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While the impact of an individual, residential, and small commercial sized Distributed Generation (DG) might be insignificant for many distribution cooperatives, in aggregate they can begin to create unforeseen issues with the distribution system. Planning tools were needed to determine the amount of small interconnected DER allowable on the system without requiring system improvements.

In the future, the base stations are expected to be deployed with higher density. To save cost and man forces, wireless links operating at 300 GHz can replace conventional cable-based backhaul connections. One of the goal of Horizon 2020 EU-Japan project ThoR is to design automatic planning tools for 300 GHz wireless backhaul network. To accomplish this task, a novel planning tool has been developed to plan backhaul links with the usage of a ring topology. To evaluate the proposed tool’s functionality, system-level simulations are conducted with an in-house developed mobile network simulator. In this paper, the algorithm of the new planning tool for 300 GHz wireless backhaul network is introduced and the SINR characteristics of the planned THz links are evaluated using 3D ray optical path loss predictions. For that, a realistic scenario of an ultra-dense cellular network in Hanover, Germany, is used with the diverse tropospheric climate conditions., 2021 15th European Conference on Antennas and Propagation (EuCAP)

The successful operation of spacecraft requires careful planning. Each mission comes with a unique set of challenges that must be met by tools and techniques developed on a mission-specific basis. In the past, these tools have been created as Command Line Interfaces (CLIs), Remote Command Line Interfaces (Remote CLIs), or Graphical User Interfaces (GUIs). This paper presents a method for the development of these custom tools implemented for the mission planning of the CYGNSS (Cyclone Global Navigation Space System) mission: using the Django web framework to act as a remote Graphical User Interface. CYGNSS, the NASA Earth Venture Class mission which launched in late 2016, is a constellation of eight microsatellites in low Earth orbit which perform ocean wind speed measurements using reflected GPS signals to aid in weather modeling. Several tools have been developed to aid in the extensive and ongoing workload in mission planning. Now operating in the extended mission phase, the CYGNSS team is small. However, each team-member works on several projects aside from CYGNSS and performs the necessary mission planning and operations from their individual computer. Since, when using traditional tools, each operator's computer generally has a different combination of hardware, software, and operating system, developers are often required to perform custom installation and debugging for each new user of the system. This results in a system which is prone to user-specific bugs, and is not suitable for the low-cost environment in which CYGNSS operates. We present a method which alleviates these problems. We use Django, a Python-based website framework, to host a suite of mission planning tools on a local website. This framework is split into three components: the Object Relational Mapping (ORM), the Template, and the View. The Django ORM is used to access the backend database from Python. Django Templates are used to control how the tool is displayed to the end user. Django Views tie the previous two components together by taking a request from the user, retrieving data from the database, rendering a template using that data, and returning the rendered template to the user where it is displayed by a web browser. We show how each of these components is used and the benefits of using such a web based system over a traditional tool.

Factory planning is an important tool for manufacturing companies to raise their efficiency and to maintain their competitiveness by changing market or customer requirements. A special challenge is the acquisition of layout data and the processing of this data in suitable planning tools. Current approaches still measure manually or have to transfer acquired data from laser scanners by hand into planning tools, which leads to a high effort and error proneness.This paper presents a holistic concept for automated and systematic data acquisition and processing for factory planning processes.

Hiring/recruitment is key to an organization’s ability to position itself for success by attracting the right talent. Similarly, job search enables workers to connect to the right jobs in the right organizations. To assist in the hiring and job search processes, many technology solutions such as interest inventories, job recommendation models, job boards, and career pathway planning tools have been developed. However, solutions for preparing job postings are lacking. Job postings/ads play an essential role in hiring the right talent since they signal to the jobseeker the knowledge, skills, abilities, and other occupation-related characteristics (KSAOs) needed for a job. If the job ad does not convey the correct occupational characteristics, it is less likely that a well-qualified candidate will apply. Therefore, we present an interactive job ad visualization tool that analyzes the text in a job ad and matches phrases in it to a large occupational taxonomy of KSAOs. We combine O*NET, an occupational taxonomy, with natural language processing to perform semantic similarity matching between KSAOs for an occupation and ad text, and thereby assist jobseekers in their search process and recruiters in preparing job ads.

The placement of access point locations is now a necessity in planning computer networks in particular wireless networks. In the study of wireless networks, at present, the design and adjustment approach has replaced the experience-based approach. In some wireless network planning tools the location map is only used for visualization only, so it needs to be developed for the calculation of location optimization as well. The use of spatial data has already been applied in location optimization. Application of optimization techniques in network planning will reduce costs and time compared to trial and error techniques. Spatial location data still uses two-dimensional data, namely latitude and longitude data. However, spatial location data in three dimensions have not been widely used in this optimization method. This research implements three-dimensional spatial data in the location optimization method. In this case, the spatial analysis of GIS (Geographic Information Systems) will be useful for predicting coverage and signal strength. Integrating spatial data analysis and programming techniques can lead to improvements in wireless network design. The use of evolutionary algorithms will provide solutions for optimal access point locations. This approach provides the right solution in design and evaluation. The results of the optimization of 3-dimensional maps provide better design values compared to 2-dimensional optimization. This can be seen from the reduction in the number of access points and the average distance, although this also results in a reduction in the area of coverage.

