Simo Makkonen

Non-convex power plant modelling in energy optimisation

Abstract The European electricity market has been deregulated recently. This means that energy companies must optimise power generation considering the rapidly fluctuating price on the spot market. Optimisation has also become more difficult. New production technologies, such as gas turbines (GT), combined heat and power generation (CHP), and combined steam and gas cycles (CSG) require non-convex models. Risk analysis through stochastic simulation requires solving a large number of models rapidly. These factors have created a need for more versatile and efficient decision-support tools for energy companies. We formulate the decision-problem of a power company as a large mixed integer programming (MIP) model. To make the model manageable we compose the model hierarchically from modular components. To speed up the optimisation procedure, we decompose the problem into hourly sub-problems, and develop a customised Branch-and-Bound algorithm for solving the sub-problems efficiently. We demonstrate the use of the model with a real-life application.

Multivariate Gaussian criteria in SMAA

Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and dependencies using a stochastic simulation model. The model is based on decision variables and stochastic parameters with given distributions. Based on the simulation results, we determine for the criteria measurements a joint probability distribution that quantifies the uncertainties and their dependencies. We then use the SMAA-2 stochastic multicriteria acceptability analysis method for comparing the alternatives based on the criteria distributions. We demonstrate the use of the method in the context of a strategic decision support model for a retailer operating in the liberated European electricity market.

A multi-criteria framework for the selection of risk analysis methods at energy utilities

The ongoing deregulation and convergence of energy markets have made it imperative for energy utilities to adopt systematic risk management policies. Effective implementation of these policies calls for adequate risk information, which is typically synthesised by combining inputs from several risk analysis methods. Many utilities select such methods informally, based on subjective perceptions of how well these methods contribute to the objectives of their risk management strategy. In this paper, we address this selection problem through decision analysis; specifically we: develop a systematic multi-criteria framework for evaluating collections of risk analysis methods; and report a case study where such collections were evaluated with a novel decision support tool which accommodates incomplete preference information. Drawing upon this case study, we argue that the development of a systematic framework can contribute to an improved understanding of key issues in risk management and engender potential savings due to better decision-making.

Analysis of power pools in the deregulated energy market through simulation

The electricity market has changed rapidly in the Northern European countries. Harmonisation of the legislation and trading methods widens the market area outside national limits. Vertical integration among electricity companies is changing the traditional structure of the inner market. Successful business in this new more volatile market requires sophisticated techniques for identifying new market opportunities and managing the increased risks. We study the new market from the perspectives of regional distributors and power pools. We analyse the trading possibilities and profitability of different kinds of power pools, when a spot market and several new contract structures are available along with existing capacity based long-term contracts. Different policies for allocating the common benefits of a power pool among its members are compared and a new booking algorithm for balance settlement is introduced. To analyse the operation of different kinds of pools, we use simulation and optimisation techniques.