Economic, environmental and mixed objective functions in non-linear process optimization using simulated annealing and tabu search

Screening of topologies developed by hierarchical heuristic procedures can be carried out by comparing their optimal performance. In this work we will be exploiting mono-objective process optimization using two algorithms, simulated annealing and tabu search, and four different objective functions: two of the net present value type, one of them including environmental costs and two of the global potential impact type. The hydrodealkylation of toluene to produce benzene was used as case study, considering five topologies with different complexities mainly obtained by including or not liquid recycling and heat integration. The performance of the algorithms together with the objective functions was observed, analyzed and discussed from various perspectives: average deviation of results for each algorithm, capacity for producing high purity product, screening of topologies, objective functions robustness in screening of topologies, trade-offs between economic and environmental type objective functions and variability of optimum solutions.

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.

Numerical solution of a PDE system with non-linear steady state conditions that translates the air stripping pollutants removal

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Spectral solution for the air stripping pollutants removal dynamic model with non linear steady state conditions

This work deals with the numerical simulation of air stripping process for the pre-treatment of groundwater used in human consumption. The model established in steady state presents an exponential solution that is used, together with the Tau Method, to get a spectral approach of the solution of the system of partial differential equations associated to the model in transient state.

Produção Sustentável em BT- Análise de Características de Contadores Inteligentes

A crescente necessidade de reduzir a dependência energética e a emissão de gases de efeito de estufa levou à adoção de uma série de políticas a nível europeu com vista a aumentar a eficiência energética e nível de controlo de equipamentos, reduzir o consumo e aumentar a percentagem de energia produzida a partir de fontes renováveis. Estas medidas levaram ao desenvolvimento de duas situações críticas para o setor elétrico: a substituição das cargas lineares tradicionais, pouco eficientes, por cargas não-lineares mais eficientes e o aparecimento da produção distribuída de energia a partir de fontes renováveis. Embora apresentem vantagens bem documentadas, ambas as situações podem afetar negativamente a qualidade de energia elétrica na rede de distribuição, principalmente na rede de baixa tensão onde é feita a ligação com a maior parte dos clientes e onde se encontram as cargas não-lineares e a ligação às fontes de energia descentralizadas. Isto significa que a monitorização da qualidade de energia tem, atualmente, uma importância acrescida devido aos custos relacionados com perdas inerentes à falta de qualidade de energia elétrica na rede e à necessidade de verificar que determinados parâmetros relacionados com a qualidade de energia elétrica se encontram dentro dos limites previstos nas normas e nos contratos com clientes de forma a evitar disputas ou reclamações. Neste sentido, a rede de distribuição tem vindo a sofrer alterações a nível das subestações e dos postos de transformação que visam aumentar a visibilidade da qualidade de energia na rede em tempo real. No entanto, estas medidas só permitem monitorizar a qualidade de energia até aos postos de transformação de média para baixa tensão, não revelando o estado real da qualidade de energia nos pontos de entrega ao cliente. A monitorização nestes pontos é feita periodicamente e não em tempo real, ficando aquém do necessário para assegurar a deteção correta de problemas de qualidade de energia no lado do consumidor. De facto, a metodologia de monitorização utilizada atualmente envolve o envio de técnicos ao local onde surgiu uma reclamação ou a um ponto de medição previsto para instalar um analisador de energia que permanece na instalação durante um determinado período de tempo. Este tipo de monitorização à posteriori impossibilita desde logo a deteção do problema de qualidade de energia que levou à reclamação, caso não se trate de um problema contínuo. Na melhor situação, o aparelho poderá detetar uma réplica do evento, mas a larga percentagem anomalias ficam fora deste processo por serem extemporâneas. De facto, para detetar o evento que deu origem ao problema é necessário monitorizar permanentemente a qualidade de energia. No entanto este método de monitorização implica a instalação permanente de equipamentos e não é viável do ponto de vista das empresas de distribuição de energia já que os equipamentos têm custos demasiado elevados e implicam a necessidade de espaços maiores nos pontos de entrega para conter os equipamentos e o contador elétrico. Uma alternativa possível que pode tornar viável a monitorização permanente da qualidade de energia consiste na introdução de uma funcionalidade de monitorização nos contadores de energia de determinados pontos da rede de distribuição. Os contadores são obrigatórios em todas as instalações ligadas à rede, para efeitos de faturação. Tradicionalmente estes contadores são eletromecânicos e recentemente começaram a ser substituídos por contadores inteligentes (smart meters), de natureza eletrónica, que para além de fazer a contagem de energia permitem a recolha de informação sobre outros parâmetros e aplicação de uma serie de funcionalidades pelo operador de rede de distribuição devido às suas capacidades de comunicação. A reutilização deste equipamento com finalidade de analisar a qualidade da energia junto dos pontos de entrega surge assim como uma forma privilegiada dado que se trata essencialmente de explorar algumas das suas características adicionais. Este trabalho tem como objetivo analisar a possibilidade descrita de monitorizar a qualidade de energia elétrica de forma permanente no ponto de entrega ao cliente através da utilização do contador elétrico do mesmo e elaborar um conjunto de requisitos para o contador tendo em conta a normalização aplicável, as características dos equipamentos utilizados atualmente pelo operador de rede e as necessidades do sistema elétrico relativamente à monitorização de qualidade de energia.