In the paper we briefly discuss principles for designing multi-team collaboration, specifically coordination, which include man and machine components, focusing on interdependence and emergent dynamics of work flow. To shed light on these design principles and discuss it in an empirical context we use a case from military information processing, specifically a NATO Exercise where multiple teams collaborated to do tasking, collection, processing, exploitation and dissemination (TCPED) in support of Joint intelligence, surveillance and reconnaissance (JISR). The case indicated that the interdependencies became increasingly complex over time, but there was not planning tools in place to support the management of the multi-team coordination. Implications for further conceptual and design work is suggested, such as developing further the consideration of soft and hard interdependencies, going from an inward look to consider the influence of the external environment and the role of trust, and development of task assignment tools.

The efficient development of modern distribution system requires the deployment of flexibility services provided by Distributed Energy Resources, like distributed generation, electric energy storage and demand response. This kind of planning tools have to be risk-based, in order to deal with the high level of uncertainties introduced by these new technologies. Suitable models and methodologies for the consideration of the value at risk associated to each choice are essential to compare innovative and conventional planning solutions. In the paper, Demand Response has been modelled with its possible payback effect and the optimal exploitation of this flexibility service with a predefined confidence (residual risk) has been estimated by means of a Robust Linear Programming optimization. The effectiveness of the proposed methodology is demonstrated on a simple distribution network.

This paper describes the field trials carried out in the Bucharest region in Romania for testing and analyzing the performance of the second generation of the Digital Video Broadcasting Terrestrial standard using the base profile for portable indoor reception. Test results are presented for the terrestrial broadcasted public programs of the Romanian National Television. The results consist of the values of the Carrier to Noise ratio, Modulation Error Rate and Link Margin in different geographical locations and receiving conditions. These values can update those provided by previous studies and provide planning tools for the Digital Terrestrial Television implementation using the second generation of the Digital Video Broadcasting Terrestrial standard. The results proved that the portable indoor reception in the Bucharest region for the Romanian National Television programs is possible, and this may be used to improve the end user experience with an additional television service to the existing cable or satellite television, since the digital terrestrial television has the advantage of mobility reception.

New challenges in power system planning, such as integration of massive amount of Renewable Energy Resources (RES), global decarbonization and efficiency targets, must be addressed by the Transmission System Operator (TSO) to guarantee optimal management, reliability and power grid flexibility. In this context, High Voltage Direct Current (HVDC) may play a key role, providing additional benefits compared to HVAC transmission line. Therefore, a valid and detailed model of different HVDC technologies and configurations is needed for grid planning and middle-long term studies. The aim of this paper is reporting the Italian experience in HVDC transmission system models for steady state studies, with special reference to LCC or CSC (line-commutated converter or current-source converter) and VSC (voltage-source converter) HVDC, analyzing their impact in load-flow solution techniques. The HVDC implementation in Common Grid Model Exchange Data (CGMES), the data exchange standard defined in ENTSO-E framework, used to improve Pan-European grid modelling and information exchange among TSOs for TYNDP studies are also presented.

While NATO nations have long enjoyed relative security from air attack at military installations, recent developments in missile technology and doctrine have threatened that security. With 26 conflicts worldwide in the past 100 years featuring airbase attacks, doctrine and planning tools must be updated to allow continued use of air bases within missile range of enemy forces. Research conducted for the United States Air Force identifies the areas of base resilience and how they affect mission capability. Several models have been developed based on these principles, but there are gaps in model capability and usefulness for allied partners. This paper presents the proposal of a novel base planning model capable of directly quantifying missile attack consequences and generating optimal site layout plans and protection strategies. This model would be implemented using multi-objective genetic algorithms to identify solutions that provide optimal tradeoffs between the competing objectives of minimizing attack consequences, minimizing site construction costs, and minimizing mission impact. These capabilities are expected to assist military engineers in their critical task of analyzing and selecting the design strategy that minimizes operational impacts to a base located in a contested region.

Microgrids have been considered an essential component for improving the efficiency, resilience and reliability of the evolving electric power grid. Their modularity adds to the operational flexibility of the system in addition to provision for multi-player energy markets and transactive energy framework. The value of microgrid based systems is evident from their growing implementations globally. This underscores the need for developing a skilled workforce at the confluence of power systems and power electronics. Based on this, a special course in virtual power plants and virtual inertia was introduced at Clemson for exploratory pedagogy and building foundations for scientific scholarship in this area. This paper introduces the objectives, major challenges, design, planning and modeling tools, project outcomes and lessons learned from the instructor's experience with this hybrid course.

