Paolo Pisciella

Two-stage stochastic mixed integer optimization models for power generation capacity expansion with risk measures

We present two-stage stochastic risk averse optimization models for the power generation mix capacity expansion planning in the long run under uncertainty. Uncertainty is described by a set of possible scenarios in the second stage and uncertain parameters are the unit production costs of the existing power plants as well as those of the candidate plants of new technologies among which to choose, the market electricity price, the price of green certificates and the emission permits and the potential market share of the producer. The problem is expressed as a two-stage stochastic integer optimization model subject to technical constraints, market opportunities and budget constraints. First stage variables represent the number of new power plants for each candidate technology to be added to the existing generation mix every year of the planning horizon. Second stage variables are the continuous operation variables of all power plants in the generation mix along the time horizon. We solve the problem of the maximization of the net present value of the expected profits along the time horizon using both a risk neutral approach and different risk averse strategies (conditional value at risk, shortfall probability, expected shortage and first- and second-order stochastic dominance), under different hypotheses of the available budget, analysing the impact of each risk averse strategy on the expected profit. Results show that risk control strongly reduces the possibility of reaching unwanted scenarios as well as providing consistent solutions under different strategies.

A leader-followers model of power transmission capacity expansion in a market driven environment

We introduce a model for analyzing the upgrade of the national transmission grid that explicitly accounts for responses given by the power producers in terms of generation unit expansion. The problem is modeled as a bilevel program with a mixed integer structure in both upper and lower level. The upper level is defined by the transmission company problem which has to decide on how to upgrade the network. The lower level models the reactions of both power producers, who take a decision on new facilities and power output, and Market Operator, which strikes a new balance between demand and supply, providing new Locational Marginal Prices. We illustrate our methodology by means of an example based on the Garver’s 6-bus Network.

Optimal Power Flow Analysis in Power Dispatch for Distribution Networks

This paper presents two applications of Optimal Power Flow analysis for active and reactive power redispatch in medium-voltage distribution networks and shows how this tool can be used to efficiently manage the selection and operation of network resources as well as the definition of a market interface with the transmission network. The description of the frameworks is complemented by the analysis of a case study for the optimal selection and operation of available devices.

Models for Optimization of Power Systems

This chapter provides an overview of possible approaches that can be outlined to model and analyze the decision problems encountered in different stages of power production and delivery. The introduced models can be used for the control of two of the most important activities in power system management: production and transmission. In both cases, we describe how a single producer or an entire system can draw benefits from using optimization techniques for fine-tuning the expansion decisions to be taken. The theoretical basis for the analysis is drawn from different branches of operational research and optimization, ranging from mixed integer linear programming to stochastic programming and bilevel programming.

Business Model Evaluation for an Advanced Multimedia Service Portfolio

In this paper we analyze quantitatively a business model for the collaborative provision of an advanced mobile data service portfolio composed of three multimedia services: Video on Demand, Internet Protocol Television and User Generated Content. We provide a description of the provision system considering the relation occurring between tecnical aspects and business aspects for each agent providing the basic multimedia service. Such a techno-business analysis is then projected into a mathematical model dealing with the problem of the definition of incentives between the different agents involved in a collaborative service provision. Through the implementation of this model we aim at shaping the behaviour of each of the contributing agents modifying the level of profitability that the Service Portfolio yields to each of them.