Comprehensive Energy Systems Analysis Support Tools for Decision Making

Sustainability of energy systems is a common priority that involves key issues such as security of energy supply, mitigation of environmental impacts - the energy sector is currently responsible for 80% of all EU greenhouse gas emissions (European Environment Agency, 2007), contributing heavily to the overall emissions of local air pollutants - and energy affordability. In this framework, energy planning and decision making processes can be supported at different stages and spatial scales (regional, national, pan-European, etc.) by the use of comprehensive models in order to manage the large complexity of energy systems and to define multi-objective strategies on the medium-long term. This Chapter is aimed to outline the value of model-based decision support systems in addressing current challenges aimed to carry out sustainable energy systems and to diffuse the use of strategic energy-environmental planning methods based on the use of partial equilibrium models. The proposed methodology, aimed to derive cost-effective strategies for a sustainable resource management, is based on the experiences gathered in the framework of the IEA-ETSAP program and under several national and international projects.

An Intelligent Motor-Pump System

Process industries are energy intensive in nature and are one of the largest consumers of electrical energy that is commercially generated for utilization. Motor driven systems consume more than two-thirds of the total energy consumed by the industrial sector; among which, centrifugal pumps are the most widely used equipment mainly for the purpose of fluid transportation. The efficiency of pumping units is around 40 to 50%, hence they offer tremendous opportunities of not only improving the efficiency of the process, but also ensure effective energy utilisation and management. With the increasing use of power electronics equipment, power quality (PQ) has become a very serious issue of consideration. On account of the random switching of single-phase loads in addition to time varying operations of industrial loads, PQ problem of voltage variation and unbalance is inevitable across three-phase systems. Application of varying or unbalanced voltages across the three-phase motor terminals results in performance variations leading to inefficient operation. For the purpose of study, the performance of a motor-pump system can be separately analyzed from the motor and pump points of view. The motor efficiency may vary in a very narrow band, pump efficiency depends upon the system head and flow rate but the system efficiency is a combination of the two; hence, necessary to analyze separately. As centrifugal pumps are classified under variable torque-variable speed load category, variation on the input side has a significant effect on the output side. Therefore the system efficiency now becomes an important index for ensuring efficient energy utilisation and efficiency. The main objective of the chapter is to put forward a methodology to analyze the working performance of a three-phase induction motor driven centrifugal pump under conditions of voltage and load variations by, defining additional factors for correct interpretation about the nature and extent of voltage unbalance that can exist in a power system network; define induction motor derating factors for safe and efficient operation based on operational requirements and devise energy management strategies for efficient utilization of electrical energy by the motor-pump system considering the voltage and load conditions.

Information Technology in Power System Planning and Operation under Deregulated Markets

Power systems have grown recently in size and complexity to unprecedented levels. This means that planning and operation of power systems can not be made possible without the aid of information technology tools and instruments. Even small systems need such aid because of the complexity factor. On the other hand, new trends have recently emerged to solve the problems arising from increased size of power systems. These trends are related to the market structure, legal, and business issues. Other trends also cover technological developments, and environmental issues. Moreover, power systems have special characteristics and features that are not duplicated in other infrastructures. All these issues confirm the need for special information technology tools and instruments which aid in planning and operation of power systems.

Developing an Energy Risk Assessment System

Throughout the last two decades many attempts took place in order policy makers and researchers to be able to measure the energy security of supply of a particular country, region and corridor. This chapter is providing an overview presentation of the Energy Security Risk Assessment System (E.S.R.A.S.) which comprises the Module of Robust Decision Making (RDM) and the Module of Energy Security Indices Calculation (ESIC). Module 1 & 2 are briefly presented throughout section 2 and the application of Module 2 in nine case study countries is discussed at section 3. Finally, in the last section are the conclusions, which summarize the main points, arisen in this chapter.