United Illuminating (UI) implemented the Operational Excellence Initiative (OEI) to meet a regulatory commitment to provide transparency and better communications to customers, including accurate Estimated Restoration Times (ERTs) during daily operations and within 48 hours of the completion of a major storm. This transformational project includes the integration of an Outage Management (OMS), Geographic Information System (GIS) and Mobile Work Management System (MWMS), configuration of a GIS-based Damage Assessment Tool (DAT), and the custom development of Storm Planning Tools. This robust digital solution enables the collection of damage data in the field and back office analysis of this data to generate a detailed work order with an accurate ERT. Additionally, this solution enables two-way communications between UI and their customers. Customers receive proactive communications, report outages, and request on-demand status via web, Short Message Service (SMS), and Integrated Voice Response (IVR), thus reducing the call volume to the call center.

The approach to planning, design and operation of distribution networks have significantly changed due to the proliferation of distributed energy resources (DERs) together with load growth, energy storage technology advancements and increased consumer expectations. Planning of active distribution systems (ADS) has been a very hot topic in the 21st Century. A large number of studies have been done on ADS planning. This paper reviews the state of the art of current ADS planning. Firstly, the influences of DERs on the ADS planning are addressed. Secondly, the characteristics and objectives of ADS planning are summarized. Then, up to date planning model and some related research are highlighted in different areas such as forecasting load and distributed generation, mathematical model of ADS planning and solution algorithms. Finally, the paper explores some directions of future research on ADS planning including planning collaboratively with all elements combined in ADS, taking into account of joint planning in secondary system, coordinating goals among different layers, integrating detailed operation simulations and regular performance based reviews into planning, and developing advanced planning tools.

Wireless design is essential as it provides time and cost saving. Several WIFI planning tools are available on the market but most of them were initially designed to be user-friendly and provided limited configuration options making it hard to model site-specific environment factors. In this paper, we proposed a WIFI heatmap generator tool that allows users to predict wireless signal strength within the building. Our tool allows users to characterize wireless propagation model including pathloss exponent and pathloss attenuation factors which are usually caused by wall partitions, building layouts, etc. Network administrators and wireless users can deploy this tool to visualize heatmaps which represent wireless received signal strength in each location of the floor plan. Limited WIFI coverage area can be easily determined using this tool. This can be helpful during access point deployment and redeployment. A site-specific propagation model was proposed, and the accuracy of this model was discussed at the end of this paper.

Companion systems are technical systems that adjust their functionality to the needs and the situation of an individual user. Consequently, companion systems are strongly knowledge-based. We propose a modelling paradigm for integrating procedural and conceptual knowledge which is targeted at companion systems that require a combination of planning and reasoning capabilities. The presented methodology couples the hierarchical task network (HTN) planning formalism with an ontology-based knowledge representation, thereby minimising redundancies in modelling and enabling the use of state-of-the-art reasoning and planning tools on the shared knowledge model. The approach is applied within a prototype of a companion system that assists novice users in the do-it-yourself (DIY) domain with the planning and execution of home improvement projects involving the use of power tools.

Prophylactic interventions such as vaccine allocation are one of the most effective public health policy planning tools. The supply of vaccines is limited, and an importantproblem is when and how to allocate the available vaccination supply, referred to as the Vaccine Allocation Problem. The spread of epidemics is modeled by the SEIR process, which has a very complex dynamics, and depends on human contacts and mobility. This makes the design of efficient solutions tovaccine allocation problem to minimize the number of infections a very challenging problem. In particular, this requires good models for human mobility, and optimization tools for vaccine allocation.In this paper, we study the vaccine allocation problem in the context of seasonal Influenza spread inthe United States. We develop a novel national scale flu model that integrate both short andlong distance travel, which are known to be important determinants of the spread of Influenza. We also design a greedy algorithm for allocating the vaccine supply at a county level. Our results show significant improvement over the current baseline, whichinvolves allocating vaccines based on the state population.

To limit computational effort, current power system expansion planning tools typically consider limited detail on the technical constraints of power systems, such as the need for operating reserves. With growing balancing needs, this is likely to underestimate the technical barriers and integration cost of large shares of renewable generation. This contribution studies the impact of operating reserve requirements on generation capacity investments following the large-scale integration of intermittent renewable generation. Simulations show that operating reserves have a substantial impact on the generation capacity installed, and its operation, and result in a substantial increase of renewable integration costs. Furthermore, it is shown that the use of improved reserve strategies, such as dynamic reserve sizing, and the participation of renewables in the supply of downward reserves, is able to significantly reduce this cost increase.

