Cost Allocation Model for Distribution Networks Considering High Penetration of Distributed Energy Resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitiveenvironment of electricity markets impose the use of new approaches in several domains. The networkcost allocation, traditionally used in transmission networks, should be adapted and used in the distribu-tion networks considering the specifications of the connected resources. The main goal is to develop afairer methodology trying to distribute the distribution network use costs to all players which are usingthe network in each period. In this paper, a model considering different type of costs (fixed, losses, andcongestion costs) is proposed comprising the use of a large set of DER, namely distributed generation(DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehi-cles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). Theproposed model includes three distinct phases of operation. The first phase of the model consists in aneconomic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen’s andBialek’s tracing algorithms are used and compared to evaluate the impact of each resource in the net-work. Finally, the MW-mile method is used in the third phase of the proposed model. A distributionnetwork of 33 buses with large penetration of DER is used to illustrate the application of the proposedmodel.

Demand Response Programs Design and Use Considering Intensive Penetration of Distributed Generation

Further improvements in demand response programs implementation are needed in order to take full advantage of this resource, namely for the participation in energy and reserve market products, requiring adequate aggregation and remuneration of small size resources. The present paper focuses on SPIDER, a demand response simulation that has been improved in order to simulate demand response, including realistic power system simulation. For illustration of the simulator’s capabilities, the present paper is proposes a methodology focusing on the aggregation of consumers and generators, providing adequate tolls for the demand response program’s adoption by evolved players. The methodology proposed in the present paper focuses on a Virtual Power Player that manages and aggregates the available demand response and distributed generation resources in order to satisfy the required electrical energy demand and reserve. The aggregation of resources is addressed by the use of clustering algorithms, and operation costs for the VPP are minimized. The presented case study is based on a set of 32 consumers and 66 distributed generation units, running on 180 distinct operation scenarios.

Cost allocation model for distribution networks considering high penetration of distributed energy resources

The high penetration of distributed energy resources (DER) in distribution networks and the competitive environment of electricity markets impose the use of new approaches in several domains. The network cost allocation, traditionally used in transmission networks, should be adapted and used in the distribution networks considering the specifications of the connected resources. The main goal is to develop a fairer methodology trying to distribute the distribution network use costs to all players which are using the network in each period. In this paper, a model considering different type of costs (fixed, losses, and congestion costs) is proposed comprising the use of a large set of DER, namely distributed generation (DG), demand response (DR) of direct load control type, energy storage systems (ESS), and electric vehicles with capability of discharging energy to the network, which is known as vehicle-to-grid (V2G). The proposed model includes three distinct phases of operation. The first phase of the model consists in an economic dispatch based on an AC optimal power flow (AC-OPF); in the second phase Kirschen's and Bialek's tracing algorithms are used and compared to evaluate the impact of each resource in the network. Finally, the MW-mile method is used in the third phase of the proposed model. A distribution network of 33 buses with large penetration of DER is used to illustrate the application of the proposed model.

A multi-objective evaluation of the impact of the penetration of Distributed Generation

This paper proposes a methodology to consider the effects of the integration of DG on planning. Since DG has potential to defer investments in networks, the impact of DG on grid capacity is evaluated. A multi-objective optimization tool based on the meta-heuristic MEPSO is used, supporting an alternative approach to exploiting the Pareto front features. Tests were performed in distinct conditions with two well-known distribution networks: IEEE-34 and IEEE-123. The results combined minimization and maximization in order to produce different Pareto fronts and determine the extent of the impact caused by DG. The analysis provides useful information, such as the identification of futures that should be considered in planning. A future means a set of realizations of all uncertainties. MEPSO also presented a satisfactory performance in obtaining the Pareto fronts. © 2011 IEEE.

Maximização da penetração da geração distribuída através do algoritmo de otimização nuvem de partículas

This work develops a methodology for defining the maximum active power being injected into predefined nodes in the studied distribution networks, considering the possibility of multiple accesses of generating units. The definition of these maximum values is obtained from an optimization study, in which further losses should not exceed those of the base case, i.e., without the presence of distributed generation. The restrictions on the loading of the branches and voltages of the system are respected. To face the problem it is proposed an algorithm, which is based on the numerical method called particle swarm optimization, applied to the study of AC conventional load flow and optimal load flow for maximizing the penetration of distributed generation. Alternatively, the Newton-Raphson method was incorporated to resolution of the load flow. The computer program is performed with the SCILAB software. The proposed algorithm is tested with the data from the IEEE network with 14 nodes and from another network, this one from the Rio Grande do Norte State, at a high voltage (69 kV), with 25 nodes. The algorithm defines allowed values of nominal active power of distributed generation, in percentage terms relative to the demand of the network, from reference values

The influence of positive or negative charges in the passive and iontophoretic skin penetration of porphyrins used in photodynamic therapy

