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- Virtual Inertia and Mechanical Power-Based Control Strategy to Provide Stable Grid Operation under High Renewables PenetrationPublication . Mehrasa, Majid; Pouresmaeil, Edris; Soltani, Hamid; Blaabjerg, Frede; Calado, M. do Rosário; Catalão, JoãoThis paper presents a virtual inertia and mechanical power-based control strategy to provide a stable operation of the power grid under high penetration of renewable energy sources (RESs). The proposed control technique is based on a new active and reactive power-based dynamic model with the permanent magnet synchronous generator (PMSG) swing equation, in which all PMSG features i.e., inertia and mechanical power are embedded within the controller as the main contribution of this paper. To present an accurate analysis of the virtual PMSG-based parameters, the desired zero dynamics of the grid angular frequency are considered to evaluate the effects of virtual mechanical power (VMP) on the active and reactive power sharing, as well as the investigation of virtual inertia variations for the grid angular frequency responses. Moreover, by considering various active power errors and virtual inertia, the impacts of active power error on reactive power in the proposed control technique, are precisely assessed. Simulation results are employed in Matlab/Simulink software to verify the stabilizing abilities of the proposed control technique.
- Real-Time Scheduling of Demand Response Options Considering the Volatility of Wind Power GenerationPublication . Talari, Saber; Shafie-khah, Miadreza; Chen, Yue; Wei, Wei; Gaspar, Pedro Dinis; Catalão, J. P. S.In this paper, a new methodology to unleash the potential of demand response (DR) in real-time is presented. Customers may tend to apply their DR potential in the real-time market in addition to their scheduled potential in the day-ahead stage. Thus, the proposed method facilitates balancing the realtime market via DR aggregators (DRAs). It can be vital once the stochastic variables of the network such as production of wind power generators (WPG) do not follow the forecasted production in real-time and have some distortions. Two-stage stochastic programming is employed to schedule some DR options in both day-ahead and real-time markets. DR options in real-time are scheduled based on possible scenarios that reflect the behaviors of wind power generation and are generated through Monte-Carlo simulation method. The merits of the method are demonstrated in a 6-bus case study and in the IEEE RTS-96, which shows a reduction in total operation cost.
- Large-Scale Grid Integration of Renewable Energy Resources with a Double Synchronous ControllerPublication . Mehrasa, Majid; Pouresmaeil, Edris; Soltani, Hamid; Blaabjerg, Frede; Calado, M. do Rosário; Catalao, J.P.S.This paper provides virtual inertia and mechanical power-based double synchronous controller (DSC) for power converters based on the d- and q-components of the converter current to assure the stable operation of the grid with the penetration of large-scale renewable energy resources (RERs). The DSC is projected based on emulating both the inertia and mechanical power variables of the synchronous generators (SGs), and its performance is compared with a non-synchronous controller (NSC) that is without these emulations. The main contributions of the DSC are providing a large margin of stability for the power grid with a wide area of low and high values of virtual inertia, also improving significantly power grid stability (PGS) with changing properly the embedded virtual variables of inertia, mechanical power, and also mechanical power error. Also, decoupling features of the proposed DSC in which both d and q components are completely involved with the characteristics of SGs as well as the relationship between the interfaced converter and dynamic models of SGs are other important contributions of the DSC over the existing control methods. Embedding some coefficients for the proposed DSC to show its robustness against the unknown intrinsic property of parameters is another contribution in this paper. Moreover, several transfer functions are achieved and analyzed that confirm a more stable performance of the emulated controller in comparison with the NSC for power-sharing characteristics. Simulation results confirm the superiority of the proposed DSC in comparison with other existing control techniques, e.g., the NSC techniques.
- Demand Response-Based Operation Model in Electricity Markets With High Wind Power PenetrationPublication . Hajibandeh, Neda; Shafie-khah, Miadreza; Talari, Saber; Dehghan, Shahab; Amjady, Nima; Mariano, S.; Catalão, JoãoThe issue of climate change has received considerable attention in recent decades. Therefore, renewable energies and especially wind units have become a central point of attention. To cope with the uncertainties of wind power generation, resulting from the intermittent nature of this kind of energy, this paper proposes a Demand Response (DR) based operation approach. In other words, unlike the previous models in the literature that considered a supplementary role for the DR, this paper introduces the main role for the DR in the operation of future electricity markets. This approach focuses on a comprehensive modeling of the Demand Response Programs (DRPs) for the operational scheduling of electricity markets, considering the uncertainties of the generation of wind turbines, aiming at increasing the network security and decreasing the operation cost. The incorporation of market-based DRPs such as Demand Bidding (DB) and Ancillary Service Demand Response (ASDR) is also considered. Two novel quantitative indices are introduced to analyze the success of DRPs regarding efficiency and wind integration. Numerical results obtained on two IEEE test systems indicate the effectiveness of the proposed model.