Short-term scheduling considering five-minute and hour-ahead energy resource management

The introduction of new distributed energy resources, based on natural intermittent power sources, in power systems imposes the development of new adequate operation management and control methods. This paper proposes a short-term Energy Resource Management (ERM) methodology performed in two phases. The first one addresses the hour-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. Both phases consider the day-ahead resource scheduling solution. The ERM scheduling is formulated as an optimization problem that aims to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixed-integer non-linear programming approach and by a heuristic approach based on genetic algorithms. A case study considering a distribution network with 33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units has been implemented in a PSCADbased simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.

Distributed energy resource short-term scheduling using signaled particle swarm optimization

Distributed Energy Resources (DER) scheduling in smart grids presents a new challenge to system operators. The increase of new resources, such as storage systems and demand response programs, results in additional computational efforts for optimization problems. On the other hand, since natural resources, such as wind and sun, can only be precisely forecasted with small anticipation, short-term scheduling is especially relevant requiring a very good performance on large dimension problems. Traditional techniques such as Mixed-Integer Non-Linear Programming (MINLP) do not cope well with large scale problems. This type of problems can be appropriately addressed by metaheuristics approaches. This paper proposes a new methodology called Signaled Particle Swarm Optimization (SiPSO) to address the energy resources management problem in the scope of smart grids, with intensive use of DER. The proposed methodology’s performance is illustrated by a case study with 99 distributed generators, 208 loads, and 27 storage units. The results are compared with those obtained in other methodologies, namely MINLP, Genetic Algorithm, original Particle Swarm Optimization (PSO), Evolutionary PSO, and New PSO. SiPSO performance is superior to the other tested PSO variants, demonstrating its adequacy to solve large dimension problems which require a decision in a short period of time.

An optimal scheduling problem in distribution networks considering V2G

This paper addresses the problem of energy resource scheduling. An aggregator will manage all distributed resources connected to its distribution network, including distributed generation based on renewable energy resources, demand response, storage systems, and electrical gridable vehicles. The use of gridable vehicles will have a significant impact on power systems management, especially in distribution networks. Therefore, the inclusion of vehicles in the optimal scheduling problem will be very important in future network management. The proposed particle swarm optimization approach is compared with a reference methodology based on mixed integer non-linear programming, implemented in GAMS, to evaluate the effectiveness of the proposed methodology. The paper includes a case study that consider a 32 bus distribution network with 66 distributed generators, 32 loads and 50 electric vehicles.

Genetic algorithm methodology applied to intelligent house control

In recent years the use of several new resources in power systems, such as distributed generation, demand response and more recently electric vehicles, has significantly increased. Power systems aim at lowering operational costs, requiring an adequate energy resources management. In this context, load consumption management plays an important role, being necessary to use optimization strategies to adjust the consumption to the supply profile. These optimization strategies can be integrated in demand response programs. The control of the energy consumption of an intelligent house has the objective of optimizing the load consumption. This paper presents a genetic algorithm approach to manage the consumption of a residential house making use of a SCADA system developed by the authors. Consumption management is done reducing or curtailing loads to keep the power consumption in, or below, a specified energy consumption limit. This limit is determined according to the consumer strategy and taking into account the renewable based micro generation, energy price, supplier solicitations, and consumers’ preferences. The proposed approach is compared with a mixed integer non-linear approach.

Distribution network short term scheduling in Smart Grid context

The large increase of Distributed Generation (DG) in Power Systems (PS) and specially in distribution networks makes the management of distribution generation resources an increasingly important issue. Beyond DG, other resources such as storage systems and demand response must be managed in order to obtain more efficient and “green” operation of PS. More players, such as aggregators or Virtual Power Players (VPP), that operate these kinds of resources will be appearing. This paper proposes a new methodology to solve the distribution network short term scheduling problem in the Smart Grid context. This methodology is based on a Genetic Algorithms (GA) approach for energy resource scheduling optimization and on PSCAD software to obtain realistic results for power system simulation. The paper includes a case study with 99 distributed generators, 208 loads and 27 storage units. The GA results for the determination of the economic dispatch considering the generation forecast, storage management and load curtailment in each period (one hour) are compared with the ones obtained with a Mixed Integer Non-Linear Programming (MINLP) approach.