Weihui Shao

A Hybrid GRASP

The two-echelon vehicle routing problem (2E-VRP) is a variant of the classical vehicle routing problem (VRP) arising in two-level transportation systems such as those encountered in the context of city logistics. In the 2E-VRP, freight from a depot is compulsorily delivered through intermediate depots, named satellites. The first echelons are routes that distribute freight from depot to satellites, and the second are those from satellites to customers. This problem is solved by a hybrid heuristic which is composed of a greedy randomized adaptive search procedure (GRASP) with a route-first cluster-second procedure embedded and a variable neighborhood descent (VND), called GRASP

Real-Time Pricing Control on Generation-Side: Optimal Demand-Tracking Model and Information Fusion Estimation Solver

This paper develops the information fusion based pricing control (IFPC) scheme for the generation-side in the liberalized wholesale electricity market. The market mechanism is described by a feedback system, in which the independent system operator (ISO) interacts with generation companies (GenCOs) via proposing and responding to real-time nodal prices. The linear constrained quadratic optimal tracking problem is formulated; and the solution (nodal price sequence) is repeatedly computed by fusing the recently available information with backward manner and updated over the receding preview horizon. So that the total supply dynamically tracks the demand, the price is stationarized and each GenCO gains the maximal profit for the given price. Numeric results on a 118-bus network validate IFPCs effectiveness and flexibility on incorporating various line rating constraints as well as wind power fluctuation uncertainties. Comparative study demonstrates that IFPC outperforms the negotiated predictive dispatch but elapsing heavier computations. The irrational behavior analysis verifies the convergence to equilibrium; and speculation behavior of GenCOs in the real market is also discussed. Along with the rapid development of smart grid, IFPC is practically enabled by the information and communication technology (ICT); its significance and potentials for renewable energy sources (RES) integration would be realized and exploited.

Study on charging strategy of electric vehicle parking lot based on improved PSO

Electric vehicle parking lot is a kind of profit service facilities nearby commercial office buildings for electric vehicles to park and charge. A V2P model is built to describe electric vehicles charging in the parking lot based on V2G (vehicle to grid) technology. Under the conditions of real-time pricing, improved particle swarm optimization (PSO) algorithm is applied to study on charging strategies of electric vehicles. Real-time electrovalency data of PJM and the parameters of mainstream electric vehicles are used in simulation. Results of the simulations show that the proposed model is reasonable and the improved PSO algorithm is both efficient and effective.

A Comparative Study of Pricing Control Algorithms in Deregulated Electricity Market

In the future smart grid, both sides of the generation and the demand participate in the real-time electricity market, and their activities are responsive to the electricity price. Thus it is proposed the concept of “pricing control.” Considering the numerous algorithms of pricing control which are reported in literature, this paper performs a comparative study and evaluates their effectiveness and advantages. The pricing control scheme of electricity market is formulated. The control algorithms are presented, i.e., info-fusion-based control, multiperiod optimal control, adaptive estimation, proportional-integral, and moving average estimation. The differences are clarified; from the model description to the solving technique. The quality of the solution is computationally compared and analyzed.

Islanding partition of the distribution system with distributed generations based on Memetic algorithm

A new scheme for the islanding partition of the distribution system with distributed generations (DGs) is proposed in this paper. A bi-objective optimization model is built; the fixed weight approach, fuzzy membership function and Memetic algorithm are employed to solve the islanding problem. The simulations on the American PG&E 69-node distribution system show that the results obtained from the new model and Memetic algorithm can converge to an acceptable result rapidly, and the islands formed by the results possess better power quality than the single objective optimization case. The results of the case study demonstrate that an islanding scheme with good power quality can be obtained by the proposed model and algorithm after the fault occurred in the distribution system.

Mechanism Design of Virtual Power Plant for the Future Smart Grid

Virtual power plant (VPP) can respond to the real-time electricity price and implement management of controllable power plants and the distributed energy resource (DER) coordinately in future Smart Grid. Thus the mechanism of virtual power plant in future Smart Grid is designed in this paper. The model formulations are presented and the MS-VND algorithm is used to optimize the objects of both commercial VPP (CVPP) and technical VPP (TVPP). Simulations are conducted on IEEE-30 standard test system and the performance of the solutions is computationally compared and analyzed.

Demand-side response of smart clients under real-time pricing

Electric power market will transform to the free market based on real-time pricing and the traditional clients will change to smart clients with the development of Smart Grid. A smart client model which includes general loads, energy storage devices, electric vehicles and distributed generations is developed in this paper to study the demand-side response under real-time pricing. MS_VND algorithm is used to search the optimal strategies. Computational tests on the real data show that the proposed model is reasonable and MS_VND algorithm is both efficient and effective.