1,547 research outputs found
Evolution of microgrids with converter-interfaced generations: Challenges and opportunities
© 2019 Elsevier Ltd Although microgrids facilitate the increased penetration of distributed generations (DGs) and improve the security of power supplies, they have some issues that need to be better understood and addressed before realising the full potential of microgrids. This paper presents a comprehensive list of challenges and opportunities supported by a literature review on the evolution of converter-based microgrids. The discussion in this paper presented with a view to establishing microgrids as distinct from the existing distribution systems. This is accomplished by, firstly, describing the challenges and benefits of using DG units in a distribution network and then those of microgrid ones. Also, the definitions, classifications and characteristics of microgrids are summarised to provide a sound basis for novice researchers to undertake ongoing research on microgrids
Risks and Prospects of Smart Electric Grids Systems measured with Real Options
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Investigation on electricity market designs enabling demand response and wind generation
Demand Response (DR) comprises some reactions taken by the end-use customers to decrease
or shift the electricity consumption in response to a change in the price of electricity or a
specified incentive payment over time. Wind energy is one of the renewable energies which
has been increasingly used throughout the world. The intermittency and volatility of
renewable energies, wind energy in particular, pose several challenges to Independent
System Operators (ISOs), paving the way to an increasing interest on Demand Response
Programs (DRPs) to cope with those challenges. Hence, this thesis addresses various
electricity market designs enabling DR and Renewable Energy Systems (RESs) simultaneously.
Various types of DRPs are developed in this thesis in a market environment, including
Incentive-Based DR Programs (IBDRPs), Time-Based Rate DR Programs (TBRDRPs) and
combinational DR programs on wind power integration. The uncertainties of wind power
generation are considered through a two-stage Stochastic Programming (SP) model. DRPs are
prioritized according to the ISO’s economic, technical, and environmental needs by means of
the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. The
impacts of DRPs on price elasticity and customer benefit function are addressed, including
the sensitivities of both DR parameters and wind power scenarios. Finally, a two-stage
stochastic model is applied to solve the problem in a mixed-integer linear programming (MILP)
approach. The proposed model is applied to a modified IEEE test system to demonstrate the
effect of DR in the reduction of operation cost.A Resposta Dinâmica dos Consumidores (DR) compreende algumas reações tomadas por estes
para reduzir ou adiar o consumo de eletricidade, em resposta a uma mudança no preço da
eletricidade, ou a um pagamento/incentivo específico. A energia eólica é uma das energias
renováveis que tem sido cada vez mais utilizada em todo o mundo. A intermitência e a
volatilidade das energias renováveis, em particular da energia eólica, acarretam vários
desafios para os Operadores de Sistema (ISOs), abrindo caminho para um interesse crescente
nos Programas de Resposta Dinâmica dos Consumidores (DRPs) para lidar com esses desafios.
Assim, esta tese aborda os mercados de eletricidade com DR e sistemas de energia renovável
(RES) simultaneamente. Vários tipos de DRPs são desenvolvidos nesta tese em ambiente de
mercado, incluindo Programas de DR baseados em incentivos (IBDRPs), taxas baseadas no
tempo (TBRDRPs) e programas combinados (TBRDRPs) na integração de energia eólica. As
incertezas associadas à geração eólica são consideradas através de um modelo de
programação estocástica (SP) de dois estágios. Os DRPs são priorizados de acordo com as
necessidades económicas, técnicas e ambientais do ISO por meio da técnica para ordem de
preferência por similaridade com a solução ideal (TOPSIS). Os impactes dos DRPs na
elasticidade do preço e na função de benefício ao cliente são abordados, incluindo as
sensibilidades dos parâmetros de DR e dos cenários de potência eólica. Finalmente, um
modelo estocástico de dois estágios é aplicado para resolver o problema numa abordagem de
programação linear inteira mista (MILP). O modelo proposto é testado num sistema IEEE
modificado para demonstrar o efeito da DR na redução do custo de operação
MCA4climate: A Practical Framework for Planning Pro-Development Climate Policy
MCA4climate is a major new UNEP initiative providing 1 Introduction practical assistance to governments in preparing their climate change mitigation and adaptation plans and strategies. It aims to help governments, particularly in developing countries, identify policies and measures that are low cost, environmentally effective and consistent with national development goals. It does this by providing a structured approach to assessing and prioritizing climate-policy options, while taking into consideration associated social, economic, environmental and institutional costs and benefits. In doing so, it seeks to counter the widely held perception that tackling climate change is costly, highlight the potential developmental benefits of addressing climate change and encourage action to that end
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