Understanding electricity prices beyond the merit order principle using explainable AI

Electricity prices in liberalized markets are determined by the supply and demand for electric power,which are in turn driven by various external influences that vary strongly in time.In perfect competition,the merit order principle describes that dispatchable power plants enter the market in the order of their marginal costs to meet the residual load,i.e.the difference of load and renewable generation.Various market models are based on this principle when attempting to predict electricity prices,yet the principle is fraught with assumptions and simplifications and thus is limited in accurately predicting prices.In this article,we present an explainable machine learning model for the electricity prices on the German day-ahead market which foregoes of the aforementioned assumptions of the merit order principle.Our model is designed for an ex-post analysis of prices and builds on various external features.Using SHapley Additive exPlanation(SHAP)values we disentangle the role of the different features and quantify their importance from empiric data,and therein circumvent the limitations inherent to the merit order principle.We show that load,wind and solar generation are the central external features driving prices,as expected,wherein wind generation affects prices more than solar generation.Similarly,fuel prices also highly affect prices,and do so in a nontrivial manner.Moreover,large generation ramps are correlated with high prices due to the limited flexibility of nuclear and lignite plants.Overall,we offer a model that describes the influence of the main drivers of electricity prices in Germany,taking us a step beyond the limited merit order principle in explaining the drivers of electricity prices and their relation to each other.

Research on Optimal Configuration of Energy Storage in Wind-Solar Microgrid Considering Real-Time Electricity Price

Capacity allocation and energy management strategies for energy storage are critical to the safety and economical operation of microgrids.In this paper,an improved energymanagement strategy based on real-time electricity price combined with state of charge is proposed to optimize the economic operation of wind and solar microgrids,and the optimal allocation of energy storage capacity is carried out by using this strategy.Firstly,the structure and model of microgrid are analyzed,and the outputmodel of wind power,photovoltaic and energy storage is established.Then,considering the interactive power cost between the microgrid and the main grid and the charge-discharge penalty cost of energy storage,an optimization objective function is established,and an improved energy management strategy is proposed on this basis.Finally,a physicalmodel is built inMATLAB/Simulink for simulation verification,and the energy management strategy is compared and analyzed on sunny and rainy days.The initial configuration cost function of energy storage is added to optimize the allocation of energy storage capacity.The simulation results show that the improved energy management strategy can make the battery charge-discharge response to real-time electricity price and state of charge better than the traditional strategy on sunny or rainy days,reduce the interactive power cost between the microgrid system and the power grid.After analyzing the change of energy storage power with cost,we obtain the best energy storage capacity and energy storage power.

EV Charging Station Load Prediction in Coupled Urban Transportation and Distribution Networks

The increasingly large number of electric vehicles(EVs)has resulted in a growing concern for EV charging station load prediction for the purpose of comprehensively evaluating the influence of the charging load on distribution networks.To address this issue,an EV charging station load predictionmethod is proposed in coupled urban transportation and distribution networks.Firstly,a finer dynamic urban transportation network model is formulated considering both nodal and path resistance.Then,a finer EV power consumption model is proposed by considering the influence of traffic congestion and ambient temperature.Thirdly,the Monte Carlo method is applied to predict the distribution of EVcharging station load based on the proposed dynamic urban transportation network model and finer EV power consumption model.Moreover,a dynamic charging pricing scheme for EVs is devised based on the EV charging station load requirements and the maximum thresholds to ensure the security operation of distribution networks.Finally,the validity of the proposed dynamic urban transportation model was verified by accurately estimating five sets of test data on travel time by contrast with the BPR model.The five groups of travel time prediction results showed that the average absolute percentage errors could be improved from 32.87%to 37.21%compared to the BPR model.Additionally,the effectiveness of the proposed EV charging station load prediction method was demonstrated by four case studies in which the prediction of EV charging load was improved from27.2 to 31.49MWh by considering the influence of ambient temperature and speed on power energy consumption.