This paper proposes a simulation platform developed to study and identify critical cases in a Smart Grid. A distribution network with different Distributed Energy Resources (DER) components, connected along the feeders, is analyzed, having the objective to identify limitations of existing simulation and planning tools, with a particular objective on the challenges faced by the introduction of Smart Grid technologies. Another important issue of the paper is to identify critical load cases, as well as the voltage variations with the highest potential, able to implement the grid model and the worst case scenarios developed.

Accurate estimation of RF signal spatial local mean is of crucial importance in wireless communication systems planning, design and operation, specifically in coverage planning tools, channel access and power control, handoff algorithms, etc. However, so far, no universally applicable and verified approach for calculation of relevant averaging parameters has been developed. In this paper, comprehensive overview of spatial averaging problem is presented, including available methods for solving it. With this regard, closed-form expressions for averaging parameters calculation are delivered based on the approaches that are considered most accurate. Finally, the validity domains of these expressions are tested, indicating their applicability areas under specific propagation conditions.

This paper shows how generic protection relay models available in planning tools can be augmented with settings that are based on NERC standards or best engineering practice. Selected generic relay models in Siemens PSS®E have been used in dynamic simulations in the proposed approach. Undervoltage, overvoltage, underfrequency, and overfrequency relays have been modeled for each generating unit. Distance-relay protection was modeled for transmission system protection. Two types of load-shedding schemes were modeled: underfrequency (frequency-responsive non-firm load shedding) and underfrequency and undervoltage firm load shedding. Several case studies are given to show the impact of protection devices on dynamic simulations. This is useful for simulating cascading outages.

Underwater autonomous gliders have transitioned from exotic experimental systems to becoming a standard platform capable of collecting data over a critical range of spatial and temporal scales in the ocean. The data are proving to be extremely valuable for addressing a wide range of basic and applied research questions. These communities are growing from distributed research and/or education groups. It is crucial as systems continue to evolve that there is an effort to “harmonize” data products while preserving the diversity of approaches/science/experimentation. As the gliders have matured and new battery solutions provide additional energy, there is an increased focus on the integration of a wider range of sensors to be incorporated into gliders. Many of these new classes of sensors will be particularly effective for characterizing biological processes in the coastal ocean. As biological sensors generally provide proxy estimates of a parameter, developing robust quality control and assurance procedures is critical. These new sensors will be more power intensive thus requiring the development of planning tools for increasing energy efficiency during missions. Given the significant growth in the highly distributed glider community, efforts are now focusing on the development mission planning tools to allow for efficient operation of glider fleets. To further collaboration and standardization of the growing number of glider operators we have initiated a series of community efforts called glider paloozas. We had an exceptional turnout last year, encompassing 18 U.S. and Canadian partners, 28 gliders, 36 glider deployments, and spatial coverage from coastal regions of Newfoundland to the Gulf of Mexico and offshore to Bermuda. The coordinated effort focused on several research themes including continental shelf circulation, fish migrations, and storm activity. The main goals of last year's effort were to produce a seamless flow of real-time glider data into the Global Telecommunications System (GTS) via DMAC and into the regional ocean models and demonstrate the potential of a U.S. national glider network. This is in line with the goal to increase glider data accessibility from Federal and Academic oceanographic modeling communities, the U.S. Integrated Ocean Observing System (IOOS), and other federal funding agencies (i.e., NSF). In order to demonstrate the value and necessity of the planned U.S. national glider network and build on last years successes, we hope to continue these efforts and require that all glider data produced by Gliderpalooza 2015 participants be uploaded by the individual operators to the DAC 2.0 and into GTS.

Dispersed generation sources are slowly penetrating into distribution power networks. Renewables represent the majority of newly installed energy sources, which are of stochastic nature. With this phenomenon, new technical challenges are rising up, where appropriate impact assessment of volatile dispersed generation on voltage quality stands for one of them. Current planning tools and optimization methods mostly rely on the deterministic key performance indicators (KPI), which assesses the power quality in a distribution network. These indicators may not be sufficient for power network with high presence of uncertainty. In this paper, power network model with emphasis on probabilistic description of power injections is described. Correlation among stochastic power injection is discussed and consequently this correlation is categorized into several groups. Main focus of the paper is on design of probabilistic key performance indicators for assessment of power quality in a distribution network. Two probabilistic load flow methods used for computation of introduced KPIs are presented and their performance is analyzed on selected test case. On the test case, KPIs evaluation is demonstrated and the results are analyzed.

In spite of the growing presence of wireless communications, some concerns have recently loomed about the potential risks of the exposure to the electromagnetic fields they induce. In this paper we introduce a methodology that would allow to study the performance of enhanced access selection mechanisms, which include the willingness to reduce such exposure. The proposed framework has been conceived with the main goal of complementing other types of analysis that, despite providing a much more accurate characterization of the physical parameters, do not offer the degree of flexibility that would be required to understand the performance of these novel resource management solutions.

