The high penetration of the wind energy in the power systems raises some issues such as ramping and mismatch between the wind power and power demand. One of the possible solutions to these issues is the demand side management (DSM). In this paper, dynamic economic dispatch (DED) incorporating different penetration levels of wind energy and utilizing the DSM is proposed to solve the issues related to high penetration of wind energy. The effect of utilizing the DSM on the operation cost with different test cases is discussed. The General Algebraic Modeling System (GAMS) using BARON as a solver and genetic algorithm (GA) with hybrid function are used to solve the proposed DED model and a comparison between them is assessed. The proposed model is applied to a six units’ generation system to test the effectiveness of the proposed model.
In Egypt most electricity is generated from electric power stations that use natural gas. The government decided to increase the generation from renewable energy, such as wind energy, to reach 20% at 2020. The wind energy has a lot of advantages which are clean and low running cost, however it has some disadvantages as the wind energy resources are intermittent in nature. As a consequence of high wind penetration, some issues must be widely studied which are as follows:
• Comprehensive focus on system planning and load forecasting.
• The inadequate correlation between the wind power and the load (power balancing issue).
• Ancillary services requirements such as faster ramp rates resources.
• Power quality issues such as voltage variations, voltage fluctuations and harmonics.
To solve these issues the electrical power system needs to be more flexible to respond to the instantaneous fluctuations in both load and renewable generation . This paper will focus on two issues from the above list which are power balancing issue and high ramp rates issue.
Energy storage and demand side management (DSM) or demand response (DR) are common flexible resources that show compatibility with wind power. All of them have been known as effective resources to integrate wind power; however, the experience in doing that remains limited. Energy storage and DR present reasonably quick response in shifting or clipping the load because of their flexible characteristics. Energy storage and DR are quiet not extensively installed on the power system (with the exception of pumped hydro storage) and need additional consideration of their importance to widely install them in power systems . As an example of utilizing a storage system to mitigate the wind variability, the system proposed in , in which a wind power smoothing system that uses an optimization algorithm to reduce the variability of wind energy, is introduced. In , a dispatch strategy is proposed which allows the battery capacity to be determined so as to maximize a defined service lifetime/unit cost index. Besides, it shows how to yield the short term wind farm output power schedule which meets the specified confidence level of power delivery commitment.
There is a lot of research work that incorporate the DSM for different objectives such as the economic evaluation of (DR) through a mathematical model . The objective is to find the fair value of the DR in mitigating the intermittent effects of the wind power. In , the DSM is utilized through two options which are peak clipping and demand shifting in a unit commitment problem to study the impact of high wind penetration on operation and cost savings from the use of DR. A day-ahead network constrained market clearing formulation considering DR is suggested in . It is concluded that this model can introduce flexibility into the load profile; less dependence on ramp up/down services by the conventional generators and increases the penetration of wind energy. In , a dynamic economic dispatch (DED) model is proposed having both thermal and wind generators. In this model, normally distributed random variables have been considered for the wind speed and load forecast errors. The DED model gives valuable information for reliable, safe, and economic operation of power systems. In , bio-diesel engines are used for compensation of the intermittent wind energy and solving ramp rate issue with wind energy. Real-time pricing (RTP) in case of high wind penetration has been utilized to decrease the re-dispatch costs and cancel loss of load events [10,11]. Besides, the results conclude that hosting wind and RTP into a market can result in a big surplus gains which will push electricity demand to respond to actual wind resource availability. Demand dispatch and probabilistic wind power forecasting is used to enhance the operation of electricity markets incorporating a high penetration of wind power . A stochastic optimization model for the day-ahead scheduling in power systems, with the hourly DR for managing the intermittency of renewable energy sources has been introduced in . The analysis of the impact of DSM, with the aim of enabling the integration of the growing intermittent resources in Portugal, has been discussed in .
In this paper, the solution for some of the issues related to the high penetration of wind energy such as load balancing difficulties and ramping problems has been discussed showing the importance of using DSM to solve these issues and the consequences for not using it. A DED model incorporating different penetration levels of wind energy is applied and the load shifting is implemented by using the DSM to solve the issues related to the high penetration of wind energy. The comparison between different cases has been demonstrated by using the DSM for shifting the shiftable loads and without using the DSM. Different load profiles such as summer and winter loads have been addressed and finally different participation levels from consumers and their effects on the results have also been addressed. GA with hybrid function and GAMS using BARON as a solver have been used as optimization techniques to solve the DED problem with different scenarios. It shows that both are almost giving nearly the same results, but GAMS is faster than GA, therefore the GAMS will be chosen for solving the DED model.
Full description of the dynamic economic dispatch and demand side management approaches is introduced in Section 2, the case study based on a system consisting of six thermal generators and one wind farm is fully described in Section 3, the discussion of the results are presented in Section 4, and conclusions are finally drawn in Section 5.
2. Modeling approaches
2.1. Dynamic economic dispatch (DED)
Optimal operation of electric power system networks is a challenging real-world engineering problem. The dynamic economic dispatch (DED) occupies a prominent place in power system’s operation and control. The goal of DED is to determine the optimal power outputs of online generating units in order to meet the load demand satisfying various operational constraints over finite dispatch periods. The DED considers additional practical constraints such as upper and lower bounds on the units’ ramping-rates. In reality, units will not respond to steep or instantaneous load variations.
In the proposed DED optimization problem, the cost of operation will be minimized through the day as given in Eq. (1) and subjected to the different constraints which are as follows: the load balance as given in Eq. (2) where the wind power can be utilized as any value between zero and the maximum forecasted wind power as in Eq. (3), loss value as given in Eq. (4), minimum and maximum generation capacities as shown in Eq. (5) and ramping up and down constraints as given in Eqs. (6) and (7) .