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

Considering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response becomes imperative for power grid companies.For this purpose,a power grid-flexible load bilevel model is constructed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,considering the lowest power grid dispatching cost as the objective function and incorporating the power grid-side constraints.Then,the lower level comprehensively considers the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-consuming cost as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing costs.

A Short-Term Electricity Price Forecasting Scheme for Power Market

Electricity price forecasting has become an important aspect of promoting competition and safeguarding the interests of participants in electricity market. As market participants, both producers and consumers intent to contribute more efforts on developing appropriate price forecasting scheme to maximize their profits. This paper introduces a time series method developed by Box-Jenkins that applies autoregressive integrated moving average (ARIMA) model to address a best-fitted time-domain model based on a time series of historical price data. Using the model’s parameters determined from the stationarized time series of prices, the price forecasts in UK electricity market for 1 step ahead are estimated in the next day and the next week. The most suitable models are selected for them separately after comparing their prediction outcomes. The data of historical prices are obtained from UK three-month Reference Price Data from April 1st to July7th 2010.

Analyses of Current Electricity Price and Its Changing Trend Forecast in the Coming Five Years

This paper analyzes the level, characteristics and existing problems of current electricityprice in China. Under the present circumstances the overall orientation of power price reform inthe 10th Five-year Plan period should satisfy the requirements of power industry restructuring.Therefore, it is necessary to set up an appropriate pricing mechanism and system including thelinks of sales price to network, transmission and distribution price (T&D price) and sales price.In the light of various factors influencing increase and decrease in price, a forecast of electricitytariff is given in the five years to come.[

Investing and Pricing with Supply Uncertainty in Electricity Market:A General View Combining Wholesale and Retail Market

Renewable energy,such as wind and solar energy,may vary signifi cantly over time and locations depending on the weather and the climate conditions.This leads to the supply uncertainty in the electricity(power) market with renewable energy integrated to power grid.In this paper,electricity in the market is classified into two types:stablesupply electricity(SSE) and unstablesupply electricity(USE).We investigate the investment and pricing strategies under the electricity supply uncertainty in wholesale and retail electricity market.In particular,our model combines the wholesale and retail market and capture the dominant players,i.e.,consumers,power plant(power operator),and electricity supplier.To derive the market behaviors of these players,we formulate the market decision problems as a multistage Stackelberg game.By solving the game model,we obtain the optimal,with closedform,wholesale investment and retail pricing strategy for the operator.We also obtain the energy supplier's best price mechanism numerically under certain assumption.We fi nd the price of SSE being about 1.4 times higher than that of USE will benefi t energy supplieroptimally,under which power plant's optimal strategy of investing is to purchase USE about 4.5 times much more than SSE.

Electricity Pricing Policy Should Serve Macro-Economic Control

The National Development and Reform Commission beefed up its efforts to promote the work of electricity price reform in 2004. It took measures in aspects of easing price contradictions, tentatively implementing discriminated price and time-of-use price and issuing a policy on the linkage of coal and electricity prices and price administration. In 2005 the basic thinking of the Commission's electricity price reform is to actively advance the pilot work of price reform,carry out the reform of transmission and distribution price, enlarge the scope of pilot work of large consumer's direct purchase, simplify sales price structure and bring about the linkage of coal and electricity prices.

A New Round of Reform in Electricity Pricing System in China

The State Council issued the Scheme for Reforming Electricity Pricing System m the second half of year 2003. It touches upon separating price of plant from that of network, sales price to network, transmission and distribution price, sales price and system principles in regard to electricity tariff mainly.

SVR-Boosting ensemble model for electricity price forecasting in electric power market

A revised support vector regression (SVR) ensemble model based on boosting algorithm (SVR-Boosting) is presented in this paper for electricity price forecasting in electric power market. In the light of characteristics of electricity price sequence, a new triangular-shaped 为oss function is constructed in the training of the forecasting model to inhibit the learning from abnormal data in electricity price sequence. The results from actual data indicate that, compared with the single support vector regression model, the proposed SVR-Boosting ensemble model is able to enhance the stability of the model output remarkably, acquire higher predicting accuracy, and possess comparatively satisfactory generalization capability.

