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.

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.

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 A Short-Term Decision Model for Electricity Retailers: Electricity Procurement and Time-of-Use Pricing

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3258 ◽  
Author(s):  
Feihu Hu ◽  
Xuan Feng ◽  
Hui Cao
Keyword(s):  
Robust Optimization ◽  
Demand Response ◽  
Electricity Market ◽  
Decision Model ◽  
Expected Profit ◽  
Optimization Approach ◽  
Short Term ◽  
Spot Prices ◽  
Retail Prices ◽  
Time Of Use Pricing

This paper establishes a short-term decision model, based on robust optimization, for an electricity retailer to determine the electricity procurement and electricity retail prices. The electricity procurement process includes purchasing electricity from generation companies and from the spot market. The selling prices of electricity for the customers are based on time-of-use (TOU) pricing which is widely employed in modern electricity market as a demand response program. The objective of the model is to maximize the expected profit of the retailer through optimizing the electricity procurement strategy and electricity pricing scheme. A price elasticity matrix (PEM) is adopted to model the demand response. Also, uncertainty in spot prices is modeled using a robust optimization approach, in which price bounds are considered instead of predicted values. Using a robust optimization approach, the retailer can adjust the level of robustness of its decisions through a robust control parameter. A case study is presented to illustrate the performance of the model. The simulation results demonstrate that the developed model is effective in increasing the expected profit of the retailer and flattening the load profiles of customers.

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.

scholarly journals Description of Colombian Electricity Pricing Derivatives

2021 ◽  
Vol 2 (3) ◽  
pp. 191-211
Author(s):  
Sellamuthu Prabakaran
Keyword(s):  
Electricity Markets ◽  
Electricity Market ◽  
Jump Process ◽  
Electricity Price ◽  
Price Dynamics ◽  
Model Estimation ◽  
Electricity Pricing ◽  
Electricity Derivatives ◽  
Analytical Formulas ◽  
Electricity Spot Market

Electricity markets are becoming a popular field of research amongst academics because of the lack of appropriate models for describing electricity price behavior and pricing derivatives instruments. Models for price dynamics must consider seasonality and spiky behavior of jumps which seem hard to model by standard jump process. Without good models for electricity price dynamics, it is difficult to think about good models for futures, forward, swaps and option pricing. In this paper we attempt to introduce an algorithm for pricing derivatives to intuition from Colombian electricity market. The main ambition of this study is fourfold:  1) First we begin our approach through to simple stochastic models for electricity pricing. 2) Next, we derive analytical formulas for prices of electricity derivatives with different derivatives tools. 3) Then we extent short of the model for price risk in the electricity spot market 4) Finally we construct the model estimation under the physical measures for Colombian electricity market. And this paper end with conclusion.

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