- Novas Metodologias de Optimização em Sistemas de Energia HidrotérmicosPublication . Catalão, João Paulo da Silva; Mariano, Sílvio José Pinto Simões; Ferreira, Luís António Fialho MarcelinoEsta dissertação incide sobre o tema da optimização em sistemas de energia hidrotérmicos, evoluindo no contexto actual de reestruturação do sector eléctrico. Novas metodologias baseadas em optimização não linear e optimização multiobjectivo são propostas, respectivamente, para a exploração de recursos hídricos, tendo em consideração o efeito de queda, e para a exploração de recursos térmicos, tendo em consideração a restrição de emissões, concretizando assim contribuições originais para o progresso no conhecimento. Ainda, é desenvolvida uma ferramenta computacional, baseada em redes neuronais artificiais, para a previsão dos preços da energia eléctrica no apoio à decisão em ambiente competitivo. Os resultados obtidos em casos de estudo realísticos permitem concluir sobre o desempenho das novas metodologias de optimização propostas nesta dissertação.
- Short-term electricity prices forecasting in a competitive market: A neural network approachPublication . Catalão, J. P. S.; Mariano, S.; Mendes, V. M. F.; Ferreira, L. A. F. M.This paper proposes a neural network approach for forecasting short-term electricity prices. Almost until the end of last century, electricity supply was considered a public service and any price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices and technical improvements. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive electricity markets. In this new competitive framework, short-term price forecasting is required by producers and consumers to derive their bidding strategies to the electricity market. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgement of future price movements, and for consumers to maximize their utilities. A three-layered feedforward neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of mainland Spain and California.
- Parameterisation effect on the behaviour of a head-dependent hydro chain using a nonlinear modelPublication . Catalão, João Paulo da Silva; Mariano, S.; Mendes, V. M. F.; Ferreira, L. A. F. M.This paper is on the problem of short-term hydro scheduling (STHS), particularly concerning a head-dependent hydro chain. We use a method based on nonlinear programming (NLP), namely quadratic programming, to consider hydroelectric power generation a function of water discharge and of the head. The method has been applied successfully to solve a test case based on a realistic cascaded hydro system with a negligible computational time requirement and is also applied to show that the role played by reservoirs in the hydro chain do not depend only on their relative position. As a new contribution to earlier studies, which presented reservoir operation rules mainly for medium and long-term planning procedures, we show that the physical data defining hydro chain parameters used in the nonlinear model have an effect on the STHS, implying different optimal storage trajectories for the reservoirs accordingly not only with their position in the hydro chain but also with the new parameterisation defining the data for the hydro system. Moreover, considering head dependency in the hydroelectric power generation, usually neglected for hydro plants with a large storage capacity, provides a better short-term management of the conversion of the potential energy available in the reservoirs into electric energy, which represents a major advantage for the hydroelectric utilities in a competitive electricity market.
- Planeamento Operacional de Curto Prazo de Sistemas de Energia HidroeléctricosPublication . Catalão, João Paulo da Silva; Ferreira, Luís António Fialho MarcelinoEsta tese incide sobre o problema de planeamento operacional de curto prazo de sistemas de energia hidroeléctricos e os aspectos algorítmicos da sua solução. Recursos baseados em aproveitamentos hidroeléctricos com capacidades de armazenamento reduzidas são classificados como fio de água. Tipicamente, considera-se que estes recursos operam em condições estacionárias com altura de queda constante e ao nível máximo de água nos reservatórios, correspondendo, em regra e por projecto, ao ponto de operação óptimo. Contudo, é muitas vezes desejável alterar esta política, incorrendo-se, por isso, em variações da altura de queda. Devido ao reduzido volume de água nos reservatórios, a altura de queda pode variar rapidamente e a eficiência de operação torna-se sensível à altura de queda – efeito de variação da altura de queda. Assim, a potência gerada é função não só do caudal de água turbinado mas também da altura de queda. Este efeito não linear conjuntamente com a configuração hidráulica em cascata torna o problema complexo e de grande dimensão. Este estudo propõe e compara métodos de optimização baseados em programação dinâmica, linear e não linear em rede. Os resultados da simulação computacional mostram que a programação não linear em rede é o método de optimização mais apropriado.