A new intelligent algorithm for online voltage stability assessment and monitoring

This paper presents a new approach for assessing power system voltage stability based on artificial feed forward neural network (FFNN). The approach uses real and reactive power, as well as voltage vectors for generators and load buses to train the neural net (NN). The input properties of the NN are generated from offline training data with various simulated loading conditions using a conventional voltage stability algorithm based on the L-index. The performance of the trained NN is investigated on two systems under various voltage stability assessment conditions. Main advantage is that the proposed approach is fast, robust, accurate and can be used online for predicting the L-indices of all the power system buses simultaneously. The method can also be effectively used to determining local and global stability margin for further improvement measures.

Lake sediment research as a part of lake management - case studies and implications from southern Finland

In Finland one of the most important current issues in the environmental management is the quality of surface waters. The increasing social importance of lakes and water systems has generated wide-ranging interest in lake restoration and management, concerning especially lakes suffering from eutrophication, but also from other environmental impacts. Most of the factors deteriorating the water quality in Finnish lakes are connected to human activities. Especially since the 1940's, the intensified farming practices and conduction of sewage waters from scattered settlements, cottages and industry have affected the lakes, which simultaneously have developed in to recreational areas for a growing number of people. Therefore, this study was focused on small lakes, which are human impacted, located close to settlement areas and have a significant value for local population. The aim of this thesis was to obtain information from lake sediment records for on-going lake restoration activities and to prove that a well planned, properly focused lake sediment study is an essential part of the work related to evaluation, target consideration and restoration of Finnish lakes. Altogether 11 lakes were studied. The study of Lake Kaljasjärvi was related to the gradual eutrophication of the lake. In lakes Ormajärvi, Suolijärvi, Lehee, Pyhäjärvi and Iso-Roine the main focus was on sediment mapping, as well as on the long term changes of the sedimentation, which were compared to Lake Pääjärvi. In Lake Hormajärvi the role of different kind of sedimentation environments in the eutrophication development of the lake's two basins were compared. Lake Orijärvi has not been eutrophied, but the ore exploitation and related acid main drainage from the catchment area have influenced the lake drastically and the changes caused by metal load were investigated. The twin lakes Etujärvi and Takajärvi are slightly eutrophied, but also suffer problems associated with the erosion of the substantial peat accumulations covering the fringe areas of the lakes. These peat accumulations are related to Holocene water level changes, which were investigated. The methods used were chosen case-specifically for each lake. In general, acoustic soundings of the lakes, detailed description of the nature of the sediment and determinations of the physical properties of the sediment, such as water content, loss on ignition and magnetic susceptibility were used, as was grain size analysis. A wide set of chemical analyses was also used. Diatom and chrysophycean cyst analyses were applied, and the diatom inferred total phosphorus content was reconstructed. The results of these studies prove, that the ideal lake sediment study, as a part of a lake management project, should be two-phased. In the first phase, thoroughgoing mapping of sedimentation patterns should be carried out by soundings and adequate corings. The actual sampling, based on the preliminary results, must include at least one long core from the main sedimentation basin for the determining the natural background state of the lake. The recent, artificially impacted development of the lake can then be determined by short-core and surface sediment studies. The sampling must be focused on the basis of the sediment mapping again, and it should represent all different sedimentation environments and bottom dynamic zones, considering the inlets and outlets, as well as the effects of possible point loaders of the lake. In practice, the budget of the lake management projects of is usually limited and only the most essential work and analyses can be carried out. The set of chemical and biological analyses and dating methods must therefore been thoroughly considered and adapted to the specific management problem. The results show also, that information obtained from a properly performed sediment study enhances the planning of the restoration, makes possible to define the target of the remediation activities and improves the cost-efficiency of the project.

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

Analysis of cool roof coatings for residential demand side management in tropical Australia

Cool roof coatings have a beneficial impact on reducing the heat load of a range of building types, resulting in reduced cooling energy loads. This study seeks to understand the extent to which cool roof coatings could be used as a residential demand side management (DSM) strategy for retrofitting existing housing in a constrained network area in tropical Australia where peak electrical demand is heavily influenced by residential cooling loads. In particular this study seeks to determine whether simulation software used for building regulation purposes can provide networks with the ‘impact certainty’ required by their DSM principles. The building simulation method is supported by a field experiment. Both numerical and experimental data confirm reductions in total consumption (kWh) and energy demand (kW). The nature of the regulated simulation software, combined with the diverse nature of residential buildings and their patterns of occupancy, however, mean that simulated results cannot be extrapolated to quantify benefits to a broader distribution network. The study suggests that building data gained from regulatory simulations could be a useful guide for potential impacts of widespread application of cool roof coatings in this region. The practical realization of these positive impacts, however, would require changes to the current business model for the evaluation of DSM strategies. The study provides seven key recommendations that encourage distribution networks to think beyond their infrastructure boundaries, recognising that the broader energy system also includes buildings, appliances and people.

