Accurate prediction of regional wind power generation intervals is an effective support tool for the economic and stable operation provincial grid. However, it involves a large amount high-dimensional meteorological historical information related to massive stations in province. In this paper, lightweight model developed directly obtain probabilistic predictions form intervals. Firstly, input features are formed through fused image method geographic as well aggregation strategy, which avoids...

The importance of the environmental impact assessment (EIA) large development projects is increasingly underlined.Usually, EIA involves a lot qualitative and quantitative criteria.Data Envelopment Analysis (DEA), an effective method which used to rank select best alternative from set alternatives, not tailored address criteria, thus rendering application multiple criteria problems amenable.This paper presents new methodology Multiple Criteria Data (MCDEA) can both criteria.MCDEA divided into...

With the deepening of electricity market reform in China, competition retail becomes increasingly intense. Electricity retailers (ERs) need to explore new business models enhance their competitiveness market. Meanwhile, with improvement industrial production and people's living standards, more nonlinear electrical equipment have been put into use, leading severe harmonic pollution problems. Harmonic causes loss electricity, resulting economic customers, especially for large customers. In...

Abstract With the development of big data and artificial intelligence, applications smart grid have received extensive attention. Specifically, accurate power system load forecasting plays an important role in safety stability production scheduling process. Due to limitations traditional methods dealing with large scale nonlinear time series data, this paper, we proposed Attention-BiLSTM (Attention based Bidirectional Long Short-Term Memory, Attention-BiLSTM) network do short-term...

Accurate and reliable power generation energy forecasting of small hydropower (SHP) is essential for management scheduling. Due to nonperson supervision a long time, there are not enough historical records, so the model difficult be developed. In this paper, support vector machine (SVM) chosen as method short-term prediction because it shows many unique advantages in solving sample, nonlinear, high dimensional pattern recognition. order identify appropriate parameters SVM model, genetic...

Abstract Accurate power load prediction is an important guide for system planning and operation. High‐ or low‐load results will affect the operation of system. In recent years, deep learning technology represented by convolution neural network (CNN) transformer has been proved to be suitable prediction. This paper proposes a new short‐term hybrid forecasting model, called channel enhanced attention (CEA) temporal convolutional (TCN)‐based comprehensive model. method combines feature...

As a novel recurrent neural network (RNN), an echo state (ESN) that utilizes reservoir with many randomly connected internal units and only trains the readout, avoids increased complexity of training procedures faced by traditional RNN. The ESN can cope complex nonlinear systems because its dynamical properties has been applied in hydrological forecasting load forecasting. Due to linear regression algorithm usually adopted generic train output weights, ill-conditioned solution might occur,...

Short-term load forecasting (STLF) has always been a very important issue in power system planning and operation. Recently, along with privatization deregulation, accurate forecast of electricity received increasing attention. However, is difficult because the randomness uncertainties demand. Support vector machine (SVM) novel type learning machine, which successfully employed to solve nonlinear regression time series problems showed its potential STLF. accuracy STLF greatlty related...

Abstract China is implementing a new power system reform, with one goal of renewable energy absorption such as hydropower. However, the forthcoming spot market challenges cascade hydropower generation in terms short-term hydro scheduling (STHS) problem. Specifically, STHS involves fulfilling bilateral obligations and bidding for day-ahead uncertainty. Coordination these two tasks while managing risks becomes problem that must be urgently solved. Herein, we propose method based on...

In this paper, a two-dimensional Cournot model is proposed to study generation companies’ (GENCO’s) strategic quantity-setting behaviors in the newly established Yunnan’s electricity market. A hybrid pricing mechanism introduced market with aim stimulate demand. Market equilibrium obtained by iteratively solving each GENCO’s profit maximization problem and finding their optimal bidding outputs. As key element of market, impacts different parameters on price power state should be fully...

Abstract Under the medium- and long-term electric markets, cascaded hydropower stations face a series of practical challenges due to uncertainty inflow market price. For dispatch scheduling, allocation power generation in multimarkets is critical, including clean energy priority consumption market, inter provincial intra order maximize operator’s expected revenue reduce operation risks. Based on hydro-dominant electricity structure settlement rules, we propose optimal method for cascade...

Due to the distribution of runoff is uneven and uncertain in time space, there are huge differences between electricity markets dominated by hydropower thermal power. Therefore, how evaluate risk cascade plants participating market an urgent problem be solved. Based on rules southwest China which plays a leading role, this paper proposes analysis method for participate coupled with monthly day-ahead market: Copula-Monte Carlo used generate combined scenario daily clearing price, LINGO solver...

Coal-fired thermal power plants, which represent the largest proportion of China’s electric system, are very sluggish in responding to system load demands. Thus, a reasonable and feasible scheme for medium-term optimal commitment units (MOCTU) can ensure that generation process runs smoothly minimizes start-up shut-down times units. In this paper, based on real-world practical demands dispatch centers China, flexible mathematical model MOCTU uses equal utilization hours installed capacity...

To further promote market competition, enrich trading varieties, alleviate information asymmetry, and improve efficiency during electricity reform in China, the continuous bidirectional transaction (CBT) was designed applied Yunnan (YNEM), which is dominated by medium- long-term power energy trading. The clearing model for CBT with goal of maximum social welfare proposed two bidding stages, including call auction (CA) double (CDA). Correspondingly, integrated two-stage algorithm also...

As one of the most important renewable resources, small hydropower is also an emphasized project Clean Development Mechanism (CDM), which has been greatly developed and great importance to alleviate energy crisis resulting from rapid economic growth China in past few decades. The impact on power grid more obvious as plants operate a river run-off system generation output variation very large between wet period dry period. In meanwhile, operation management have many outstanding problems due...