Bird mortality as a result of collisions with power lines has been of increasing concern in recent decades, but the real impact on bird populations requires an experimental assessment of scavenger removal rates and searcher detection errors. Farmland and steppe birds, two of the most threatened avian groups, have been shown to be particularly vulnerable to collision with power lines, but few removal and detectability studies have been developed in cereal farmland habitats, and none in the Mediterranean region. We conducted five carcass disappearance trials in central Spain by placing 522 corpses of different sizes under power lines, and searching for remains four times during the following month. The influence of several factors was examined using multivariate approach. The accumulated number of carcasses removed by scavengers increased logarithmically, with 32% removed over the 2-day period after the initial placement, but only 1.5% removed on a daily basis by day 28. Small birds disappeared earlier and at a higher proportion than larger birds. Carcass removal rates were site-dependent, but were not influenced by carcass density or season. The detection rate increased with the observer's previous experience and carcass size. Carcass counts at power lines notably underestimate bird casualties. Our 4-week disappearance equations provide a full range of scavenging rates and observer efficiency correction factors for a wide range of bird weights. Fortnightly to monthly search frequencies may be adequate to detect medium-to large-sized corpses, but are insufficient for smaller birds. Finally, all personnel participating in carcass searches should be trained previously in this task.

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Nowadays, problems facing Distribution System Operators (DSOs) due to demand increase and the wide penetration of renewable energy are usually solved by means of grid reinforcement. However, the smart grid paradigm enables the deployment of demand flexibility for congestion management in distribution grids. This could substitute, or at least postpone, these needed investments. A key role in this scheme is the aggregator, who can act as a "flexibility provider" collecting the available flexibility from the consumers. Under this paradigm, this paper proposes a flexibility market led by the DSO and aimed at solving distribution grid congestions. The proposal also includes a flexibility market clearing algorithm, which is easy to implement, has low computational requirements and considers the energy rebound effect. The proposed design has the advantage of excluding the DSO's need for trading in energy markets. Also, the solution algorithm proposed is fully compatible with already existing grid analysis tools. The proposed electricity market is tested with two case studies from a real Spanish distribution network, where the proposed clearing algorithm is used, and finally, results are presented and discussed.

Congestion management is one of the core enablers of smart distribution systems where distributed energy resources are utilised in network control to enable cost-effective network interconnection of distributed generation (DG) and better utilisation of network assets. The primary aim of congestion management is to prevent voltage violations and network overloading. Congestion management algorithms can also be used to optimise the network state. This study proposes a hierarchical and distributed congestion management concept for future distribution networks having large-scale DG and other controllable resources in MV and LV networks. The control concept aims at operating the network at minimum costs while retaining an acceptable network state. The hierarchy consists of three levels: primary controllers operate based on local measurements, secondary control optimises the set points of the primary controllers in real-time and tertiary control utilises load and production forecasts as its inputs and realises network reconfiguration algorithm and connection to the market. Primary controllers are located at the connection point of the controllable resource, secondary controllers at primary and secondary substations and tertiary control at the control centre. Hence, the control is spatially distributed and operates in different time frames.

Abstract:The role of the distribution system operator (DSO) is evolving with the increasing possibilities of demand management and flexibility. Rather than implementing conventional approaches to mitigate network congestions, such as upgrading existing assets, demand flexibility services have been gaining much attention lately as a solution to defer the need for network reinforcements. In this paper, a framework for a decentralized local market that enables flexibility services trading at the distribution level is introduced. This market operates on two timeframes, day-ahead and real-time and it allows the DSO to procure flexibility services which can help in its congestion management process. The contribution of this work lies in considering the uncertainty of demand during the day-ahead period. As a result, we introduce a probabilistic process that supports the DSO in assessing the true need of obtaining flexibility services based on the probability of congestion occurrence in the following day of operation. Besides being able to procure firm flexibility for high probable congestions, a new option is introduced, called the right-to-use option, which enables the DSO to reserve a specific amount of flexibility, to be called upon later if necessary, for congestions that have medium probabilities of taking place. In addition, a real-time market for flexibility trading is presented, which allows the DSO to procure flexibility services for unforeseen congestions with short notice. Also, the effect of the penetration level of flexibility on the DSO's total cost is discussed and assessed. Finally, a case study is carried out for a real distribution network feeder in Spain to illustrate the impact of the proposed flexibility framework on the DSO's congestion management process.