The distribution grid is changing to become an active resource with complex modeling needs. The new active distribution grid will, within the next ten years, contain a complex mix of load, generation, storage and automated resources all operating with different objectives on different time scales from each other and requiring detailed analysis. Electrical analysis tools that are used to perform capacity and stability studies have been used for transmission system planning for many years. In these tools, the distribution grid was considered a load and its details and physical components were not modeled. The increase in measured data sources can be utilized for better modeling, but also control of distributed energy resources (DER). The utilization of these sources and advanced modeling tools will require data management, and knowledgeable users. Each of these measurement and modeling devices have accuracy constraints, which will ultimately define their future ability to be planned and controlled. This paper discusses the importance of measured data accuracy for inverter control, interconnection and planning tools and proposes ranges of control accuracy needed to satisfy all concerns based on the present grid infrastructure.

The continuous change in the manufacturing world is demanding more flexible, responsive and accurate planning tools, which are able to assist the decision-makers to take tactical and strategic decisions on short notice with a high level of confidence. For this purpose, these tools should dynamically explore different operative scenarios in the planning procedure and produce information about key performance indicators. This paper describes the development of an agentbased strategic planner, combining the flexibility of multi-agent systems principles with the optimization capability of a Mixed Integral Programming technique. The tool is integrated in an ecosystem of heterogeneous decision-making systems through an Enterprise Service Bus that also provides access to legacy data. info:eu-repo/semantics/publishedVersion

Continuous advances in network technologies challenge network architects in their attempt to foresee what new technologies deserve resources and investments, what existing infrastructure to keep, and their interplay during migration processes. Moreover, topics like energy efficiency, disaster resilience, or SDN/NFV are being intensively considered and investigated during the last years. As a result, R&D efforts have led to a number of solutions. Unfortunately, it is often difficult for operators to reproduce such results on their networks, maybe due to divergent philosophies between commercial planning tools used in the industry and academic tools. A paradigm shift to an open-source view of network planning could emphasize the power of peer-review and transparency to promote innovation at an accelerated pace and lower cost. This tutorial would focus on Net2Plan (http://www.net2plan.com), an open-source tool developed by the authors, and actively used in several courses (>200 students) and research projects since 2012. Built on top of a technology-agnostic multilayer network representation, Net2Plan is designed to assist users in the evaluation of built-in or original user-developed planning algorithms. In addition, users can analyze their designs using either reports or a simulation tool for in-operation scenarios like network resilience, connection-admission-control, time-varying traffic resource allocation, or even combinations of them. Besides, Net2Plan permits applying algorithms to orchestrate OpenFlow-enabled networks interacting with the northbound interface of OpenDaylight. Throughout the tutorial, attendees would have the opportunity to learn about the main features of Net2Plan, also discovering some of its applications. At the end of this tutorial, attendees would be guided through an intensive hands-on case study based on an IP-over-WDM network, e.g., including network dimensioning using built-in or user-developed algorithms, WDM line engineering (e.g., EDFA placement, impairment computations), automatic availability calculation under different failure patterns, and automatic simulation of the effects of time-varying traffic and assessment of energy-efficient switch-off techniques.

In this paper, a comparative study between the results of a measurement campaign conducted in northern Greece and simulations performed with Radio Mobile and ICS Telecom radio planning tools is performed. The DVB-T coverage of a transmitting station located near the city of Thessaloniki is estimated using three empirical propagation models (NTIA-ITS Longley Rice, ITU-R P.1546 and Okumura-Hata-Davidson) and one deterministic model (ITU-R 525/526). The best results in terms of minimum average error and standard deviation are obtained using the deterministic model and the NTIA-ITS Longley Rice empirical model. In order to improve the results, the tuning options available in the ICS Telecom software are used on the Okumura-Hata-Davidson model, leading to a significant increase in accuracy.

Multi-disciplinary technologies are currently involved in orthognathic and dental surgery. By using 3D and CT scans, the surgery can be planned beforehand by making use of 3D image processing, visualization and planning tools. With 3D printing, accurate splints and wafers can be generated for the surgery. Nowadays, these tools are on-premises software and this makes it very hard for collaboration between several specialists. Therefore, we researched the possibility to create an online cloud-based platform to run the currently used surgical planning tools. We achieved multiple two-factor authentication user logins, simultaneous surgical planning sessions and lightweight multi-platform support.

