scholarly journals A Cluster-Based Baseline Load Calculation Approach for Individual Industrial and Commercial Customer

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 64 ◽  
Author(s):  
Tianli Song ◽  
Yang Li ◽  
Xiao-Ping Zhang ◽  
Jianing Li ◽  
Cong Wu ◽  
...  
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Average Model ◽  
Load Calculation ◽  
Different Types ◽  
Usage Patterns ◽  
Wholesale Electricity Market ◽  
Multiple Power ◽  
Baseline Calculation ◽  
The Impact

Demand response (DR) in the wholesale electricity market provides an economical and efficient way for customers to participate in the trade during the DR event period. There are various methods to measure the performance of a DR program, among which customer baseline load (CBL) is the most important method in this regard. It provides a prediction of counterfactual consumption levels that customer load would have been without a DR program. Actually, it is an expected load profile. Since the calculation of CBL should be fair and simple, the typical methods that are based on the average model and regression model are the two widely used methods. In this paper, a cluster-based approach is proposed considering the multiple power usage patterns of an individual customer throughout the year. It divides loads of a customer into different types of power usage patterns and it implicitly incorporates the impact of weather and holiday into the CBL calculation. As a result, different baseline calculation approaches could be applied to each customer according to the type of his power usage patterns. Finally, several case studies are conducted on the actual utility meter data, through which the effectiveness of the proposed CBL calculation approach is verified.

Detecting the impact of fundamentals and regulatory reforms on the Greek wholesale electricity market using a SARMAX/GARCH model

Energy ◽  
2018 ◽  
Vol 142 ◽  
pp. 1083-1103 ◽  
Author(s):  
George P. Papaioannou ◽  
Christos Dikaiakos ◽  
Athanasios S. Dagoumas ◽  
Anargyros Dramountanis ◽  
Panagiotis G. Papaioannou
Keyword(s):  
Electricity Market ◽  
Garch Model ◽  
Wholesale Electricity Market ◽  
The Impact ◽  
Regulatory Reforms

scholarly journals Demand response program in Singapore’s wholesale electricity market

2017 ◽  
Vol 142 ◽  
pp. 279-289 ◽  
Author(s):  
Shengfeng Zhou ◽  
Zhen Shu ◽  
Yue Gao ◽  
Hoay Beng Gooi ◽  
Shuaixun Chen ◽  
...  
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Demand Response Program ◽  
Wholesale Electricity Market

scholarly journals The Impact of Regulatory Reforms on Demand Weighted Average Prices

Mathematics ◽  
2021 ◽  
Vol 9 (10) ◽  
pp. 1112
Author(s):  
Sherzod N. Tashpulatov
Keyword(s):  
Electricity Market ◽  
Weighted Average ◽  
England And Wales ◽  
On Demand ◽  
Volatility Model ◽  
History Of ◽  
Wholesale Electricity Market ◽  
Model Residuals ◽  
The Impact ◽  
Regulatory Reforms

Average prices are popularly used in the literature on price modeling. Calculating daily or weekly prices as an average over hourly or half-hourly trading periods assumes the same weight ignoring demand or traded volumes during those periods. Analyzing demand weighted average prices is important if producers may affect prices by decreasing them during low-demand periods and increasing them during high-demand periods within a day. The prediction of this price manipulation might have motivated the regulatory authority to introduce price caps not only on annual average prices but also on annual demand weighted average prices in the England and Wales wholesale electricity market. The dynamics of demand weighted average prices of electricity has been analyzed little in the literature. We show that skew generalized error distribution (SGED) is the appropriate assumption for model residuals. The estimated volatility model is used for evaluating the impact of regulatory reforms on demand weighted average prices during the complete history of the England and Wales wholesale electricity market.

scholarly journals Novel Hybrid Stochastic-Robust Optimal Trading Strategy for a Demand Response Aggregator in the Wholesale Electricity Market

2021 ◽  
pp. 1-1
Author(s):  
Morteza Vahid-Ghavidel ◽  
Mohammad Sadegh Javadi ◽  
Sergio F. Santos ◽  
Matthew Gough ◽  
Behnam Mohammadi-Ivatloo ◽  
...  
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Trading Strategy ◽  
Optimal Trading ◽  
Wholesale Electricity Market

scholarly journals Study on Pricing Mechanism of Cooling, Heating, and Electricity Considering Demand Response in the Stage of Park Integrated Energy System Planning

2020 ◽  
Vol 10 (5) ◽  
pp. 1565
Author(s):  
Hang Yu ◽  
Zhiyuan Liu ◽  
Chaoen Li ◽  
Rui Liu
Keyword(s):  
Demand Response ◽  
Electricity Market ◽  
Optimal Solution ◽  
Energy System ◽  
Benefit Sharing ◽  
Selling Price ◽  
Pricing Mechanism ◽  
Integrated Energy System ◽  
The Impact

With the opening of the Chinese electricity market, as a retailer that provides energy services to consumers, the park-integrated energy system (PIES) not only serves as an effective way to earn benefits and reduce carbon emissions but also impacts the energy consumption characteristics of consumers. The PIES implements this function by adjusting the energy selling price in free energy markets. The pricing mechanism model (P-M model) is established to obtain the energy selling price in the planning and design stages. In this model, the impact of the demand response on the energy configuration and the impact of the changes in energy configuration on the energy cost price are both considered. Additionally, the optimal result ensures that both the consumers and the PIES benefit simultaneously. The reactive demand response zone, which represents a consumer trap, is found in numerical studies. The results indicate the following: (1) from the perspective of P-M model optimization, the benefit exclusive point of the PIES is the optimal solution in the short term; (2) from the perspective of the long-term benefit, the ultimate result in the relationship between the PIES and consumers is that the PIES will share its profits with consumers; in other words, benefit sharing point is the optimal solution for the long term.

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