Strategy-making for a proactive distribution company in the real-time market with demand response

Abstract

This paper proposes a methodology to optimize the trading strategies of a proactive distribution company (PDISCO) in the real-time market by mobilizing the demand response. Each distribution-level demand is considered as an elastic one. To capture the interrelation between the PDISCO and the real-time market, a bi-level model is presented for the PDISCO to render continuous offers and bids strategically. The upper-level problem expresses the PDISCO's profit maximization, while the lower-level problem minimizes the operation cost of the transmission-level real-time market. To solve the proposed model, a primal-dual approach is used to translate this bi-level model into a single-level mathematical program with equilibrium constraints. Results of case studies are reported to show the effectiveness of the proposed model.

Optimal Price Based Demand Response of HVAC Systems in Commercial Buildings Considering Peak Load Reduction

“…We propose optimal pricing decision model to reduce the peak load using HVAC system in this paper. Our paper has been compared with several previous studies on the development of retail pricing strategies for distribution network management via optimal operation of DR resources, particularly, with respect to the three comparative criteria such as decision models, DR resource models, and network load curves [10,[16][17][18][19][20][21][22][23].…”

“…For example, with the type of decision models, bi-level decision models were formulated in this paper, and in [18][19][20][21], whereas single-level decision models were developed in [16,17] and [10,22,23], depending on the types of decision-makers and their objective functions. The single-level decision models in [16,17] and [10,22,23] could not reflect the characteristic of DR resources because the price demand function and price sensitivity were assumed to be simple linear or quadratic function.…”

“…The single-level decision models in [16,17] and [10,22,23] could not reflect the characteristic of DR resources because the price demand function and price sensitivity were assumed to be simple linear or quadratic function. While the bi-level decision models in [18][19][20][21] could consider the optimal demand of DR resources for retail electricity price because the hierarchical relationships between decision-makers could be reflected by bi-level optimization problem. In other words, the bi-level decision model reflects the conflicting objective functions of the autonomous decision-makers based on Stackelberg game theory.…”

Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach

“…The impact of demand response integration on peak energy consumption, energy price and emissions under load uncertainty is analyzed in [2]. A model of demand response participation in real-time markets to minimize the operation cost considering the load elasticity is formulated in [3]. The interaction between renewable intermittency and demand response in the market environment is investigated in [4].…”

Optimal single phase smart meter design

“…Several approaches are used to reconfigure the electricity market to improve the capacity of the network, the efficiency of the energy flow, and the development of a scenario that can reduce the carbon emission by setting the system constraints [15]. Some of those strategies are demand side management [1][2][3][4][5][6][7][8][9][10][12][13][14][15][16], demand response strategy [17][18][19], real-time electricity pricing environment, and day-ahead electricity pricing strategy [6][7][8][9][20][21][22][23][24]. The promise of renewable energy development and integration is of significant value in the smart grid environment which can quickly facilitate a mixing of different generation resources in various electricity market configurations [20,21,24].…”