Introduction to stochastic programming

Survey of research in the design and control of automated guided vehicle systems

This paper proposes a new heuristic approach for distributed generation (DG) capacity investment planning from the perspective of a distribution company (disco). Optimal sizing and siting decisions for DG capacity is obtained through a cost-benefit analysis approach based on a new optimization model. The model aims to minimize the disco's investment and operating costs as well as payment toward loss compensation. Bus-wise cost-benefit analysis is carried out on an hourly basis for different forecasted peak demand and market price scenarios. This approach arrives at the optimal feasible DG capacity investment plan under competitive electricity market auction as well as fixed bilateral contract scenarios. The proposed heuristic method helps alleviate the use of binary variables in the optimization model thus easing the computational burden substantially.

Optimal investment planning for distributed generation in a competitive electricity market

This paper proposes a new integrated model for solving the distribution system planning (DSP) problem by implementing distributed generation (DG) as an attractive option in distribution utilities territories. The proposed model integrates a comprehensive optimization model and planner's experience to achieve optimal sizing and siting of distributed generation. This model aims to minimize DG's investment and operating costs, total payments toward compensating for system losses along the planning period, as well as different costs according to the available alternative scenarios. These scenarios vary from expanding of an existing substation and adding new feeders to purchasing power from an existing intertie to meet the load demand growth. Binary decision variables are employed in the proposed optimization model to provide accurate planning decisions. The present worth analysis of different scenarios is carried out to estimate the feasibility of introducing DG as a key element in solving the DSP problem.

An integrated distributed generation optimization model for distribution system planning

Artificial Intelligence and Tutoring Systems

Power distribution planning is a complex task in which planners must ensure that there is adequate substation capacity (transformer capacity) and feeder capacity (distribution capacity) to meet the load demands. Decisions such as allocation of power flow, installation of feeders and substations, and procurement of transformers are costly ones which must be evaluated carefully. This paper provides a review of research problems as well as models related to the planning of substations and/or distribution feeders. Following a general discussion, we review existing research work under two major groups: planning under normal conditions, and planning for emergency. A discussion on relevant research opportunities is included.

Power distribution planning: a review of models and issues

Proactive preparedness to cope with emergencies, especially those of nature origins, significantly improves the resilience and minimizes the restoration cost of electric power systems. In this paper, a proactive resource allocation model for repair and restoration of potential damages to the power system infrastructure located on the path of an upcoming hurricane is proposed. The objective is to develop an efficient framework for system operators to minimize potential damages to power system components in a cost-effective manner. The problem is modeled as a stochastic integer program with complete recourse. The large-scale mixed-integer equivalence of the original model is solved by the Benders' decomposition method to handle computation burden. The standard IEEE 118-bus system is employed to demonstrate the effectiveness of the proposed model and further discuss its merits.

Stochastic Pre-hurricane Restoration Planning for Electric Power Systems Infrastructure

This paper presents a significant change in current electric power grid response and recovery schemes by developing a framework for proactive recovery of electric power assets with the primary objective of resiliency enhancement. Within the proposed framework, which can potentially present the next generation decision-making tool for proactive recovery, several coordinated models will be developed including: 1) the outage models to indicate the impact of hurricanes on power system components; 2) a stochastic pre-hurricane crew mobilization model for managing resources before the event; and 3) a deterministic post-hurricane recovery model for managing resources after the event. Proposed models will be extended to ensure applicability to a variety of electric power grids with different technologies and regulatory issues. The theoretical and practical implications of the developed models will push the research frontier of proactive response and recovery schemes in electric power grids, while its flexibility will support application to a variety of infrastructures, in response to a wide range of extreme weather events and natural disasters.

Suresh K. Khator

Papers

Power distribution planning: a review of models and issues

Stochastic Pre-hurricane Restoration Planning for Electric Power Systems Infrastructure

Proactive Recovery of Electric Power Assets for Resiliency Enhancement

A survey of Petri net applications in modeling controls for automated manufacturing systems

Cell formation in group technology: a new approach