Meso-tetra-(N-methylpiridinium-4-yl)-porphyrin (TMPyP) and meso-tetra-(4-sulfonatophenyl)-porphyrin (TPPS(4)) are photosensitizing drugs (PS) used in photodynamic therapy (PDT). Based on the fact that these compounds present similar chemical structures but opposite charges at pH levels near physiological conditions, this work aims to evaluate the in vitro and in vivo influence of these electrical charges on the iontophoretic delivery of TMPyP and TPPS4, attempting to achieve maximum accumulation of PS in skin tissue. The iontophoretic transport of these drugs from a hydrophilic gel was investigated in vitro using porcine ear skin and vertical, flow-through diffusion cells. In vivo experiments using rats were also carried out, and the penetration of the PSs was analyzed by fluorescence microscopy to visualize the manner of how these compounds were distributed in the skin after a short period of iontophoresis application. In vitro, both passive and iontophoretic delivery of the positively charged TMPyP were much greater (20-fold and 67-fold, respectively) than those of the negatively charged TPPS(4). TPPS(4) iontophoresis in vivo increased the fluorescence of the skin only in the very superficial layers. On the other hand, iontophoresis of the positively charged drug expressively increased the rat epidermis and dermis fluorescence, indicating high amounts of this drug throughout the skin layers. Moreover, TMPyP was homogeneously distributed around and into the nuclei of the skin cells, suggesting its potential use in topical PDT. (C) 2010 Elsevier B.V. All rights reserved.

ANN-Based LMP forecasting in a distribution network with large penetration of DG

In recent years, power systems have experienced many changes in their paradigm. The introduction of new players in the management of distributed generation leads to the decentralization of control and decision-making, so that each player is able to play in the market environment. In the new context, it will be very relevant that aggregator players allow midsize, small and micro players to act in a competitive environment. In order to achieve their objectives, virtual power players and single players are required to optimize their energy resource management process. To achieve this, it is essential to have financial resources capable of providing access to appropriate decision support tools. As small players have difficulties in having access to such tools, it is necessary that these players can benefit from alternative methodologies to support their decisions. This paper presents a methodology, based on Artificial Neural Networks (ANN), and intended to support smaller players. In this case the present methodology uses a training set that is created using energy resource scheduling solutions obtained using a mixed-integer linear programming (MIP) approach as the reference optimization methodology. The trained network is used to obtain locational marginal prices in a distribution network. The main goal of the paper is to verify the accuracy of the ANN based approach. Moreover, the use of a single ANN is compared with the use of two or more ANN to forecast the locational marginal price.

Maximum penetration of microgeneration photovoltaic panels in distribution network

In smart grids context, the distributed generation units based in renewable resources, play an important rule. The photovoltaic solar units are a technology in evolution and their prices decrease significantly in recent years due to the high penetration of this technology in the low voltage and medium voltage networks supported by governmental policies and incentives. This paper proposes a methodology to determine the maximum penetration of photovoltaic units in a distribution network. The paper presents a case study, with four different scenarios, that considers a 32-bus medium voltage distribution network and the inclusion storage units.

Multi-objective evolutionary particle swarm optimization in the assessment of the impact of distributed generation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Time-series-based maximization of distributed wind power generation integration

Energy policies and technological progress in the development of wind turbines have made wind power the fastest growing renewable power source worldwide. The inherent variability of this resource requires special attention when analyzing the impacts of high penetration on the distribution network. A time-series steady-state analysis is proposed that assesses technical issues such as energy export, losses, and short-circuit levels. A multiobjective programming approach based on the nondominated sorting genetic algorithm (NSGA) is applied in order to find configurations that maximize the integration of distributed wind power generation (DWPG) while satisfying voltage and thermal limits. The approach has been applied to a medium voltage distribution network considering hourly demand and wind profiles for part of the U.K. The Pareto optimal solutions obtained highlight the drawbacks of using a single demand and generation scenario, and indicate the importance of appropriate substation voltage settings for maximizing the connection of MPG.

Distributed generators as providers of reactive power support - A market approach

Traditionally, ancillary services are supplied by large conventional generators. However, with the huge penetration of distributed generators (DGs) as a result of the growing interest in satisfying energy requirements, and considering the benefits that they can bring along to the electrical system and to the environment, it appears reasonable to assume that ancillary services could also be provided by DGs in an economical and efficient way. In this paper, a settlement procedure for a reactive power market for DGs in distribution systems is proposed. Attention is directed to wind turbines connected to the network through synchronous generators with permanent magnets and doubly-fed induction generators. The generation uncertainty of this kind of DG is reduced by running a multi-objective optimization algorithm in multiple probabilistic scenarios through the Monte Carlo method and by representing the active power generated by the DGs through Markov models. The objectives to be minimized are the payments of the distribution system operator to the DGs for reactive power, the curtailment of transactions committed in an active power market previously settled, the losses in the lines of the network, and a voltage profile index. The proposed methodology was tested using a modified IEEE 37-bus distribution test system. © 1969-2012 IEEE.

