Viabilidade económica e energética do biodiesel produzido a partir de Chlorella vulgaris

Contemporaneamente o Homem depara-se com um dos grandes desafios que é o de efetivar a transição para um futuro sustentável. Assim, o setor da energia tem um papel fundamental neste processo de transição, com principal enfoque no setor dos automóveis, sendo este um setor que contribui com elevadas quantidades de gases de efeito estufa libertados para a atmosfera. Também a escassez dos recursos petrolíferos constitui um ponto fundamental no tema apresentado. Com a necessidade de combater esses problemas é que se tem vindo a tentar desenvolver combustíveis renováveis e neutros quanto às emissões. A primeira geração de biocombustíveis obtidos através de culturas agrícolas terrestres preenche em parte esses requisitos, porém, não atinge os valores da procura e ainda competem com a produção de alimentos. Daí o interesse na aposta de uma segunda geração de biocombustíveis produzidos de fontes que não pertencem à cadeia alimentar e são residuais mas, que mesmo assim não permitem satisfazer as necessidades de matériaprima. A terceira geração de biocombustíveis vem justamente responder a estas questões pois assenta em matérias-primas que não competem pela utilização do solo agrícola nem são usadas para fins alimentares, tendo produtividades areais substancialmente superiores às que as culturas convencionais ou biomassas residuais conseguem assegurar. A matéria prima de terceira geração são portanto as microalgas, cujas produtividades em biomassa são extremamente elevadas, para além de produtividades muito superiores em lípidos, hidratos de carbono e/ou outros produtos de valor elevado. No entanto, este tipo de produção de biocombustível ainda enfrenta alguns problemas técnicos que o tornam num processo dispendioso para competir economicamente com outros tipos de produção de biodiesel. Na linha do que foi dito anteriormente, este trabalho apresenta um estudo de viabilidade económica e energética do biodiesel produzido através da Chlorella vulgaris, apresentando as técnicas e resultados de cultivo da Chlorella vulgaris e posteriormente de produção do biodiesel através dos lípidos obtidos através da mesma. Para melhorar a colheita das microalgas, que é uma das fases mais dispendiosas, testou-se o aumento de pH e a adição de um floculante (Pax XL-10), sendo que o primeiro não permitiu obter resultados satisfatórios, enquanto o segundo permitiu obter resultados de rendimento na ordem dos 90%. Mesmo com a melhoria da etapa da colheita, o preço mínimo do biodiesel produzido a partir do óleo de Chlorella vulgaris, com as condições ótimas de cultivo e produtividades máximas encontradas na literatura, foi de 8,76 €/L, pois, na análise económica, o Pax XL-10 revelou-se extremamente caro para utilizar na floculação de microalgas para obtenção de um produto de baixo valor, como é o biodiesel. A não utilização da floculação reduz o preço do biodiesel para 7,85 €/L. O que se pode concluir deste trabalho é que face às técnicas utilizadas, a produção de biodiesel Chlorella vulgaris apenas, não é economicamente viável, pelo que para viabilizar a sustentabilidade do processo seria ainda necessário desenvolver mais esforços no sentido de otimizar a produção de biodiesel, eventualmente associando-a à produção de um outro biocombustível produzido a partir da biomassa extraída residual e/ou da recuperação de outros produtos de maior valor.

Energy and reserve provision dispatch considering distributed generation and demand response

In competitive electricity markets with deep concerns at the efficiency level, demand response programs gain considerable significance. In the same way, distributed generation has gained increasing importance in the operation and planning of power systems. Grid operators and utilities are taking new initiatives, recognizing the value of demand response and of distributed generation for grid reliability and for the enhancement of organized spot market´s efficiency. Grid operators and utilities become able to act in both energy and reserve components of electricity markets. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The proposed method has been computationally implemented and its application is illustrated in this paper using a 32 bus distribution network with 32 medium voltage consumers.

Distributed Generation and Demand Response Dispatch for a Virtual Power Player Energy and Reserve Provision

Recent changes in the operation and planning of power systems have been motivated by the introduction of Distributed Generation (DG) and Demand Response (DR) in the competitive electricity markets' environment, with deep concerns at the efficiency level. In this context, grid operators, market operators, utilities and consumers must adopt strategies and methods to take full advantage of demand response and distributed generation. This requires that all the involved players consider all the market opportunities, as the case of energy and reserve components of electricity markets. The present paper proposes a methodology which considers the joint dispatch of demand response and distributed generation in the context of a distribution network operated by a virtual power player. The resources' participation can be performed in both energy and reserve contexts. This methodology contemplates the probability of actually using the reserve and the distribution network constraints. Its application is illustrated in this paper using a 32-bus distribution network with 66 DG units and 218 consumers classified into 6 types of consumers.

Dispatch of distributed Energy Resources to Provide Energy and Reserve in Smart Grids using a Particle Swarm Optimization Approach

The smart grid concept is a key issue in the future power systems, namely at the distribution level, with deep concerns in the operation and planning of these systems. Several advantages and benefits for both technical and economic operation of the power system and of the electricity markets are recognized. The increasing integration of demand response and distributed generation resources, all of them mostly with small scale distributed characteristics, leads to the need of aggregating entities such as Virtual Power Players. The operation business models become more complex in the context of smart grid operation. Computational intelligence methods can be used to give a suitable solution for the resources scheduling problem considering the time constraints. This paper proposes a methodology for a joint dispatch of demand response and distributed generation to provide energy and reserve by a virtual power player that operates a distribution network. The optimal schedule minimizes the operation costs and it is obtained using a particle swarm optimization approach, which is compared with a deterministic approach used as reference methodology. The proposed method is applied to a 33-bus distribution network with 32 medium voltage consumers and 66 distributed generation units.

