Reactive power control in photovoltaic systems through (explainable) artificial intelligence

Across the world, efforts to support the energy transition and halt climate change have resulted in significant growth of the number of renewable distributed generators (DGs) installed over the last decade, among which photovoltaic (PV) systems are the fastest growing technology. However, high PV penetration in the electricity grid is known to lead to numerous operational problems such as voltage fluctuations and line congestions, which could be eased by utilizing the reactive power capability of PV systems. To this end, we propose to use artificial neural network (ANN) to predict optimal reactive power dispatch in PV systems by learning approximate input–output mappings from AC optimal power flow (ACOPF) solutions in either a centralized or a decentralized manner. In the case of decentralized control, we leverage Shapley Additive Explanations (SHAP), an explainable artificial intelligence (XAI) technique, to identify non-local grid state measurements which significantly influence the optimal dispatch of each individual system. Both centralized and decentralized ANN-based controllers are evaluated through a case study based on the CIGRE medium-voltage distribution grid and compared to baseline control strategies. Results show that both ANN-based controllers exhibit superior performance, hindering voltage problems and line congestions which are encountered with baseline strategies while recording an energy saving of 0.44% compared to fixed power factor control. By leveraging ANN and SHAP, the proposed decentralized controllers for reactive power control are able to achieve ACOPF-level performance while promoting data privacy and reducing computational burden

IMPACT OF DATA COLLECTION ON ML MODELS: ANALYZING DIFFERENCES OF BIASES BETWEEN LOW- VS. HIGH-SKILLED ANNOTATORS

Labeled data is crucial for the success of machine learning-based artificial intelligence. However, companies often face a choice between collecting few annotations from high- or low-skilled annotators, possibly exhibiting different biases. This study investigates differences in biases between datasets labeled by said annotator groups and their impact on machine learning models. Therefore, we created high- and low-skilled annotated datasets measured the contained biases through entropy and trained different machine learning models to examine bias inheritance effects. Our findings on text sentiment annotations show both groups exhibit a considerable amount of bias in their annotations, although there is a significant difference regarding the error types commonly encountered. Models trained on biased annotations produce significantly different predictions, indicating bias propagation and tend to make more extreme errors than humans. As partial mitigation, we propose and show the efficiency of a hybrid approach where data is labeled by low-skilled and high-skilled workers

Explainable artificial intelligence for photovoltaic fault detection: A comparison of instruments

Faults in photovoltaic arrays are known to cause severe energy losses. Data-driven models based on machine learning have been developed to automatically detect and diagnose such faults. A majority of the models proposed in the literature are based on artificial neural networks, which unfortunately represent black-boxes, hindering user interpretation of the models’ results. Since the energy sector is a critical infrastructure, the security of energy supply could be threatened by the deployment of such models. This study implements explainable artificial intelligence (XAI) techniques to extract explanations from a multi-layer perceptron (MLP) model for photovoltaic fault detection, with the aim of shedding some light on the behavior of XAI techniques in this context. Three techniques were implemented: Shapley Additive Explanations (SHAP), Anchors and Diverse Counterfactual Explanations (DiCE), each representing a distinct class of local explainability techniques used to explain predictions. For a model with 99.11% accuracy, results show that SHAP explanations are largely in line with domain knowledge, demonstrating their usefulness to generate valuable insights on model behavior which could potentially increase user trust in the model. Compared to Anchors and DiCE, SHAP demonstrated a higher degree of stability and consistency

Absolute clock synchronization with a single time-correlated photon pair source over 10km

We demonstrate a point-to-point clock synchronization protocol based on bidirectionally propagating photons generated in a single spontaneous parametric down-conversion (SPDC) source. Tight timing correlations between photon pairs are used to determine the single and round-trip times measured by two separate clocks, providing sufficient information for distance-independent absolute synchronization secure against symmetric delay attacks. We show that the coincidence signature useful for determining the round-trip time of a synchronization channel, established using a 10\,km telecommunications fiber, can be derived from photons reflected off the end face of the fiber without additional optics. Our technique allows the synchronization of multiple clocks with a single reference clock co-located with the source, without requiring additional pair sources, in a client-server configuration suitable for synchronizing a network of clocks.Comment: 5 pages, 6 figures. arXiv admin note: text overlap with arXiv:1812.0845

Pengaruh Variasi Media Cetakan Pasir, Cetakan Logam dan Pasir RCS (Resin Coated Sand ) Terhadap Hasil Coran Produk Tap Handle dari Bahan Perunggu (Bronze)