Multi-objective analysis of impacts of distributed generation placement on the operational characteristics of networks for distribution system planning

Recent advances in energy technology generation and new directions in electricity regulation have made distributed generation (DG) more widespread, with consequent significant impacts on the operational characteristics of distribution networks. For this reason, new methods for identifying such impacts are needed, together with research and development of new tools and resources to maintain and facilitate continued expansion towards DG. This paper presents a study aimed at determining appropriate DG sites for distribution systems. The main considerations which determine DG sites are also presented, together with an account of the advantages gained from correct DG placement. The paper intends to define some quantitative and qualitative parameters evaluated by Digsilent (R), GARP3 (R) and DSA-GD software. A multi-objective approach based on the Bellman-Zadeh algorithm and fuzzy logic is used to determine appropriate DG sites. The study also aims to find acceptable DG locations both for distribution system feeders, as well as for nodes inside a given feeder. (C) 2010 Elsevier Ltd. All rights reserved.

Modeling of Distributed Control Systems in Intelligent Building based on Colored Petri Nets

Distributed control systems consist of sensors, actuators and controllers, interconnected by communication networks and are characterized by a high number of concurrent process. This work presents a proposal for a procedure to model and analyze communication networks for distributed control systems in intelligent building. The approach considered for this purpose is based on the characterization of the control system as a discrete event system and application of coloured Petri net as a formal method for specification, analysis and verification of control solutions. With this approach, we develop the models that compose the communication networks for the control systems of intelligent building, which are considered the relationships between the various buildings systems. This procedure provides a structured development of models, facilitating the process of specifying the control algorithm. An application example is presented in order to illustrate the main features of this approach.

Penetration of hydrolysed soy protein-added brine and its effect on yield and pH of beef steaks from the biceps femoris muscle

This study was aimed to evaluate the penetration behaviour of different brines with tumbled beef steaks from the biceps femoris muscle, specifically their interactions with pH and effects on yield. Six muscles from different animals, divided into origin (OP) and insertion (IP) portions, were cut into 60 steaks of 2.5 cm thickness and tumbled for 30 or 60 min. The steaks were tumbled with two brines, with (WTB/HSP) or without (WTB) hydrolysed soy protein (HSP), and steaks that were not tumbled with brine or water were used as controls. Brine penetration was verified by measuring the amount of dye-containing brine (absorbance at 627 nm) recovered from homogenates of four thin (2 mm) slices from the surface of the beef steaks after tumbling. The WTB/HSP steaks exhibited greater (P < 0.05) brine penetration when tumbled for 60 min than for 30 min. The OP steaks showed greater yield and lower pH (P < 0.05) than IP steaks. HSP-added brine increased the water absorption and retention in the first slices of the steaks, and its efficiency was increased with a longer tumbling time. The portion of the biceps femoris muscle used influenced brine absorption and retention, impacting meat yield. (C) 2010 Elsevier Ltd. All rights reserved.

Skin Penetration of Epigallocatechin-3-Gallate and Quercetin from Green Tea and Ginkgo biloba Extracts Vehiculated in Cosmetic Formulations

Green tea (Camellia sinensis) and Ginkgo biloba extracts in cosmetic formulations have been suggested to protect the skin against UV-induced damage and skin ageing. Thus, it is very important to assess the human skin penetration of their major flavonoids to verify if they penetrate and remain in the skin to exert their proposed effects. The aim of this study was to evaluate the human skin penetration of epigallocatechin-3-gallate (EGCG) and quercetin from green tea and G. biloba extracts vehiculated in cosmetic formulations. This study was conducted with fresh dermatomed human Caucasian skin from abdominal surgery mounted on static Franz diffusion cells. Skin samples were mounted between two diffusion half-cells and 10 mg/cm(2) of formulations supplemented with 6% of green tea or G. biloba extract were applied on the skin surface. The receptor fluid was removed after 6 and 24 h and analyzed by high-performance liquid chromatography for the quantification of the flavonoids. The stratum corneum was removed by tape stripping and immersed in methanol and the epidermis was mechanically separated from the dermis and triturated in methanol to extract EGCG and quercetin. The results showed that the flavonoids under study penetrated into the skin, without reaching the receptor fluid. The majority of EGCG was quantified in the stratum corneum (0.87 mu g/cm(2)), which was statistically higher than the EGCG concentrations found in viable epidermis (0.54 mu g/cm(2)) and in the dermis (0.38 mu g/cm(2)). The majority of quercetin was quantified in the viable epidermis (0.23 mu g/cm(2)), which was statistically higher than the EGCG concentration found in the stratum corneum layer (0.17 mu g/cm(2)). Finally, it can be concluded that EGCG and quercetin from green tea and G. biloba extracts vehiculated in cosmetic formulations presented good skin penetration and retention, which can favor their skin effects. Copyright (C) 2009 S. Karger AG, Basel