This paper focuses on the development of an interactive system dynamics simulation model of the strategic university planning framework. To develop the model, we integrated both the balanced scorecard method and the system dynamics modelling method. Contrasting the traditional university planning tools, the developed model addresses university management problems holistically and dynamically. By integrating the balanced scorecard and system dynamics modelling methods, this study was carried out in three phases. During the first phase, several interviews were conducted, and few documents content were analyzed to formulate the university balanced scorecard. The second phase involved the development of the university planning simulation model. In the third phase, the implications of various different strategies towards university performances were evaluated. Inclusive, a Microworld of the dynamic balanced scorecard for university planning (DBSC-UNI) is constructed to support decision makers in analysing the impact of various different policies towards university performances before real-world implementation. It is found that using system dynamics modelling method, the cause-and-effect relationships among variables related to the four conventional balanced scorecard perspectives are better understand. The dynamic processes that give rise to performance differences between targeted and actual performances also could be better understood. So, it is expected that the quality of the decisions taken are improved because of being better informed. The developed model can be exploited by university management to design policies that can positively influence the future in the direction of desired goals, and will have minimal side effects. This paper integrates balanced scorecard and system dynamics modelling methods in analyzing university performance. Therefore, this paper demonstrates the effectiveness and strength of system dynamics modelling method in solving problem in strategic planning area particularly in higher education sector.

Number of mobile technologies is rapidly growing, and their planning is becoming more and more complex. Therefore it is necessary to use high precision propagation models in planning tools which, together with the increasing precision of available GIS data, form a good basis for realistic and accurate propagation predictions.

Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut's state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.

This work proposes an empirical propagation model to obtain the path loss and therefore determine the average received power of a signal for a specific outdoor urban scenario with UAVs. The proposed 3D propagation model for terrestrial cellular networks generalizes the LUI model and is valid in the frequency ranges of GSM, UMTS and LTE technologies. We report experimental work in 3D space, considering the height, the antennas base station tilt, sectorziation, angle and distances profile The experimental work included in this study is in good agreement with the proposed theoretical model, corroborating the idea that this model is a good contribution for cellular planning tools. info:eu-repo/semantics/acceptedVersion

Distribution network operators require more advanced planning tools to deal with the challenges of future network planning. An appropriate planning and optimization tool can identify which option for network extension should be selected from available alternatives. However, many optimization approaches described in the literature are quite theoretical and do not yield results that are practically relevant and feasible. In this paper, a distribution network planning approach is proposed which meets requirements originating from network planning practice to guarantee realistic outcomes. This approach uses a state-of-the-art evolutionary algorithm: Gene-pool Optimal Mixing Evolutionary Algorithm. The performance of this algorithm, as well as the proposed model, is demonstrated using a real-world case study.

This paper presents a method for evaluating reliability when some error occurs in upstream grid and the microgrid is in island mode. Also, a connection matrix for the linkage between grid components as well as a load prioritization matrix for indicating loads priority along with effects of prioritization on reliability indices is recommended. In addition, a failure effect matrix for a feeder over loads of adjacent feeders is provided. Moreover, an algorithm is used to show how the failure effect matrix is obtained. In present paper, a 4-bus RBTS system with microgrids is studied, the reliability of which is analyzed in 3 modes: (i) No microgrids, (ii) with microgrid in island mode without load prioritization, and (iii) with microgrid in island mode with load prioritization; and failure effects on loads are also examined and, for these 3 modes, reliability indices are calculated, indicating that it is improved in the mode of load prioritization.

Coordinated Multi-Point (CoMP) detection and transmission promises great improvements in cellular network coverage and throughput. To make full advantage of CoMP, however, appropriate radio planning is required that considers decoding of UEs at clusters of multiple BSs. Therefore, planning tools need accurate models that capture multi-cell propagation characteristics. This paper presents the analysis of uplink joint detection CoMP using ray tracing (RT). The main contribution is a comparison of RT simulation results with those of transmission experiments obtained through field trials. For this purpose, the testbed was modeled in a RT simulator. Measured and simulated results were evaluated for conventional and joint detection.

State of the art planning tools rely on intricate simulation models and metaheuristic approaches to determine the optimal azimuth angle of each sector in a system. The process is highly time consuming and the quality of outcome is heavily dependent on the practitioner's experience in setting input parameters. To address this problem, in this paper we exploit a mathematical approach and develop a system model that ultimately helps to obtain a low complexity analytical solution. In addition to providing insights into system behaviour as function of azimuth angles, the potential performance gain of the proposed optimisation solution is investigated through extensive numerical results.