Formulating National Action Plans for Energy Business Environment

The penetration of the Renewable Energy Sources (RES) and the development of the Energy Efficiency (EE) is related to the synthesis of an appropriate action plan by each state for its energy business environment (companies such as “clean” energy producers, energy services companies etc.). The aim of this chapter is to present an information intelligent system which consists of an expert subsystem, as well as a Multi Criteria subsystem. The system supports the state towards the formulation of a modern business environment, since it incorporates the increasing needs for energy reform, successful energy planning, rational use of energy as well as climate change. The system was successfully applied to the thirteen “new” member states of the EU.

Solving Environmental/Economic Dispatch Problem

Multiobjective particle swarm optimization (MOPSO) technique for environmental/economic dispatch (EED) problem is proposed and presented in this work. The proposed MOPSO technique evolves a multiobjective version of PSO by proposing redefinition of global best and local best individuals in multiobjective optimization domain. The proposed MOPSO technique has been implemented to solve the EED problem with competing and non-commensurable cost and emission objectives. Several optimization runs of the proposed approach have been carried out on a standard test system. The results demonstrate the capabilities of the proposed MOPSO technique to generate a set of well-distributed Pareto-optimal solutions in one single run. The comparison with the different reported techniques demonstrates the superiority of the proposed MOPSO in terms of the diversity of the Pareto optimal solutions obtained. In addition, a quality measure to Pareto optimal solutions has been implemented where the results confirm the potential of the proposed MOPSO technique to solve the multiobjective EED problem and produce high quality nondominated solutions.

Setting Technology Transfer Priorities with CDM-SET

There is no much meaning in separating “good” and “bad” technologies. A definitely more critical issue is to identify “good” and “bad” technological options for a specific country & region based on its specific needs and special characteristics. In this framework, aim of this chapter is the presentation of the CDM-SET3 tool that incorporates the potential host country’s priority areas in terms of energy services and the suitable sustainable energy technologies to fulfil these needs and priorities, taking into consideration several criteria that examine the benefits in the economic, environmental and social dimension and through a MCDA approach facilitates the identification of the most proper technology alternatives to be implemented under the umbrella of CDM to a specific host country. The application of CDM-SET3 in representative case study countries is also presented and the results are discussed. Finally, in the last section are the conclusions, which summarize the main points, arisen in this chapter.

Doubly Fed Induction Generators

Adjustable speed induction generators, especially the Doubly-Fed Induction Generators (DFIG) are becoming increasingly popular due to its various advantages over fixed speed generator systems. A DFIG in a wind turbine has ability to generate maximum power with varying rotational speed, ability to control active and reactive by integration of electronic power converters such as the back-to-back converter, low rotor power rating resulting in low cost converter components, etc, DFIG have become very popular in large wind power conversion systems. This chapter presents an extensive literature survey over past 25 years on the different aspects of DFIG. Application of H8 Controller for enhanced DFIG-WT performance in terms of robust stability and reference tracking to reduce mechanical stress and vibrations is also demonstrated in the chapter.

Formulating Modern Energy Policy through a Collaborative Expert Model

Nowadays, a comprehensive and modern energy policy making, which will be characterized by clarity and transparency, is necessary. Indeed, there exists a number of energy policy and planning systems, but there are no decision support systems investigating the energy policy making in an integrated way. In this context, the main aim of this chapter is to present an expert system based on a “multidimensional” approach for the energy policy making, which also incorporates the three objectives (security of supply, competitiveness of energy market and environmental protection) and takes into consideration all the related economical, social and technological parameters. This model was successfully applied in order to support the decisions towards the development of the energy policy priorities in the developing Mediterranean Countries as well as the countries of Gulf Cooperation Council – GCC.

Use of Nerual Networks for Modeling Energy Consumption in the Residential Sector

This chapter investigates the use of neural networks (NN) for modeling of residential energy consumption. Currently, engineering and conditional demand analysis (CDA) approaches are mainly used for residential energy modeling. The studies on the use of NN for residential energy consumption modeling are limited to estimating the energy use of individual or a group of buildings. Development of a national residential end-use energy consumption model using NN approach is presented in this chapter. The comparative evaluation of the results of the model shows NN approach can be used to accurately predict and categorize the energy consumption in the residential sector as well as the other two approaches. Based on the specific advantages and disadvantages of three models, developing a hybrid model consisting of NN and engineering models is suggested.