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This paper will propose an approach to calculate and evaluate the reserve capacity and energy size of Pumping-Hydro Combined Energy Storage (PHCES) when wind power is integrated to power grid while considering the scheme of generation capacity allocation and operation of PHCES. This approach will use Monte Carlo Method to simulate large amount of samples to obtain the minimum value of capacity and energy size that could satisfy the requirement of system reliability. Finally this approach will apply in a RBTS system to assess the project feasibility.

With the increasing attention of environment protection and depletion of fossil fuel sources, the increasing advancement of renewable energy sources is indispensable [

Wind power has some adverse effect on power system owing to wind output is uncertain and variable, In addition, the electric energy is often supplied by diesel generators that can only operate in a fixed range in many grids. Therefore, there is a potential reliability issue when integrated wind power in to grid, which is the imbalance power between local demand and power generation [

In this paper, a simulation technique to size a PHCES for power system with wind farm based on PHCES dynamic model and scheme of generation capacity allocation is presented. It could provide beneficial information for wind farm owners and power system designers to evaluate the optimal size of PHCES. In addition, Monte Carlo simulation was used to determine the reasonable capacity power and energy size of PHCES and system reliability, because that this method do not depend on truly random numbers and it is suitable for evaluate complex systems [

In this paper, Weibull probability density function has been utilized to predict the value of wind speed every hour

The power output of wind turbine forcefully not only depends on wind speed, but also the performance characteristics of the turbine. The power output curve of the wind farm can be calculated by Equation (1).

where

The constants of A, B, C can be calculated based on the equation in [

Also the forced outage rate (FOR) of wind and conventional generators will be taken in to account. FOR of units indicates the unavailability of the system that is the basic parameter of non-sequential simulation algorithm measuring the system status by sampling, and the wind turbine will meet an average of 170 hours downtime and 1.5 times failures per year per turbine.

Load profile is difficult to predict because that it will influence by many factors, such as customer types, temperature and seasons. Hourly peak power consumption load model is most primitive and extensively adopted, and is established by documenting the load peak power in a set time [

Conventional generating system model will consider the scheme of generation capacity allocation which is that conventional generators will provide constant percentage of load demand, and the remaining load demand will supplied by wind power and PHCES, and the total real output of conventional generators

where

PHCES is addressed to compensate the generation output in order to balance the total generation and total demand in the system, when the output of conventional generators and wind farms do not match the total requirement of the loads. There are 11 conditions of PHCES operation, so that the dynamic PHCES model could be modified and

The outage power

Effective load carrying capacity (ELCC) is a kind of reliability index and is used to evaluate the value of the capacity of added renewable and traditional power plant. Loss of load expectation (LOLE) is the most common used index utilized

Operation Condition | Power output (MW) | Stored Energy (MWh) | Loss of Load Expectation |
---|---|---|---|

0 | 0 | 1 | |

0 | 1 | ||

1 | |||

0 | |||

0 | 1 | ||

0 | |||

0 | |||

0 | |||

0 | |||

0 | |||

0 | 0 |

to evaluate ELCC, which means the risk standard of the additional power plant, and in this paper, LOLE is considered as the reliability index and can be evaluated by Equation (4).

The aim of this paper is to searching the reasonable power capacity and energy size amount of PHCES which cooperated with wind power could let the result of Monte-Carlo simulation with LOLE value similar to conventional system. Though Equations (5) and (6) the power capacity and energy size could be simulated.

where:

N is the total number of samples for Monte-Carlo (in this paper, N = 10000).

There are five steps to evaluate the reliability index of test system:

1) Utilizing annual peak load demand and certain load variation pattern to predict load model

2) Using capacity and reliability data to build conventional generator output

3) Simulating the output of wind farm

4) Calculating

5) Evaluating LOLE of test system by comparing

In this paper, the load model data is modified based on the IEEE-RTS which is developed by the IEEE subcommittee on the Application of Probability Methods [

The total capacity of generating units is 240 MW which base on modified RBTS test system. The capacity of generating units and reliability data of modified RBTS test system has been shown in

The wind penetration level is the ratio of the installed wind generation capacity to the total installed system generation capacity, and assumes wind power penetration level is 20% in this case study. As previously mentioned, the total installed power capacity of conventional generators is 240 MW, and the total installed power capacity of wind farm is 48 MW. Besides that, the constant percentage of load demand that conventional generators should applied set to 90%. So that the real power output of conventional and the power output of wind farm could be simulated in a year. The curve of one year would be too dense, so this case study will show the curve in 100 hours. In

Unit size (MW) | No. of units | Failure times per year (occ/year) | average downtime (hours/year) |
---|---|---|---|

5 | 2 | 2 | 45 |

10 | 1 | 4 | 45 |

20 | 4 | 2.4 | 55 |

20 | 1 | 5 | 45 |

40 | 1 | 3 | 60 |

40 | 2 | 6 | 45 |

After 10,000 sampling, the reasonable capacity and energy size amount of PHCES can be evaluated. In this case,

The simulation results of reliability indices for conventional generation power system, wind-conventional generation power system and wind-conventional generation power system with PHCES are 1.0717, 19.3847 and 1.0346. Hence, for this system, the PHCES which minimum capacity data are 25 MW and 168 MWh should be installed to increase system reliability and satisfy the requie- ment of the scheme of generation capacity allocation.

This paper presents a way to evaluate the capacity of PHCES when wind power is integrated to power grid while considering the scheme of generation capacity allocation and operation of PHCES. It shows that PHCES with wind power integration could increase the reliability of generating system though balance the output of wind farm. The methodology is based on Monte Carlo method that is used to calculate the reasonable capacity and energy size of PHCES and calculate the system reliability.

Future work will focus on reliability cost and worth analysis to find the optimal capacity and energy size of PHCES. The approach proposed in this paper could calculate the operation of PHCES which contribute to evaluate the worth of PCHES.

Wang, S., Lo, K.L. and Lu, J.F. (2017) Calculating Size of Pump-Hydro Combined Energy Storage System in Wind-Diesel Systems Based on PHCES Dynamic Model. Energy and Power Engineering, 9, 224-231. https://doi.org/10.4236/epe.2017.94B027