The Icelandic power system is based primarily on hydroelectric and geothermal generation. The system has large resources compared to the size of Iceland's economy. The main utilization practice for electrical energy hitherto has been bulk Energy Intensive Industry (EII) with relatively flat and constant load. A possible future interconnection to neighboring countries via High Voltage Direct Current (HVDC) submarine cable could affect dramatically the operations planning framework, for instance with possibilities of linking to wind power, local and/or foreign and short term markets. This should affect factors such as operation strategies for hydro system and the planning and operations tools needed to realize this rent. Planning tools and modeling for hydro dominated systems may in some respects inherently be more complex than those of thermally dominated systems, due to the time-interdependence associated with reservoir storage and various constraints [4]. In this paper we give an overview of historical and current modeling practices used both as a tool to form system expansion policies and operations strategies in the long, medium and short term. The basic time frame requirements for such tools are discussed in this paper and how the may evolve in the future in terms of methodology and other important issues. Conclusions will be drawn regarding these planning tools and the future planning and operations framework in such a system, especialy the time frame issue. The long and medium term hydro-scheduling problem has been investigated since in the early part of the 20th century [14], applying various optimization and iterative simulation methodologies. The practices applied in the Icelandic system have traditionally been based on Scandinavian approaches, such as those originally suggested by [9], [17] and [2]. These methods in hydro dominated systems have been based on an iterative calculation of water value tables based on iterative dynamic programming like algorithms. Future methodology may involve LP or SDDP [16], but with a short term considerations (DTM, see below) to certain extent as outlined in this paper.

Despite the radical changes that the electricity distribution system is currently facing and will have to face in the next decade, utilities still adopt a traditional approach for the expansion planning of their networks, based essentially on the fit and forget concept (only network reinforcements to cope with the worst case scenario). Although innovative solutions have been proposed in the last decade at the electricity distribution level (distributed energy storage, active management of distributed generation, demand side integration, etc.) and are becoming technically and economically feasible, they are not yet considered as viable planning alternatives. The reasons of this reluctance are the lack of ad hoc planning tools and business cases. In the paper, a novel planning tool for Active Distribution Networks is applied to a real MV distribution network of the A2A utility sited in the district of Brescia in order to prove the benefit of energy storage devices.

In general, the objective of electric transmission expansion planning (TEP) is to specify addition of transmission facilities that provide adequate capacity and in the mean time maintain operating performance of electric transmission system. To achieve effective plan, exact location, capacity, timing and type of new transmission equipment must be thoroughly determined to meet demand growth, generation addition and increased power flow. However, cost-effective transmission expansion planning becomes one of the major challenges in power system optimisation due to the nature of the problem that is complex, large-scale, difficult and nonlinear. Meanwhile, mixed integer nature of TEP results in an exponentially increased number of possible solutions when system size is enlarged. This research paper deals with various planning tools for TEP based on solution methods, the treatment of the planning horizon, and the consideration of the new competitive schemes in the power sector.

This paper introduces NATO's next generation satcom management and control (M&C) capability, intended to support the new deployable assets of the growing and constantly evolving NATO ground segment. The Advanced Satcom Network Management and Control system (ASNMC) introduces a new paradigm for implementing centralized and highly resilient M&C services for military satellite communications. ASNMC brings in assured communications over a dedicated M&C network overlay, spanning over control centres, static anchor stations, multiple satellite payloads, and deployable terminals. It takes a holistic approach, leading to any NATO resource operating at military X-band frequencies to fall under ASNMC control, and paving the way to control other frequency bands and deployable satcom assets, in the near future. ASNMC introduces the notion of assured engineering orderwires (EOW), relying on bearer and geographical diversity, to maximize the availability of critical M&C processes, even when the terminals operate in hostile RF environments. On top of that, ASNMC integrates classical satcom management and control capabilities, like link power control (LPC) and spectrum monitoring services (SMS), together with centralized mission planning tools, enabling the fast roll-out of large satcom networks, involving heterogeneous links (protected and nonprotected) and ground terminals.

The requirements of a network equivalent to be used in new planning tools are very different from those used in traditional equivalencing procedures. For example, in the classical Ward equivalent, each generator in the external system is broken up into fractions. For newer long-term investment applications that take into account such things as greenhouse gas (GHG) regulations and generator availability, it is computationally impractical to model fractions of generators located at many buses. To overcome this limitation, a modified- Ward equivalencing scheme is proposed in this paper. The proposed scheme is applied to the entire Eastern Interconnection (EI) to obtain several backbone equivalents and these equivalents are tested for accuracy under a range of operating conditions. In a companion paper, the application of an equivalent developed by this procedure is used to perform optimal generation investment planning.

Solar PV interconnection analyses have historically been addressed by analyzing one or two PV system interconnection requests at a time. As higher penetration levels and numbers of PV systems are realized, the ability to efficiently model and analyze large numbers of PV system deployments and scenarios becomes increasingly important yet difficult. Time and spatial impacts along with uncertainty in the rate of PV adoption must also be considered. Advanced distribution analysis tools are necessary to take into account such factors, and also allow for the quick screening of interconnection requests. This paper discusses some of these issues along with the examples illustrated using an open source distribution analysis program.