The use of printed material in the cast product has the nature and character of its own. These properties greatly affect the quality of the cast product. The purpose of this study was to determine the effect of variations in the mold of the quality of the cast, cast defects and hardness. This study uses aluminum scrap, which is melted in the kitchen krusible, a variation of the mold used three types: wet sand molds, metal molds and mold RCS (Resin Coated Sand). To determine the shrinkage defects comparing dimensional objects with the original specimen results of each specimen, Porosity can be seen by looking for true density values calculated by referring to the standard ASTM E-252, testing Brinell hardness testing using the ASTM E10 standard, micro structure testing done with standard ASTM E3 and chemical composition testing performed by the ASTM E1251 standard. The percentage value of depreciation for the wet sand molds variation of 0,66%, 0,92% metal mold and to mold RCS (Resin Coated Sand) by 0,66%. The difference in shrinkage occurs because the conductivity of each mold to absorbing heat is different, so the higher conductivity makes the metal solidification fast and also affects a large grain size that is seen on the microstructure. At the porosity is obtained from the true density, wet sand mold ρ = 8,869, metal molds ρ = 8,481, and RCS (Resin Coated Sand) ρ = 8,768 the higher the true density value the material is solid. The density of the material associated with violence is also higher Brinell testing of prints obtained on wet sand at 75,576 BHN, amounting to 86,038 BHN metal mold and mold RCS (Resin Coated Sand) 70,436 BHN. The chemical composition of the bronze is found (Cu) 76,00%, (Pb) 16,20%, (Sn) 5,73%, (Zn) 1,40%, (Ni) 0,496%, (Cd) 0,0731% and other

Exploration of the Advantages of Tourism Branding in Bali, Indonesia

Purpose:  This research tried to find a short-term solution by designing an itinerary model for Bali tourism destinations. This model was believed to be able to help travel entrepreneurs choose the tourism branding to take to their tourist destinations advantages.   Theoretical framework: Destination quality and marketing in the marketing mix, there is a set of marketing tools known as the 4P mix, namely Product, Price, Place, and Promotion, whereas tourism marketing has several additional marketing tools that are broken down or developed from product elements such as attraction, accessibility, convenience, and ancillary, which hereinafter known as 4A + 3P mixture. So the tourism marketing mix includes 3P namely: Price, Place, and Promotion, and added 4A namely Attraction, Accessibility, Amenity, and Ancillary   Design/methodology/approach: This study uses a desk research method by conducting studies and comparisons of several theories and secondary data from a couple of official reports then compared with the development of Bali tourism destinations. The Bali tourism destination consist of 8 regencies namely Badung, Gianyar, Bangli, Klungkung, Karangasem, Tabanan, Jembrana, and Buleleng, and 1 city that namely Denpasar.   Findings: All regencies and cities in Bali, it can be explained that Bali Tourism has branding strength in nature, heritage, and culture. The provincial government must be able to make a joint consensus to determine development priority scales based on the advantages of each region, who is the center of tourism, and who is the supporter of tourism. more importantly, what is the ideal distribution system, and determines the composition of the allocation of tourism's contribution to regional development in the Province of Bali.   Research, Practical & Social implications:  All the tourist attractions in all regencies and cities in the Province of Bali, it seems that they have the same category, except for the City of Denpasar. As a result, a joint promotion program through the promotion of the Province of Bali, will be able to become a more effective, and efficient promotion program.   Originality/value: The value of the study is finding the advantages of tourism branding in Bali can be determined in real-time

Pengaruh Kondisi Operasi Proses Pemekatan Litium Dari Geothermal Brine Sintetis Dengan Metode Direct Contact Membrane Distillation (DCMD)

Penggunaan lithium dalam pembuatan baterai meningkat secara signifikan dalam beberapa tahun terakhir. Karena peningkatan kebutuhan lithium, maka diperlukan sumber litium yang dapat di eksploitasi. Target dari penelitian ini adalah untuk memekatkan konsentrasi dari litium sebelum dilakukan proses pemisahan lainnya. Perangkat DCMD ini menggunakan perbedaan tekanan uap dikedua sisi membran sebagai driving force. Larutan umpan divariasikan pada berbagai suhu dan laju alir sedangkan suhu sisi permeat dipertahankan pada 25 °C. Suhu umpan divariasikan pada 60, 50, dan 40 °C dan laju alir umpan pada 420, 260, dan 180 ml/menit.  Untuk mengurangi penyumbatan pada membran, digunakan geothermal brine sintetis. Penelitian yang telah dilakukan menunjukkan bahwa suhu operasi dan laju alir memberikan pengaruh yang signifikan pada proses pengkonsentrasian lithium dari geothermal brine sintetis. Kenaikan suhu operasi dan laju alir umpan pada sistem DCMD menunjukkan adanya kenaikan konsentrasi lithium pada retentate dan fluks permeat yang dihasilkan. Hasil optimum diperoleh pada suhu 60 °C. dengan laju alir 420 ml/menit. Perolehan rerata fluks tertinggi dicapai pada 60 °C sebesar 7,3 LMH, di ikuti suhu 50 dan 40 °C sebesar 5,3 dan 2,7 LMH. Selain fluks diperoleh juga nilai Liquid enter pressure (LEP) 7,3 bar yang menunjukkan kekuatan membran dalam menahan tekanan uap, sehingga tidak terjadi wetting selama proses

