Mingqiang Wang

Benders decomposition algorithm for reference network

A reference network is topologically identical to the existing network in which the generators and loads are not changed while the transmission line capacity will be optimized. By applying a reference network, the optimal transmission capacities of each line could be identified, as it takes annual operational and transmission costs into consideration. A reference network provides a standard to evaluate the real network objectively. The congestion costs can be quantified and the optimal investment proposal can also be obtained based on load forecasting. Furthermore, the weakness of the system can be detected by comparing those in the reference and the actual network. However, for a large-scale power system, it is extremely complicated to build the reference network, as the optimal capacities for each line must be determined considering various contingency events. In this paper a simplified Benders decomposition algorithm is presented and applied to solve this model. Simulation results show that this technique can reduce computation time and improve convergence performance.

Assessment of up and down spinning reserve considering transmission constraints

In this paper a new model is proposed to schedule the capacity of both up and down spinning reserve (SR) considering transmission constraints. Up SR is seen as the most important resource to cope with many contingencies and it is well studied, while the down SR is ignored by many papers especially when network constraints are considered. Ignoring the down SR would cause sub-optimal or even unfeasible solution. In this paper an iterative process is proposed to schedule up and down SR and the importance of down SR will be analyzed and illustrated. At each iteration of the process, the up SR cost is firstly minimized with respect to reserve constraints and reliability constraints and then the sum of expected interruption cost and down SR cost is minimized with respect to various post- contingency constraints under each contingency event to alleviate transmission congestion. The effectiveness of the proposed method is demonstrated by the Roy Billinton Test System (RBTS) and the results are analyzed to illustrate the significance of down SR in the market-clearing model with transmission constraints.

A new method for reference network considering contingent events based on line outage distribution factor

Reference network model determines the optimal transmission line capacities by minimizing the generation cost and investment cost of transmission lines, in which line flow constraints under contingency events should be respected. However, the number of these constraints is tremendous and this makes the impediment when reference network model is applied for real large power systems. In this paper a new method is proposed to solve reference network efficiently based on line outage distribution factor (LODF). Firstly, the power flow without contingency events is calculated. Next, the line flow under contingency events is calculated based on LODF. For each contingency event, the line flow constraint which possesses the most severe overload level is added into the reference network model. The optimization procedure proceeds until all the overload flows are eliminated. The efficiency and validity of the proposed method is verified by IEEE test systems and a real large power system.

Solving dynamic economic dispatch with valve point effect by a two-step method

A two-step method is proposed in the paper to solve the dynamic economic dispatch (DED) with valve-point effect (VPE). In the first step, the rectified sinusoidal term which represents the effect of VPE is piecewise linearized and the entire problem can be solved by mixed integer linear programming (MILP). In the second step, based on the solution of the first step, the DED problem is decoupled into static economic dispatch (SED) problem. With the introduction of quasi singular point, a modified dimensional steepest decline method (MDSD) is proposed to explore and exploit a better solution. More accurate solution can be found within a shorter run time. The proposed two-step method is compared with other similar methods through a ten-unit test system.

Spinning reserve optimization using reliability constrained unit commitment

Maintaining an appropriate amount of spinning reserve (SR) is a necessary condition to keep the reliable operation of power systems. In this paper, a probabilistic method is proposed to determine the optimal SR amount where the reliability levels are well kept. The SR amount is optimized through a reliability constrained unit commitment (RCUC). In the RCUC model the reliability indexes must be smaller than their upper limits are involved as the constraints. The introduction of the reliability indexes makes the optimization computation intensive. In this paper, a multi-step method is proposed to solve the problem efficiently. The reliability indices such as the expected energy not supplied and loss of load probability are analytically approximated in terms of piecewise linear formulations. The approximation error is gradually eliminated as the step progresses. The superiority of proposed technique is illustrated by the IEEE reliability test system. efficiency and validity of the proposed method is verified using the.

Generation and pump scheduling in a shipyard with interruptible loads

In this paper, an economic scheduling of distributed generating units and drydock pumps in a shipyard is proposed. The objective function is to minimize the total electricity bill payment of a shipyard while considering its own generation to meet the demand. The volatile electricity market price, contracted capacity constraint, and interruptible loads (ILs) are all considered during the optimization. A significant saving can be achieved by the proposed optimization model.

An effective algorithm for the multi-area unit commitment

A bi-level decision-making method for the network constrained unit commitment (UC) problem is proposed. The upper level aims to minimize the total cost by solving an optimal power flow problem which considering the flow constraints of the tie lines. It produces the generation output for the lower level which deals with the sub-systems. In lower level the sub problems are solved by minimizing the generation cost, then the optimal unit status and unit output power can be achieved. The two levels are solved alternatively according to the marginal information of the lower level. The efficiency and validity of the proposed method is verified using the case studies.