This panel session paper outlines one of the research thrust areas in the Power System Engineering Research Center's (PSERC) new initiative funded by the US Department of Energy (DOE) to investigate requirements for a systematic transformation of today's electric grid to enable high penetrations of sustainable energy systems. The proposed research under this thrust area aims at understanding and quantifying the impact that massive integration of wind power will have on the power system in terms of efficiency, operational reliability, economic consequences and environmental outcomes. It also focuses on the design and evaluation of technological and market based approaches to mitigation the adverse impact of such integration. The analysis will be based simulation models designed to explore and evaluate technological and market solutions that can facilitate the integration of renewable resources. Specifically, the potential of harnessing the inherent flexibility of certain load types such as heating and cooling and PHEV charging and the deployment of distributed and system level storage devices to mitigate the variability and uncertainty of renewable resources will be explored and evaluated.

Computational methods and information systems have been at the center of secure and economic planning and operation of electric power systems for several decades. Today, transformational forces such as renewable energy, distributed resources, energy storage, massive sensing, etc., pose numerous and much more difficult computational challenges. The addition of sustainability objectives to the traditional goals of grid economy and reliability has resulted in growing uncertainty and complexity, and is likely to rend a significant portion of the current computational methods and information systems obsolete. The new decision-making tools needed in operations and planning must be based on computational methods that account for uncertain conditions and are capable of handling much more complex problems. On the other hand, the availability of massive, more detailed, and new data from PMU, AMI, and IED's provides great opportunities for improved grid planning and operations, but ways must be found to aggregate, organize, and keep this data secure so that it can be leveraged to upgrade, extend, and replace existing tool.

This paper presents verifications for UMTS coverage and capacity in a live network using planning and performance tools applied to a real-world operational UMTS network. Case study results are presented and followed by comparisons between coverage predictions, capacity simulations, field measurements and system statistics. Tuned propagation models based on area clutter, population profiles, digital height maps and base station (BS) engineering elements are taken into account to match the outputs of the planning tool to the practical drive-test and UMTS Terrestrial Radio Access Network (UTRAN) system Key Performance Indicators (KPIs) measurements. This work outcome addresses the importance of using planning tools for dimensioning coverage and capacity aspects in UMTS networks and draw some attention to network future optimization, load balancing and congestions relief in advance before system traffic statistics are being generated or afterwards as supplementary grounds for network optimization and maintenance that support statistics.

Effective planning of the complex electricity supply network is essential because of the long lead times required for the development and placing in service of large new generators and transmission lines. Yet much can change while this physical process is being undertaken in terms of costs, prices, technological innovation and public policies, particularly about the environment and fuel diversity. The essential nature of well-constructed markets in yielding accurate, up-dated information about the likely effects of these many factors, as well as the use of advanced planning tools like "real-options" analysis are described, together with how these tools should be carefully staged and integrated with the planning process.

Ramp metering is known as a technique of Intelligent Transportation Systems (ITS), which can improve freeway throughput and reduce the incidents with low implementation cost. However, its benefit of application is only effective in certain conditions. It is important to accurately analyze the benefit-cost ratio before the decision making of implementing it. Sketch planning tools provides a measure to conduct benefit-cost analysis based on the impact of ramp metering, such as throughput increase and safety improvement. The default impacts used in software are reported in previous studies and expected to be functions of the conditions under investigation and may not be transferable between transportation systems. This study proposes a method to estimate the impacts of ramp metering for variable freeway traffic conditions through modeling the reduction of traffic breakdown due to ramp metering. The results show that this procedure allows flexible benefit-cost analysis for various traffic conditions.

This paper presents the of state of art about methodologies for Strategic Environmental Assessment (SEA) process applied to long-term planning of the electricity transmission, particularly in regard to the existence of gains for the sustainability of the developed proposals. It also shows the origin, concepts and development of SEA, its applications and impact. The analysis to the international experience in implementing the SEA illustrates its potential role for planning tools developments in this sector. The information is supported on a bibliographic research, case application and lessons learned by companies' experiences in the electricity sector, is summarized in this work. This work highlights the SEA Development Plan and Investment of Transmission (2009–2014), carried out by the transmission concessionaire Portuguese Rede Electrica Nacional (REN), currently being considered by the General Directorate for Energy and Geology.

Service robotics is expected to be established in human households and environments within the next decades. Therefore, dexterous and flexible behavior of these systems as well as guaranteeing safe interaction are crucial for that progress. We address these issues in terms of control strategies for the whole body of DLR's humanoid Justin. Via impedance control laws, we enable the robot to realize main tasks compliantly while, at the same time, taking care of aspects like physical limitations and collision avoidance with its own structure and the environment autonomously. The controller provides a natural redundancy resolution between the arms, the torso and the wheeled platform. A low-dimensional task space interface is proposed that can be used by planning tools. Thereby, planning time can be saved significantly. Experimental results on DLR's Justin are presented to validate our approach.