Schedule

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CIO Springer TAP Compal BES FCT
Schedule
SB5 Energy markets
[CONTRIBUTED SESSION]

Chair: Anett Grossmann, GWS, Germany
Room 3.1.6

 

SB5.1
A powerful tool for forecasting and scenario analysis: The Russian Economic-Environmental-Emission model e3.ru

Anett Grossmann (grossmann@gws-os.de), Frank Hohmann (hohmann@gws-os.de)
For many years, macroeconomic models have been used as tools for analyzing complex economic, social and environmental structures as well as to perform and evaluate future policy measures. Many economic models exist but they differ in aspects such as used data sets, size, econometric methods, underlying economic theory and model building environments. Such models usually can only be used and maintained by those people who build them. The complexity of the models and the required expert knowledge leads to the criticism that models are considered a "black box". Within the project “Support to the Development of New Generation Models to estimate and forecast Greenhouse Gas Emissions and Efficiency of Russian Climate Change Mitigation Measures and Policy" (EuropeAid/129527/C/SER/RU), GWS had to develop a comprehensive model for Russia comprising the 3 e’s (economy, environment, emissions). The model integrates the economy at the industry level given by the structure of Input-Output tables and considers all market actors (i.e. consumers, government and corporations). The environmental module consists of an energy and land use module. The energy module represents energy supply, transformation and consumption by energy carriers as stated in the energy balance. The emission module covers emissions from fuel combustion processes and non combustion-related GHG as well as carbon sinks. Another key requirement was to deliver the model to policy makers so that they can quickly perform and compare a large number of different scenario calculations up to 2050 with a focus on Russian Climate Change Mitigation Measures and Policy. GWS provided a graphical user interface named IMAGINE© in English and Russian to carry out different tasks such as scenario design, calculation and analysis. Additionally, the user interface comes with an information system that contains the complete interactive hyper-linked set of model variables and equations.

Keywords: macroeconomic multi-sectoral model, scenario analysis, graphical user interface

 

SB5.2
Integrating Consumption and Reserve Strategies for Large Consumers in Electricity Markets

Nigel Cleland (nigel.cleland@gmail.com), Golbon Zakeri (g.zakeri@auckland.ac.nz), Brent Young (b.young@auckland.ac.nz), Geoff Pritchard (g.pritchard@auckland.ac.nz)
In this paper we present a simulation tool for large consumers to optimise their consumption and reserve offers in a security constrained electricity market. We utilise a replica of the NZEM market clearing software, vSPD which has security constrained generation and transmission and accurately recreates final prices. We use a series of small optimal power flow to illustrate how security constraints can influence prices. We study a five year time horizon to investigate the occurrence of security constrained pricing behaviour in the NZEM final prices. A large energy consumer may utilize our tool to assess their impact upon the prices, taking into account the instances of security constraints. We expect this approach to be extensible to other markets although we note that information surrounding the underlying market structure will heavily influence the viability.

Keywords: Electricty, simulation, optimisation

 

SB5.3
An analysis of Multiple Objective Methods in the Offshore Wind Sector

Dylan Jones (dylan.jones@port.ac.uk), Graham Wall (graham.wall@port.ac.uk)
An overview of the multiple objectives that arise in the offshore wind sector, categorised by commonly arising problem area, will be presented. The nature of the objectives and the modelling and solution techniques used will also be detailed. Major gaps in the literature will be identified using the authors’ expertise gained by work on three European level offshore wind research projects. Each of these gap fields will be analysed and potential model formulations and solution techniques discussed, with particular emphasis on the challenges of modelling multiple stakeholder preferences. The envisaged computational challenges in solving the arising models will also be discussed. A demonstrative goal programming model will then be formulated for one multi-objective situation, using the state-of-the-art extended goal programming methodology. An appropriate weight sensitivity analysis algorithm in meta-objective space will then be described and used to generate multiple solutions that will give a range of solutions in accordance with the stakeholder’s preferences. A discussion of the results of the model in the context of the European Offshore wind sector will be given.

Keywords: Multiple Criteria Decision Making, Renewable Energy, Goal Programming