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We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient...
Due to thermal inertia, commercial buildings can provide power system frequency reserves with the heating, ventilation and air-conditioning (HVAC) systems. In this paper, we follow up on a recently proposed framework for scheduling and provision of secondary frequency control (SFC) reserves within a building aggregation. We extend this framework with a new reserve scheduling formulation, which is...
We propose a model of a battery switching station (BSS) for electric buses (EBs) that captures the predictability of bus operation. We schedule battery charging in the BSS so that every EB arrives to find a battery ready for switching. We develop an efficient algorithm to compute an optimal schedule. It uses dual decomposition to decouple the charging decisions at different charging boxes so that...
Forecasting of wind speed and wind power generation is indispensable for the effective operation of a wind farm and the optimal management of revenue and risks. Hybrid forecasting of time series data is considered to be a potentially effective alternative compared with the conventional single forecasting modeling approaches such as autoregressive integrated moving average (ARIMA) and artificial neural...
To improve forecasting accuracy for baseline load and load impact from demand response resources, this paper develops three innovative statistical models. These models are regression spline fixed effect model, fixed effect change point model and mixed effect change point model. The models developed are applied to forecast baseline load and load impact from air conditioning cycling demand response...
As a type of clean and renewable energy source, wind power is being widely used all around the world. However, owing to the uncertainty and instability of the wind power, it is important to build an accurate prediction model for wind power for the grid-connected security operation. The performance of hybrid method is always better than that of single ones in the wind power prediction. Actual wind...
One of the most effective and cheapest strategies to integrate the fast-increasing number of solar-based generators is by forecasting their power output to schedule power dispatch, energy storages, manage backup generators, and compensate for any fluctuations of solar power. In particular, forecasting the insolation is invaluable to predict the power generated by photovoltaic arrays. An essential...
Spinning reserve (SR) allocation problem is of vital importance in maintaining power systems security and reliability. Considering forecast uncertainties, unit commitment problem and contingencies on the failure of transmission lines, a general probabilistic model for expected total cost is established and its corresponding solution for optimal SR allocation strategy is proposed. The objective function...
This paper proposes a novel two-stage stochastic optimization model that incorporates effect of dynamic line rating (DLR) on transmission network operation with increased penetration of wind generation, explicitly considering uncertainty in both wind generation and line rating. The stochastic model co-optimizes energy and reserve holding levels for the forecasted/expected condition (that with zero...
A control strategy to reduce OLTC operations resulting from high PV penetration on distribution feeders was developed and applied in this paper. The strategy uses 5-minute-ahead solar forecast to derive future voltage states on the distribution feeder. Unnecessary tap operations (TO) are identified as those that are reversed within 5 minutes, likely because of temporary cloudy or clear conditions...
This paper proposes a novel TRansformation Under STability-reTraining Equilibrium CHaracterization (Trust-Tech) enhanced methodology for the solar energy prediction. This novel method is an ensemble of Trust-Tech-enhanced, group-based genetic algorithm (GA)-assisted SVM predictors. Several distinguished features of the proposed method are as follows: Firstly, feature selection algorithm is used to...
The hybrid forecasting algorithm, based on empirical mode decomposition (EMD), has attracted considerable attentions and been widely applied to forecast electricity load, wind speed, and solar irradiation time series (TS). The basic idea of the EMD based method is to decompose the complicated original TS into a collection of sub-series and build specific forecasting models for individual sub-series...
A new uncertainty quantification (UQ) algorithm for the error analysis of solar power forecasting is introduced. In solar power forecasting, there is a strong need for lenders, operators, traders, and Virtual Power Plant (VPP) to evaluate the forecasting results provided by different forecast providers. The algorithm potentially evaluates the third party's forecast to increase the performance of VPP...
Improving the precision of wind power forecasting can be helpful to dispatch efficiency. In this paper, to examine the time varying characteristics in the high order moments of wind power time series, an improved auto-regressive conditional density (ARCD) model for wind power forecasting is proposed. First, a generalized form of ARCD model is presented. Furthermore, from three different aspects: skewed...
This paper introduces an application of the Gaussian Conditional Random Fields (GCRF) model for forecasting the solar power in electricity grids. The introduced forecasting technique is capable of modeling both the spatial and temporal correlations of various solar generation stations. It will be demonstrated in this paper how the suggested solution can significantly improve the forecast accuracy...
Internal winding faults are among the most common causes of transformer failure. Once a fault occurs, a fast and efficient method for its detection and location is required to repair and reconnect the device, thus avoiding further delays in the network operation. This paper introduces a simple method for the location of internal winding faults. This method is based on time-domain terminal measurements...
Despite the knowledge and experience of market operators, consultation with market participants, and approval by regulators, changes in market design do not always have the intended beneficial outcomes. Agent modeling can be a useful approach in validating whether there may be unintended consequences as market participants operate under new market rules. Examples of such outcomes are explored, with...
With the potential to enhance the power system's operational flexibility in a cost-effective way, demand response is gaining increased attention worldwide. Industrial loads such as cement crushing plants consume large amounts of electric energy and therefore are prime candidates for the provision of significant amounts of demand response. They have the capability to turn on/off an arbitrary number...
Due to its economical and environmental benefits to society and industry, integrating solar power is continuously growing in many utilities and Independent System Operators (ISOs). However, the intermittent nature of the renewable energy brings new challenges to the system operators. One key to resolve this problem is to have a ubiquitously efficient solar power output forecasting system, so as to...
Maintenance work of power equipment plays an important role in ensuring the security and reliable operation of power system and promoting the economic efficiency of enterprises. This paper takes the actual operating status of in-service equipment into account, calculates the current failure rate based on health index to improve the equipment reliability assessment. The fuzzy age reduction based failure...
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