A Research into Probabilistic Electricity Load Prediction Based on Demand Response Feature under Smart Grid Environment

2013 ◽  
Vol 380-384 ◽  
pp. 3098-3102
Author(s):  
Ning Lu ◽  
Ying Liu
Keyword(s):  
Real Time ◽  
Demand Response ◽  
Electricity Market ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Load Prediction ◽  
Characteristics Analysis ◽  
System Risk ◽  
Probabilistic Load ◽  
Demand Changes

The construction of grid plays an important role in national economic development, social stability and peoples life. In case that electricity market adopts real time electricity price, users active participation and real time response to electricity price will change the traditional load prediction from rigid forecasting to flexible forecasting which takes electricity demand response into consideration. By using wavelet analysis and error characteristics analysis, the researches into the probabilistic predicting method for demand changes under the real time electricity pricing is carried out. The probabilistic load prediction result shall enable decision makers to better understand the load change range in the future and make more reasonable decision. Meanwhile, it shall provide support to electricity system risk analysis.

Time-of-Use Pricing in the Electricity Market: An Application of Stackelberg Game

2019 ◽  
Author(s):  
Atharva Ketkar ◽  
Joselyn Koonamparampath ◽  
Mayur Sawant
Keyword(s):  
Power Consumption ◽  
Demand Response ◽  
Electricity Market ◽  
Stackelberg Game ◽  
Electrical Power ◽  
Electricity Industry ◽  
Electricity Price ◽  
Electricity Pricing ◽  
Best Response ◽  
Time Of Use Pricing

Abstract Electrical power, generated and consumed, is perhaps, one of today’s most important construct in determining the progress of a people. The power mismatch between the generated and consumed power is one of the major issues faced in the electricity industry. This can be addressed by analysing user behaviour and manipulating it. This paper attempts to put forth a demand response (DR) technique using the concept of Time-of-Use (ToU) electricity pricing. The utilities have an upper hand of quoting the electricity price whereas the users must follow this price and give their best response of power consumption. This process is similar to a leader-follower setting as in a Stackelberg game where the follower acts according to the leader’s strategy and gives its best response in every situation. This paper proposes a pricing technique where the users are charged according to the amount of power consumed in the specific period of time.

Research on Demand Side Response System of Electricity Price Under Electricity Market Incentive Mechanism

2021 ◽  
Author(s):  
Fu Xianyu ◽  
Zhou Hongmei ◽  
Qi-jie Jiang ◽  
Ke Fan
Keyword(s):  
Power System ◽  
Demand Response ◽  
Electricity Market ◽  
Incentive Mechanism ◽  
Operating Cost ◽  
Electricity Price ◽  
Demand Side ◽  
Peak Shaving ◽  
Optimal Dispatch ◽  
Grid Operation

Aiming at the traditional day-ahead dispatching scheme of power generation, the paper proposes a power system security optimization dispatching model that considers the demand response of electricity prices under the electricity market incentive mechanism. Based on the peak and valley time-of-use electricity price, the paper establishes an incentive compensation mechanism to encourage users to be active. Participating in demand-side resource scheduling makes the effect of “peak shaving and valley filling” more pronounced. Simultaneously, to rationally configure the reserve capacity of grid operation, the system incorporates the expected power outage loss into the proposed model to ensure the grid operation safety. The analysis of calculation examples based on IEEE24 nodes shows that the power optimal dispatch model proposed in the paper considering demand response and expected outage loss can reduce the operating cost of the power grid under the premise of ensuring a certain level of reliability and realize the economy of the power system in the market environment and safe operation.

scholarly journals An Incentive Based Dynamic Pricing in Smart Grid: A Customer’s Perspective

2021 ◽  
Vol 13 (11) ◽  
pp. 6066
Author(s):  
Thamer Alquthami ◽  
Ahmad H. Milyani ◽  
Muhammad Awais ◽  
Muhammad B. Rasheed
Keyword(s):  
Demand Response ◽  
Dynamic Pricing ◽  
Optimization Problem ◽  
End Users ◽  
Electricity Price ◽  
Monetary Incentives ◽  
Electricity Pricing ◽  
Pricing Policy ◽  
Load Shifting ◽  
Demand And Supply

Price based demand response is an important strategy to facilitate energy retailers and end-users to maintain a balance between demand and supply while providing the opportunity to end users to get monetary incentives. In this work, we consider real-time electricity pricing policy to further calculate the incentives in terms of reduced electricity price and cost. Initially, a mathematical model based on the backtracking technique is developed to calculate the load shifted and consumed in any time slot. Then, based on this, the electricity price is calculated for all types of users to estimate the incentives through load shifting profiles. To keep the load under the upper limit, the load is shifted in other time slots in such a way to facilitate end-users regarding social welfare. The user who is not interested in participating load shifting program will not get any benefit. Then the well behaved functional form optimization problem is solved by using a heuristic-based genetic algorithm (GA), wwhich converged within an insignificant amount of time with the best optimal results. Simulation results reflect that the users can obtain some real incentives by participating in the load scheduling process.

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