Study On Multi-period Bidding Models For Power Suppliers Considering Transmission Congestion

In electricity market environment, power suppliers are separated from the traditional system and changed to a self-sustaining economic entity. As an economic entity, maximizing the individual profit is the final target. As a result, strategic bidding is the key issues for power supplier to obtain competitive advantage in the market. In a real network, with the constraint of the heat capacity of transmission line and system stability, the power of transmission lines must be lower than the capacity to avoid transmission congestion which may affect the competitive power of power suppliers in the market. In order to win the competition, the power suppliers usually change their bidding strategies with the state of power transmission. Therefore, the study of the bidding strategy accounting for the transmission congestion is critically important for power suppliers. In the meantime, due to the limitation of the generator unit operating constraints, power suppliers must take into account each period of mutual restraint between the generator unit climbing rate and the power output when establishing the bidding strategy. Otherwise, the achieved optimal strategy may not be reasonable and effective. In this thesis, therefore, the combined effect of the transmission congestion and generator unit operating constraints on the bidding strategies of power suppliers is investigated, with which multi-period optimal bidding strategy based on MCP mechanism, incentive-compatible bidding mechanism and PAB mechanism are achieved. It is expected that the outcome of this interesting and inspiring research will be helpful for all power suppliers in China's electric power industry to establish their reasonable bidding strategies, and provide a certain reference for further improving the bidding mechanism in China.. Hence, this thesis is rather valuable in both theoretical and engineering aspects.First of all, this thesis developed a model and algorithm that can eliminate the congestion utilizing the matchmaking transaction mechanism. When taking the minimum adjustment cost as an objective function, the different settlement rules will inevitably lead to different congestion management costs, affecting the bidding strategy. Therefore, part of this thesis is focused on the development of the model and algorithm to eliminate congestion for MCP, PAB and matchmaking settlements, and calculate the adjustment cost. Aiming at the more complex matchmaking transaction mechanism, this thesis then investigated the relation between settlement rule based on matchmaking transaction mechanism and congestion management model. Due to the nonlinear interaction relation between the settlement price and generator unit outputs under such mechanism, the objective function possesses nonlinear characteristics. To solve the proposed model, the active power increment of each power supplier that successfully matches with the load is chosen as the solving variable, and the augmented objective function is built by the Lagrange multiplier. As such, the proposed model is solved by Kuhn-Tuck optimal condition method. Finally, this model is applied to a test system to compare the congestion management cost under the different settlement rules, in order to lay the foundation for the study on bidding strategy of power supplier considering transmission congestion.Furthermore, this thesis developed a two-layer optimal model to study the impact of the transmission congestion on the bidding strategies of power suppliers in electricity market. Firstly, based on the prediction of the competitors'bidding, a profit maximization model for power supplier is developed, by which a control center is simulated for market clearing to obtain the market clearing price and the active power expectations of power suppliers. In addition, according to the expectations, the transmission flow is calculated. With this model, the effect of the transmission congestion on power suppliers'bidding strategies can be induced into the bidding model as an additional payment so as to build up the optimal bidding model considering congestion, when the congestion appears. Taking the minimum adjustment cost as an objective function to eliminate congestion, the adjusted active power of each power supplier can be obtained according to sensitivity calculation. The simulation results show that the proposed method can be used to guide the drafting of bidding strategy.In addition, the power suppliers'bidding strategies should consider the optimality in an entire period of time due to the impact of generator unit climbing rate on the power output of each period. To this end, a model for obtaining optimal bidding strategy through Q-learning with generator unit climbing rate constraint for the hour-ahead power market is developed. In this model, the profits and the bidding strategies of power suppliers in each period are treated as the Q value function and the state variable respectively, and the adjusted power is considered as the action set. Based on the market clearing results one hour before, the multi-period optimal bidding strategies of power suppliers with generator unit climbing rate constraint are then achieved. By improving the updated method of Q value in solution process, it is ensured that Q-table contains the Q values of all states. The numerical testing results show that this method has high applicability and effectiveness.Considering both of the impacts of the transmission congestion and generator unit operating constrains on the bidding strategies of power suppliers, this thesis also extends the single-period bidding model to a multi-period bidding model. In this model, since both the generator unit operating constraints and the effect of transmission congestion on the bidding strategies for power suppliers are considered, the optimal bidding strategies of power suppliers in a period of time considering the transmission congestion in power market can be achieved. In this work, the improved Q-learning algorithm is utilized to solve the model, and test systems are adopted to demonstrate the validity and efficiency of this model.Finally, according to the characteristic of power suppliers'bidding strategies, an incentive-compatible bidding mechanism for the electricity market is proposed. Considering the impact of transmission congestion constraints, the bidding model for power supplier based on proposed mechanism is investigated. In this model, according to the function of expectation generation capacity and bidding strategy of power supplier, the proposed model can effectively solve the practical problem that is difficult to calculate. This thesis adopts the test system to demonstrate the proposed model, and compare the bidding strategy in proposed mechanism with that in the PAB mechanism. The results show the applicability and efficiency of this model.