Decision support requirements for intelligent operation of southern grid in India

Control centers (CC) play a very important role in power system operation. An overall view of the system with information about all existing resources and needs is implemented through SCADA (Supervisory control and data acquisition system) and an EMS (energy management system). As advanced technologies have made their way into the utility environment, the operators are flooded with huge amount of data. The last decade has seen extensive applications of AI techniques, knowledge-based systems, Artificial Neural Networks in this area. This paper focuses on the need for development of an intelligent decision support system to assist the operator in making proper decisions. The requirements for realization of such a system are recognized for the effective operation and energy management of the southern grid in India The application of Petri nets leading to decision support system has been illustrated considering 24 bus system that is a part of southern grid.

Vehicle Routing Problem with Load Compatibility Constraints

The major contribution of this paper is to introduce load compatibility constraints in the mathematical model for the capacitated vehicle routing problem with pickup and deliveries. The employee transportation problem in the Indian call centers and transportation of hazardous materials provided the motivation for this variation. In this paper we develop a integer programming model for the vehicle routing problem with load compatibility constraints. Specifically two types of load compatability constraints are introduced, namely mutual exclusion and conditional exclusion. The model is demonstrated with an application from the employee transportation problem in the Indian call centers.

Modelling electricity demand with representative load curves

Models for electricity planning require inclusion of demand. Depending on the type of planning, the demand is usually represented as an annual demand for electricity (GWh), a peak demand (MW) or in the form of annual load-duration curves. The demand for electricity varies with the seasons, economic activities, etc. Existing schemes do not capture the dynamics of demand variations that are important for planning. For this purpose, we introduce the concept of representative load curves (RLCs). Advantages of RLCs are demonstrated in a case study for the state of Karnataka in India. Multiple discriminant analysis is used to cluster the 365 daily load curves for 1993-94 into nine RLCs. Further analyses of these RLCs help to identify important factors, namely, seasonal, industrial, agricultural, and residential (water heating and air-cooling) demand variations besides rationing by the utility. (C) 1999 Elsevier Science Ltd. All rights reserved.

Profile-Based Load Scheduling in Wireless Energy Harvesting Sensors for Data Rate Maximization

In this paper, power management algorithms for energy harvesting sensors (EHS) that operate purely based on energy harvested from the environment are proposed. To maintain energy neutrality, EHS nodes schedule their utilization of the harvested power so as to save/draw energy into/from an inefficient battery during peak/low energy harvesting periods, respectively. Under this constraint, one of the key system design goals is to transmit as much data as possible given the energy harvesting profile. For implementational simplicity, it is assumed that the EHS transmits at a constant data rate with power control, when the channel is sufficiently good. By converting the data rate maximization problem into a convex optimization problem, the optimal load scheduling (power management) algorithm that maximizes the average data rate subject to energy neutrality is derived. Also, the energy storage requirements on the battery for implementing the proposed algorithm are calculated. Further, robust schemes that account for the insufficiency of battery storage capacity, or errors in the prediction of the harvested power are proposed. The superior performance of the proposed algorithms over conventional scheduling schemes are demonstrated through computations using numerical data from solar energy harvesting databases.

A dynamic topology management in a hybrid wireless superstore network

with the development of large scale wireless networks, there has been short comings and limitations in traditional network topology management systems. In this paper, an adaptive algorithm is proposed to maintain topology of hybrid wireless superstore network by considering the transactions and individual network load. The adaptations include to choose the best network connection for the response, and to perform network Connection switching when network situation changes. At the same time, in terms of the design for topology management systems, aiming at intelligence, real-time, the study makes a step-by-step argument and research on the overall topology management scheme. Architecture for the adaptive topology management of hybrid wireless networking resources is available to user’s mobile device. Simulation results describes that the new scheme has outperformed the original topology management and it is simpler than the original rate borrowing scheme.

