kourosh apornak

The retail electricity market is the intermediary between end-user customer and the wholesale market to supply customers’ energy. One of the basic tools in interaction between the retailer and the end-user customer is use of demand response programs. In this research, a business-economic model with the aim of maximum interaction between retailer and other electricity market players based on interval optimization and demand response programs is proposed to achieve an optimal decision of retailer in bilateral contracts and the pool electricity market. This proposed model calculates the retailer's profit before and after the implementation of appropriate demand response program and ultimately maximizes the difference between these two values. The results show that by using price-based demand response programs and price elasticity of each customer, maximum participation of customer in reducing peak load of the power grid can be achieved. On the other hand, based on proper modeling of uncertainties such as price elasticity and pool electricity market prices, the retailer's profit will increase with a suitable level of risk. For retailer profit, it can be concluded that based on application of fuzzy and epsilon constraint method, determining an optimal pareto points and retailer profit maximization will occur in real time pricing tariff compared to time of use pricing tariff . From the maximum interaction point of view between the retailer and the end-user customer in the electricity market based on the current research, the preferred policy is the policy of using intelligent methods of price-based demand response programs.

Nowadays, with the revision in the rules and regulations of the restructured power systems, the energy security has become crucial. From the independent system operator (ISO) point of view, in the advanced defense approach also, the energy security has gained more importance. Thus, there is a close relationship between energy security via passive defense approach, energy supply and energy economy. In restructured power systems the customer energy supply can be managed in an acceptable limitation based on the demand-side management and demand response programs considering economic efficiency. In this paper, the energy security index before and after demand response is introduced in the economic environment of the power system. On the other hand, a comprehensive solution for energy security, energy supply and energy consumption, is also presented on the basis of the optimization hybrid approach.  In this regard, a study of energy the supply security in the presence of power retail market, regarding different pricing methods is carried out. Finally, the mixed integer programming (MIP) model is implemented in GAMS software via the CONOPT solver.

As the power system restructured, new entities emerged in the electricity market, including retail electricity companies. These entities purchase electricity from the wholesale market and sell it to consumers at competitive pricing rate. With the intermediary role of these entities, it is important to adopt a proper strategy in dealing with supply and demand side because this proper strategy has a significant impact on profit or loss of the retailer. This paper presents a model to maximize the retailer profit while calculating the optimal risk limitation based on bilateral contracts, pool market, customer’s behavior and price elasticity of demand. The proposed model in the form of optimization problem solved as a nonlinear programming with SNOPT solver of GAMS software. The results of applying the proposed model show the accuracy of the results and maximize the retailer's profit in comparison with the basic model.

The growth and expansion of economic concepts in the power system is increasing in last years. Energy economists have considered the optimal decision-making of electricity market retailers in recent years. In this paper, a demand response program based model is pro-posed in order to make the optimal decision of the retailer in the electricity market, taking into account the different conditions that the retailer may face. The optimal model presented by mod-eling the behavior of retailers and consumers, while maximizing the profit of retailers, also leads to the optimal purchase of retailers from conventional contracts in the electricity market. The formulation of the proposed model is based on the presence of the retailer in the bilateral con-tracts as well as the pool market contracts in such a way that the optimization problem is solved in the form of nonlinear programming with SNOPT solver in GAMS software. The results indicate the effectiveness of the proposed model based on the fact that while increasing the retailer profit, the retailer purchase is also managed in the bilateral contract and the pool market.

This paper aims to describe the role of electricity retailer in power market for persuading consumer to shift their loads. It presents the influence of load shifting on retailer profit and risk management in market environment. In this problem, retailer participates in bilateral contract, also stochastic programming is used to manage the uncertainties of pool prices and elasticity of consumer. It shows that by participating retailer in market contract, the retailer profit will be changed. This paper also analyzes the consumer behavior when the load is shifted from the time with high price to the time with low price. The tariff of demand response program used in this paper is Time of use pricing for the periods of week. Risk Measuring is done by Value at Risk (VaR) and Conditional Value at Risk (CVaR) in this study.