The method of using millimeter-wave radar sensors to detect human vital signs, namely respiration and heart rate, has received widespread attention in non-contact monitoring. These are compact, lightweight, able sense various scenarios. However, it still faces serious problems noisy interference hardware, which leads a low signal-to-noise ratio (SNR). We used frequency-modulated continuous wave (FMCW) sensor operating at 77 GHz an office environment extract the rate person accustomed sitting...

The key challenge for automatic generation control (AGC) dispatch lies in the contradiction between detailed modeling required optimal and tight calculation time. current method includes (1) heuristics that allocates real-time commands based on certain rules (fast but nonoptimal) (2) proactive with a AGC model (relatively forecast error exists). development of renewables prevalence energy storage systems (ESSs) costly degradation calls combining advantages methods dispatch. With this mind,...

Power system dispatch is a general concept with wide range of applications. It special category optimization problems that determine the operation pattern power system, resulting in huge influence on security, efficiency, and economics. In this paper, problem revisited from basis. This paper provides categorization problem, especially an emphasis industrial Then, presents detailed review models. The common formulations are provided. Finally, discusses solutions lists major challenges.

Proper setting of regulation reserve (RR) requirements is essential for the secure and economic operation power grids. Currently, RR requirement normally determined based on ad-hoc experience or numerical methods that cannot comprehensively consider uncertainties fluctuation characters. Regarding increasing penetration renewables, it becomes an obvious challenge determining proper reasonably allocating costs to market participants. To address these issues, a data-driven assisted...

Real-time dispatch balances the power demand with minimized operating costs. For current model, is assumed to be constant within a time interval, while intra-interval balance left frequency regulation. Based on practical experience and simulations, this behavior may lead insufficient regulation uneconomic costs considering increase in fluctuations caused by renewables. In article, real-time method secondary behaviors proposed. Without changing interval of command, system mileage generation...

Probabilistic optimal power flow (POPF) is an important analytical tool to ensure the secure and economic operation of systems. POPF needs solve enormous nonlinear nonconvex optimization problems. The huge computational burden has become major bottleneck for practical application. This paper presents a deep learning approach problem efficiently accurately. Taking advantage structure reconstructive strategy stacked denoising auto encoders (SDAE), SDAE-based (OPF) developed extract high-level...

Short-term load forecasting (STLF) is the basis of power system operation. Considering that importance different training samples different, a sample weights assignment method proposed in this paper to help STLF learn key sample. At first, similarity measured considering characteristics input components. Based on this, are selected. Finally, assigned with through designed function. With method, model able focus crucial samples. Simulation results data-driven models demonstrate effectiveness method.

In market environment, it is necessary to reasonably allocate the frequency regulation mileage costs participants who cause need for mileage. this way, can be incentivized reduce their uncertainties and fluctuations, which helps improve ability consume renewables of power system. However, current cost allocation methods cannot consider comprehensive impact fluctuations different participants. With in mind, paper proposes a method based on contributions system unbalance proposed. The defined...

Reserve ancillary services are important for handling the uncertainty of renewables in power systems. In market environment, reasonable price signals used to guide optimal allocation reserve services. general, formed by clearing. However, current clearing methods do not consider controllability (in this paper, it refers cap renewables), which is essential accommodating large-scale renewables. As a result, cannot reflect influence To fill gap, operating component considering wind paper based...

Hydropower units (HPUs) are inevitably affected by vibration zone when participating in frequency regulation through automatic generation control (AGC). To improve this., the anti-vibration demand of HPUs is embedded into AGC command allocation existing studies. However., system ignored considering demand., which may deteriorate performance. With this mind., an method coordinating performance and proposed paper. Firstly., adjustment amount for crossing available capacity evaluated. Then,...

Probabilistic power flow (PPF) is an effective tool to address the increasing uncertainties in systems. However, high computational burden restricts practical application of PPF. Deep neural network (DNN) can achieve fast calculation structure DNN should match size system. With development renewable energy and demand, new buses or branches would be added Under this circumstance, trained-DNN for original system cannot applied extended To improve scalability system, a knowledge transfer method...

Abstract Security-constrained economic dispatch (SCED) is one of the most important daily tasks for operators. The scale security constraints huge practically-sized power systems, which makes SCED difficult or even impossible to be solved. Whereby, number active relatively small. By eliminating inactive constraints, complexity can significantly reduced. Focusing on it, this paper proposes an intelligent framework accelerate calculation without any loss accuracy. proposed uses a deep neural...

The large-scale integration of renewables has become an inevitable trend in China toward the target "carbon peak and carbon neutrality". Strong uncertainties will bring great challenges for security operation power systems. reasonable dispatch operating reserve is important way to handle uncertainties. stochastic method can effectively consider However, this faces computational obstacles. Therefore, deterministic used industrial practices. key point properly determine requirement before...

To establish green power systems, the development of clean but uncertain renewables has drawn global attention. Meanwhile, controllable resources with high carbon emissions such as coal-fired units (CFUs) are gradually degrading. Under this circumstance, it is a severe challenge for automatic generation control (AGC) system to maintain frequency performance systems. solve this, necessary make full use regulation capacity different types in AGC command allocation. Among resources, gas turbine...

With the rapid development of renewables, stress for deep peak regulation (DPR) and frequency (FR) power systems is increasing because degradation controllable resources uncertainty renewables. Reasonable dispatch an effective way to handle above challenge. However, sequential (the FR dispatched first, then DPR dispatched) currently used in department, which cannot coordinately consider requirements. In this way, capability remaining may not meet requirement. mind, a multi-resource joint...

Probabilistic optimal power flow (POPF) is an important analytical tool to ensure the secure and economic operation of systems. POPF needs solve enormous nonlinear nonconvex optimization problems. The huge computational burden has become major bottleneck for practical application. This paper presents a deep learning approach problem efficiently accurately. Taking advantage structure reconstructive strategy stacked denoising auto encoders (SDAE), SDAE-based (OPF) developed extract high-level...

Large-scale integration of renewables poses challenges for frequency regulation. To solve this, promoting multiple regulating resources in distribution network including energy storage systems (ESSs) to participate automatic generation control (AGC) dispatch has drawn much attention. However, the following two problems have yet be solved: 1) involving a large number increases computational burden AGC dispatch; 2) degradation oflifespan caused by providing regulation restricts application...

The connection of high-penetration renewable energy brings severe volatility and uncertainty, which puts forward higher requirements for the flexibility power system. At same time, problem matching supply demand has also expanded to a longer time scale, requires long-term resources. However, existing methods based on typical scenarios may no be applicable. And models with complex series characteristics bring challenges To this end, paper proposes flexible resources planning method that...

The user-side energy storage can effectively reduce the user's electricity cost and improve consumption reliability. However, existing planning methods do not consider selectivity of basic price billing method, evaluation decision-making factors schemes need to be improved. In this regard, paper proposes a method that takes into account different methods. Firstly, model is constructed with objective function minimizing cost, which maximum investment capital Then, proposed, net income period,...

Abstract Data-driven methods such as deep neural networks (DNNs) and Gaussian processes (GPs), have been a promising way to achieve the balance of calculation accuracy efficiency in power system analysis. For instance, studies are utilizing DNN-based method fast accurate probabilistic flow. These rely on sample data for training, which is mainly obtained by sampling. However, there still no guidance how select suitable sampling effectively generate representative training samples. To address...