An electricity price model with consideration to load and gas price effects

Some characteristics of the electricity load and prices are studied, and the relationship between electricity prices and gas (fuel) prices is analyzed in this paper. Because electricity prices are strongly dependent on load and gas prices, the authors constructed a model for electricity prices based on the effects of these two factors; and used the Geometric Mean Reversion Brownian Motion (GMRBM) model to describe the electricity load process, and a Geometric Brownian Motion(GBM) model to describe the gas prices; deduced the price stochastic process model based on the above load model and gas price model. This paper also presents methods for parameters estimation, and proposes some methods to solve the model.

Electricity Price Forecasting Based on AOSVR and Outlier Detection

Electricity price is of the first consideration for all the participants in electric power market and its characteristics are related to both market mechanism and variation in the behaviors of market participants. It is necessary to build a real-time price forecasting model with adaptive capability; and because there are outliers in the price data, they should be detected and filtrated in training the forecasting model by regression method. In view of these points, mis paper presents an electricity price forecasting method based on accurate on-line support vector regression (AOSVR) and outlier detection. Numerical testing results show that the method is effective in forecasting the electricity prices in electric power market

Electricity Pricing for Natural Gas CHP Projects The Higher, the Better?

Regarding the state's policy that gives a higher on-grid electricity price to natural gas CHP (combined heat and power) projects, this paper studies the effect of it on the operation of those projects by theoretical analysis and a case study. It concludes that on-grid electricity price on the high side, compared to heat price, will lead power plants to produce more electricity but less heat, thus causing decrease of the plants' thermal eff iciency and harm to energy saving of the whole society.

Debates on the Tiered Electricity Pricing Mechanism in China

Based on the Ramsey theory-the foundation for the tiered electricity pricing mechanism, this article analyzes the effects of the tiered electricity pricing system on social justice, eff iciency and commodity prices, and concludes that the system would direct subsidies to flow into low income groups, and promote energy conservation and emissions reduction by restricting over-consumption of high income groups, without enormous effect on commodity prices. The key to designing the tiered system is how to estimate the amount of electricity use for each tier, so as to avoid excluding low income groups from the subsidy or including high income groups in the subsidy.

Double Pressure on Power Grids——The demand for electricity is dropping while the electricity price is not adjusted properly

Since October 2008,China's social consumption of electricity had,for the first time,grown negatively compared to the same period of the previous year,and in November the negative growth range further expanded. The major pressure faced by the electricity industry has now turned from the contradiction between coal and electricity to electricity quantity. This is undoubtedly a true and new test to electricity enterprises which get used to high growth but are now suffering great losses. The reform of electricity system has already been in great difficulties and now is getting into a more serious situation. In order to help readers improve their knowledge and understanding of the current tough situation faced by the electricity industry and discuss how to alleviate and get through the difficulty resulted from the economic crisis "encountered once every one hundred years" by joint efforts of all parties concerned,a Seminar on Crisis and Countermeasures for Electricity Industry was held on November 20,2008. Here are some extracts from the speeches of four experts.

China hikes non-residential electricity price nationwide

On Wednesday, China announced adjustments for the prices of non-residential power and thermal coal in order to ease power shortages and reduce financial pressure on power companies. The National Development and Reform Commission (NDRC) announced that it will raise the retail price

Suggestions on the Current Electricity Price Level and Policies in China

The State Council decided to raise the retail electricity price by 0.25 Yuan/kWh from July, 2008. This will, to some extent, relieve the conflicts between power supply and demand, and decrease the economic losses in

Market-Oriented Electricity Pricing Mechanism Should be Eagerly Set Up in China

Electricity pricing is the core of the power institutional reform in China, which is related to not onlyinterests redistribution of all parties, but also health and security of the entire power industry. Only byaccelerating the reform on pricing mechanism can sound development of the power industry be promoted.