the results show the accuracy and effectiveness.

provincial and spot markets, is gradually formed. The number of provinces participating in the inter provincial spot market will continue to increase, and the provinces that do not participate in the inter provincial spot market, such as JingIinTang area, Fujian and so on, will be gradually included.
Thirdly, the market is becoming more and more complex. In order to improve the operation efficiency of the market, the inter provincial spot market and the regional peak regulation ancillary service market will be gradually integrated in the future. The CRIP market will be an AC -DC hybrid market in which the power flow directions on AC lines are not unidirectional.
Based on the above considerations, this study proposes a unified optimization clearing algorithm for inter provincial spot market considering path constraints, such as node power flow balance, line power flow constraints, line ramping constraints, trading path constraints, etc.
The main features of the model are as follows: first, it supports the solution of complex AC / DC hybrid network with uncertain power flow direction, adopts the unified clearing method, constructs the mathematical unified optimization equation, and does not set the fixed path. Secondly, it is compatible with the current fixed path trading mode, and develops the path constraint algorithm to support the clearing method on the fixed path at present. Thirdly, the power flow tracing algorithm is innovated and developed, which can solve the power flow path from sending province to receiving province, which is convenient for transaction matching and settlement.

Model
The topology of the proposed CRIP spot market is taking the provinces or price areas due to congestion in the province as the base node, and building cross regional AC / DC hybrid network. Under the conditions of transmission security constraints and price constraints, the participated power resources are uniformly and optimally allocated with the goal of maximizing the social welfare.

2.1.Optimization goal
The goal of the optimization is to maximizing the social welfare, where the Welfare = Purchasing cost -Generation cost -Transmission cost. The equation is shown as follows. Where at a specific time interval, X , is the clearing power output of purchaser i at band b of its bidding curve, and P , is the corresponding price on band b, and there is a total number of n purchasers. X , is the clearing power output of generator i at band b of its bidding curve, and P , is the corresponding price on band b, and there is a total number of m generators. X is the clearing power output of line k and P is the wheeling charge of line k.
In order to implement the power flow tracing method, the transmission clearing power output variable X is decomposed into multiple sub-variables, shown as the following equation.

, , 2
In which, variable x i, j, k indicates the power energy transmits from generator i, flows through transmission line k and finally reaches to purchaser j.

2.2.Constraints
The node power injection constraint, the line flow constraint, transmission and ramping up and down constraints and path constraint are considered.

2.2.2.Line constraint
The clearing power on a specific line should be within its ATC limits. , , 4

2.2.3.Ramping constraint
The power ramping between two consecutive time intervals should be within the transmission line maximal adjusting capability.

2.2.4.Path constraint
If there is a fixed trading path s between generator i and purchaser j and line k is part of the trading path, the variable x i, j, k will be included in the model and be computed. If not, the value of x i, j, k will be forced to zero.

Simulation Results
A case study is carried out by using a set of practical data on one operation day of CRIP spot market. The total power bidding by generators is 37.619 million kWh, while the total power bidding by purchasers is 620.965 million kWh. The electricity market simulation software PLEXOS is used to model the CRIP market. The schematic diagram of the model is as follows. Figure 1 Diagram of Inter-provincial Spot Market In the above diagram, the lines include both AC and DC lines There are 33 bidding data from sending end and 16 bidding data from receiving end. A total of 47 lines was modeled, including parameters of loss rate, wheeling charge, power flow limits and etc. A unified optimizing clearance algorithm was applied by PLEXOS.

3.1.Case 1 -Compare actual results and simulated results
By setting the path constraint in the above proposed model, the comparison results are shown as the following tables.  The results are basically consistent, which verifies that the unified clearing algorithm considering path constraints can achieve the optimization goal as the same as matching clearing method.

3.2.Case 2 -Compare different market clearing methods
In this case, the high-low matching clearing algorithm and proposed unified clearing method are compared. The comparison results are shown as following. The unified optimization clearing algorithm optimizes the global variables, improves the transmission utilization rate, and further promotes the renewable energy consumption. Based on the unified clearing method, the trading volume was 13 million kWh; based on the fixed path matching clearing, the trading volume was 12.1 million kWh. It can be seen the unified clearing method was more effective than the fixed path matching clearing, and increase the trading volume by 900 thousand kWh.

Conclusions
In this research, it proposes a unified optimization clearing algorithm for inter provincial spot market considering path constraints. The proposed model supports the solution of complex AC / DC hybrid network with uncertain power flow direction and is compatible with the current fixed path trading mode. Moreover, the power flow tracing algorithm is innovated and developed, which can solve the power flow path from sending province to receiving province, which is convenient for transaction matching and settlement. Simulation shows the accuracy and effectiveness of the proposed method. The proposed method can be taken as reference for future inter-provincial market design to better promote the renewable energy and optimize the allocation of power resources in large-scale range.