Rule-based scheduling of multi-stage multi-product batch plants with parallel units

A novel rule-based model for multi-stage multi-product scheduling problem(MMSP)in batch plants with parallel units is proposed.The scheduling problem is decomposed into two sub-problems of order assignment and order sequencing.Firstly,hierarchical scheduling strategy is presented for solving the former sub-problem,where the multi-stage multi-product batch process is divided into multiple sequentially connected single process stages,and then the production of orders are arranged in each single stage by using forward order assignment strategy and backward order assignment strategy respectively according to the feature of scheduling objective.Line-up competition algorithm(LCA)is presented to find out optimal order sequence and order assignment rule,which can minimize total flow time or maximize total weighted process time.Computational results show that the proposed approach can obtain better solutions than those of the literature for all scheduling problems with more than 10 orders.Moreover,with the problem size increasing,the solutions obtained by the proposed approach are improved remarkably.The proposed approach has the potential to solve large size MMSP.

New Maintenance Strategies for Generating Companies in Power Market

A new approach to maintenance scheduling of generating units(MSU)in competitive electricity markets was presented,which was formulated as a noncooperative game with complete information.The payoff of each generating company(Genco)was defined as the profit from the energy auction market minus maintenance cost and risk loss.The compensation fee of interruptible load was a part of the maintenance cost when the permitted maintenance capacity in the system was insufficient.Hourly energy auction was incorporated in the computation of both revenues from energy market and risk loss of maintenance strategy as a nested game.A new heuristic search algorithm for the calculation of the game equilibrium of MSU was presented,which coordinates the solutions of non-equilibrium,unique equilibrium and multiple equilibria.Numerical results for a two-Genco system and a realistic system were used to demonstrate the basic ideas and the applicability of the proposed method,as well as its computational efficiency.

Risk-based maintenance scheduling of generating units in the deregulated environment considering transmission network congestion

In restructured power systems,the traditional approaches of unit maintenance scheduling(UMS)need to undergo major changes in order to be compatible with new competitive structures.Performing the maintenance on generating units may decrease the security level of transmission network and result in electricity shortage in power system;as a result,it can impose a kind of cost on transmission network as called security cost.Moreover,taking off line a generating unit for performing maintenance can change power flow in some transmission lines,and may lead to network congestion.In this study,generating unit maintenance is scheduled considering security and congestion cost with N-1 examination for transmission lines random failures.The proposed UMS approach would lead to optimum operation of power system in terms of economy and security.To achieve this goal,the optimal power flow(OPF)compatible with market mechanism is implemented.Moreover,the electricity price discovery mechanism as locational marginal pricing(LMP)is restated to analyze the impacts of UMS on nodal electricity price.Considering security and congestion cost simultaneously,this novel approach can reveal some new costs which are imposed to transmission network on behalf of generation units;as a result,it provides a great opportunity to perform maintenance in a fair environment for both generating companies(GenCo)and transmission companies(TransCo).At the end,simulation results on nine-bus test power system demonstrate that by using this method,the proposed UMS can guarantee fairness among market participants including GenCos and TransCo and ensure power system security.