Penentuan Kondisi Optimum Pembuatan Silica Gel Menggunakan Silika Geothermal dengan Metode Sol-Gel

Salah satu permasalahan yang muncul di lapangan pembangkit listrik panas bumi (PLTP) adalah terjadinya silica scaling dalam sistem pemipaaan akibat konsentrasi padatan terlarut yang tinggi pada air geotermal (geothermal brine). Silica scalling dapat menyebabkan penurunan efisiensi pembangkitan energi listrik dari panas bumi. Pada penelitian ini lumpur silika yang dihasilkan dari lapangan pembangkit listrik panas bumi akan dimanfaatkan sebagai raw material sintesis silica gel. Silica gel disintesis menggunakan metode sol-gel dengan variasi rasio natrium silikat dan air (1:3 ; 1:4 ; dan 1:5) dan konsentrasi asam klorida ( 0,5 M ; 1 M; dan 2 M). Karakteristik silica gel dilihat menggunakan analisis Forier Transform Infra Red (FTIR). Secara umum, pita serapan yang muncul pada spektra sample silica gel menunjukkan bahwa gugus fungsional yang terdapat pada silica gel adalah gugus silanol (Si-OH) dan gugus siloksan (Si-O-Si). Panjang gelombang 1055,86 cm-1­ menunjukkan gugus Si-O, yang mengindikasikan adanya vibrasi SiO4 dan polimerisasi Si-O-Si saat pembentukan silica gel. Selain itu, kapasitas penjerapan air oleh silika gel menunjukkan bahwa sampel dengan kode A7 memiliki kapasitas penjerapan air terbesar, yaitu mencapai 0,9331 gr air/ gram silica gel. Analisis Response Surface Methodology (RSM) mengindikasikan bahwa konsentrasi asam memberikan pengaruh singnifikan terhadap pembentukan silica gel dibandingkan dengan variasi pengenceran natrium silikat

A comparative co-simulation analysis to improve the sustainability of cogeneration-based district multi-energy systems using photovoltaics, power-to-heat, and heat storage

For an extensive decarbonization of district multi-energy systems, efforts are needed that go beyond today\u27s cogeneration of heat and power in district multi-energy systems. The multitude of existing technical possibilities are confronted with a large variety of existing multi-energy system configurations. The variety impedes the development of universal decarbonization pathways. In order to tackle the decarbonization challenge in existing and distinct districts, this paper calculates a wide range of urban district configurations in an extensive co-simulation based on domain specific submodels. A district multi-energy system comprising a district heating network, a power grid, and cogeneration is simulated for two locations in Germany with locally captured weather data, and for a whole year with variable parameters to configure a power-to-heat operation, building insolation/refurbishment, rooftop photovoltaic orientation, future energy demand scenarios, and district sizes with a temporal resolution of 60 seconds, in total 3840 variants. The interdependencies and synergies between the electrical low-voltage distribution grid and the district heating network are analysed in terms of efficiency and compliance with network restrictions. Thus, important sector-specific simulations of the heat and the electricity sector are combined in a holistic district multi-energy system co-simulation. The clearly most important impact on emission reduction and fuel consumption is a low heat demand, which can be achieved through thermal refurbishment of buildings. Up to \SI{46}{\percent} reduction in $CO_2$ emissions are possible using the surplus electricity from photovoltaics for power-to-heat in combination with central heat storage in the district\u27s combined heat and power plant. Domestic hot water heated by district heating network in combination with power-to-heat conversion distributed in the district reduces the load on the distribution power grid. Even though the investigated measures already improve the sustainability significantly, providing the energy needed for the production of synthetic fuels remains the crucial challenge on the further path towards net-zero