Fiber Bragg Grating Sensor Instrumentation for Parking Space Occupancy Management

This work aims at providing an effective parking management system by reducing the drivers' searching time for vacant car-parking space, in turn improving the traffic flow in the car park areas. This is achieved by the use of Fiber Bragg Grating Sensor (FBG) sensor instrumentation in vehicle parking management system. Present work involves embedding an array of FBG sensors underground in the parking space, then determining the strain changes on the FBG sensor due to load applied by the vehicle parked in the parking space, occupancy of the parking space is determined. To validate the FBG sensor parking management system, three most common cases have been considered. This closed loop FBG parking management system can give real-time feed-back to space-guidance display board helping the driver in maneuvering the vehicle to the appropriate parking space. The proposed technique offers optimized usage of parking space for the various segments of cars and also facilitates in a conjoined automated billing system, as compared to conventional method of parking systems.

Emergent synchronisation properties of a refrigerator demand side management system

In order to analyse the possibilities of improving grid stability on island systems by local demand response mechanisms,a multi-agent simulation model is presented. To support the primary reserve, an under-frequency load shedding (UFLS)using refrigerator loads is modelled. The model represents the system at multiple scales, by recreating each refrigerator individually, and coupling the whole population of refrigerators to a model which simulates the frequency response of the energy system, allowing for cross-scale interactions. Using a simple UFLS strategy, emergent phenomena appear in the simulation. Synchronisation e ects among the individual loads were discovered, which can have strong, undesirable impacts on the system such as oscillations of loads and frequency. The phase transition from a stable to an oscillating system is discussed.

Coastal management measures for the lower Maumee Watershed, Lake Erie

In January 2006 the Maumee Remedial Action Plan (RAP) Committee submitted a State II Watershed Restoration Plan for the Maumee River Great Lakes Area of Concern (AOC) area located in NW Ohio to the State of Ohio for review and endorsement (MRAC, 2006). The plan was created in order to fulfill the requirements, needs and/or use of five water quality programs including: Ohio Department of Natural Resources (DNR) Watershed Coordinator Program; Ohio EPA Great Lakes RAP Program; Ohio DNR Coastal Non-point Source Pollution Control Program; Ohio EPA Total Maximum Daily Load Program; and US Fish & Wildlife Service Natural Resources Damage Program. The plan is intended to serve as a comprehensive regional management approach for all jurisdictions, agencies, organizations, and individuals who are working to restore the watershed, waterways and associated coastal zone. The plan includes: background information and mapping regarding hydrology, geology, ecoregions, and land use, and identifies key causes and sources for water quality concerns within the six 11-digit hydrological units (HUCs), and one large river unit that comprise the Maumee AOC. Tables were also prepared that contains detailed project lists for each major watershed and was organized to facilitate the prioritization of research and planning efforts. Also key to the plan and project tables is a reference to the Ohio DNR Coastal Management Measures that may benefit from the implementation of an identified project. This paper will examine the development of the measures and their importance for coastal management and watershed planning in the Maumee AOC. (PDF contains 4 pages)

Watershed monitoring and the TMDL modeling to assess bacterial loading in estuarine environments to improve management

Shellfish bed closures along the North Carolina coast have increased over the years seemingly concurrent with increases in population (Mallin 2000). More and faster flowing storm water has come to mean more bacteria, and fecal indicator bacterial (FIB) standards for shellfish harvesting are often exceeded when no source of contamination is readily apparent (Kator and Rhodes, 1994). Could management reduce bacterial loads if the source of the bacteria where known? Several potentially useful methods for differentiating human versus animal pollution sources have emerged including Ribotyping and Multiple Antibiotic Resistance (MAR) (US EPA, 2005). Total Maximum Daily Load (TMDL) studies on bacterial sources have been conducted for streams in NC mountain and Piedmont areas (U.S. EPA, 1991 and 2005) and are likely to be mandated for coastal waters. TMDL analysis estimates allowable pollutant loads and allocates them to known sources so management actions may be taken to restore water to its intended uses (U.S. EPA, 1991 and 2005). This project sought first to quantify and compare fecal contamination levels for three different types of land use on the coast, and second, to apply MAR and ribotyping techniques and assess their effectiveness for indentifying bacterial sources. Third, results from these studies would be applied to one watershed to develop a case study coastal TMDL. All three watershed study areas are within Carteret County, North Carolina. Jumping Run Creek and Pettiford Creek are within the White Oak River Basin management unit whereas the South River falls within the Neuse River Basin. Jumping Run Creek watershed encompasses approximately 320 ha. Its watershed was a dense, coastal pocosin on sandy, relic dune ridges, but current land uses are primarily medium density residential. Pettiford Creek is in the Croatan National Forest, is 1133 ha. and is basically undeveloped. The third study area is on Open Grounds Farm in the South River watershed. Half of the 630 ha. watershed is under cultivation with most under active water control (flashboard risers). The remaining portion is forested silviculture.(PDF contains 4 pages)