Distributed generation producers' reserve management

Sustainable development concerns are being addressed with increasing attention, in general, and in the scope of power industry, in particular. The use of distributed generation (DG), mainly based on renewable sources, has been seen as an interesting approach to this problem. However, the increasing of DG in power systems raises some complex technical and economic issues. This paper presents ViProd, a simulation tool that allows modeling and simulating DG operation and participation in electricity markets. This paper mainly focuses on the operation of Virtual Power Producers (VPP) which are producers’ aggregations, being these producers mainly of DG type. The paper presents several reserve management strategies implemented in the scope of ViProd and the results of a case study, based on real data.

Energy and ancillary services joint market simulation

In order to develop a flexible simulator, a variety of models for Ancillary Services (AS) negotiation has been implemented in MASCEM – a multi-agent system competitive electricity markets simulator. In some of these models, the energy and the AS are addressed simultaneously while in other models they are addressed separately. This paper presents an energy and ancillary services joint market simulation. This paper proposes a deterministic approach for solving the energy and ancillary services joint market. A case study based on the dispatch of Regulation Down, Regulation Up, Spinning Reserve, and Non-Spinning Reserve services is used to demonstrate that the use of the developed methodology is suitable for solving this kind of optimization problem. The presented case study is based on CAISO real AS market data considers fifteen bids.

ANN based day-ahead spinning reserve forecast for electricity market simulation

Electricity market players operating in a liberalized environment require adequate decision support tools, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. This paper deals with short-term predication of day-ahead spinning reserve (SR) requirement that helps the ISO to make effective and timely decisions. Based on these forecasted information, market participants can use strategic bidding for day-ahead SR market. The proposed concepts and methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Ancillary services market clearing simulation: a comparison between deterministic and heuristic methods

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tool must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case based on California Independent System Operator (CAISO) data concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Ancillary services dispatch using linear programming and genetic algorithm approaches

Electricity market players operating in a liberalized environment requires access to an adequate decision support tool, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services represent a good negotiation opportunity that must be considered by market players. For this, decision support tools must include ancillary market simulation. This paper proposes two different methods (Linear Programming and Genetic Algorithm approaches) for ancillary services dispatch. The methodologies are implemented in MASCEM, a multi-agent based electricity market simulator. A test case concerning the dispatch of Regulation Down, Regulation Up, Spinning Reserve and Non-Spinning Reserve services is included in this paper.

Angolan cymbopogon citratus used for therapeutic benefits: nutritional composition and influence of solvents in phytochemicals content and antioxidant activity of leaf extracts

Folk medicine is a relevant and effective part of indigenous healthcare systems which are, in practice, totally dependent on traditional healers. An outstanding coincidence between indigenous medicinal plant uses and scientifically proved pharmacological properties of several phytochemicals has been observed along the years. This work focused on the leaves of a medicinal plant traditionally used for therapeutic benefits (Angolan Cymbopogon citratus), in order to evaluate their nutritional value. The bioactive phytochemical composition and antioxidant activity of leaf extracts prepared with different solvents (water, methanol and ethanol) were also evaluated. The plant leaves contained ~60% of carbohydrates, protein (~20%), fat (~5%), ash (~4%) and moisture (~9%). The phytochemicals screening revealed the presence of tannins, flavonoids, and terpenoids in all extracts. Methanolic extracts also contained alkaloids and steroids. Several methods were used to evaluate total antioxidant capacity of the different extracts (DPPH; NO; and H2O2 scavenging assays, reducing power, and FRAP). Ethanolic extracts presented a significantly higher antioxidant activity (p < 0.05) except for FRAP, in which the best results were achieved by the aqueous extracts. Methanolic extracts showed the lowest radical scavenging activities for both DPPH; and NO; radicals.

Mixed integer non linear programming and artificial neural network based approach to ancillary services dispatch in competitive electricity markets

Ancillary services represent a good business opportunity that must be considered by market players. This paper presents a new methodology for ancillary services market dispatch. The method considers the bids submitted to the market and includes a market clearing mechanism based on deterministic optimization. An Artificial Neural Network is used for day-ahead prediction of Regulation Down, regulation-up, Spin Reserve and Non-Spin Reserve requirements. Two test cases based on California Independent System Operator data concerning dispatch of Regulation Down, Regulation Up, Spin Reserve and Non-Spin Reserve services are included in this paper to illustrate the application of the proposed method: (1) dispatch considering simple bids; (2) dispatch considering complex bids.

Integration in MASCEM of the Joint Dispatch of Energy and Reserves Provided by Generation and Demand Resources

The provision of reserves in power systems is of great importance in what concerns keeping an adequate and acceptable level of security and reliability. This need for reserves and the way they are defined and dispatched gain increasing importance in the present and future context of smart grids and electricity markets due to their inherent competitive environment. This paper concerns a methodology proposed by the authors, which aims to jointly and optimally dispatch both generation and demand response resources to provide the amounts of reserve required for the system operation. Virtual Power Players are especially important for the aggregation of small size demand response and generation resources. The proposed methodology has been implemented in MASCEM, a multi agent system also developed at the authors’ research center for the simulation of electricity markets.

A Multiple Criteria Utility-based Approa h for the Unit Commitment with Wind Power and Pumped Storage Hydro

The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.