Optimal Operation of Critical Peak Pricing for an Energy Retailer Considering Balancing Costs

Abstract

Recently, there have been frequent fluctuations in the wholesale prices of electricity following the increased penetration of renewable energy sources. Therefore, retailers face price risks caused by differences between wholesale prices and retail rates. As a hedging against price risk, retailers can utilize critical peak pricing (CPP) in a price-based program. This study proposes a novel multi-stage stochastic programming (MSSP) model for a retailer with self-generation photovoltaic facility to optimize both its bidding strategy and the CPP operation, in the face of several uncertainties. Using MSSP, decisions can be determined sequentially with realization of the uncertainties over time. Furthermore, to ensure a global optimum, a mixed integer non-linear programming is transformed into mixed integer linear programming through three linearization steps. In a numerical simulation, the effectiveness of the proposed MSSP model is compared with that of a mean-value deterministic model based on a rolling horizon method. We also investigate the optimal strategy of a retailer by changing various input parameters and perform a sensitivity analysis to assess the impacts of different uncertain parameters on the retailer’s profit. Finally, the effect of the energy storage system on the proposed optimization problem is investigated.

A Review on the Applications of PSO-Based Algorithm in Demand Side Management: Challenges and Opportunities

“…A case study conducted in [105] showed that residential consumers exhibit a positive effect of demand response in time of CPP event, resulting in a reduction of power consumption. Several advantages of CPP include being easily implemented because it is based on the rate structure of TOU and additionally can enhance the responsiveness of the customer's price by imposing an extremely high rate during critical peak periods [106].…”

Energy management system of microgrid: Control schemes, pricing techniques, and future horizons

“…As a result, the critical peak pricing (CPP) tariff needs to include a forecaster of the critical events and a decision mechanism to set the critical price. 61 Furthermore, since critical events are restricted to a certain number of hours, yearly or monthly, consequently the suppliers should sensibly decide when to recognize a critical event in order to maximize revenue. It is also worth to mention that the CPP tariff may reach five times higher than the normal tariff; however, this technique of peak load reduction illustrated a considerable effectiveness in North America.…”

Cost of energy optimisation for the operation of microgrids based on demand response techniques

“…The methodology developed comprises of several steps, as shown in Figure 25. Leaf Community is collected, organised and made remotely available through the MyLeaf platform [33]. In this case, the MyLeaf platform is used to collect data of ambient temperature, irradiance and power demand of the buildings considered in the analysis.…”

“…Demand response is otherwise classified into (i) incentive-based, including direct load control, interruptible/curtailable rates, emergency DR, capacity market programs, and demand bidding programs, and (ii) time-based, such as time of use (ToU) rates, critical peak pricing (CPP), and real-time pricing (RTP). In CPP, a high rate is imposed on the customer in the case of critical events of high wholesale market prices [33]. In RTP, end customers are forwarded wholesale market prices a day or an hour before energy delivery.…”