A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

Abstract

Abstract:As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs) to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED) model for the wind-thermal-energy storage system (WTESS) is developed in this paper. An optimization model with the wind power and the energy storage system (ESS) is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG). A Gaussian mixture model (GMM) distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS) is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.

Chance-Constrained Real-Time Dispatch with Renewable Uncertainty Based on Dynamic Load Flow

“…To demonstrate the advantages of the proposed CCP-CMCF, other two CCP methods are compared, i.e., CCP based on GMM (CCP-GMM) [23] and CCP based on analytical reformulation (CCP-AR) [22]. GMM is a powerful tool to fit various distributions, especially irregular distributions [23], but many Gaussian components may be needed to achieve desired accuracy, which will increase the computation burden to get the inverse of CDF.…”

“…GMM is a powerful tool to fit various distributions, especially irregular distributions [23], but many Gaussian components may be needed to achieve desired accuracy, which will increase the computation burden to get the inverse of CDF. AR tries to reformulate the CDF by a simple function.…”

“…Different analytic reformulations for chance constraints are discussed in [22] and it is pointed out that the reformulated chance constraints all have a similar form, but this approach cannot make full use of the distribution properties and may be inaccurate. Reference [23] developed a method dealing with random variables using Gaussian mixture model (GMM), which can deal with the irregular distribution well, but it has to use an iteration method to obtain the inverse of cumulative distribution function (CDF), which may influence the computation time. In order to overcome the drawbacks of the existing methods of calculating the probability of holding constraints, we propose a chance-constrained programming based on Cumulants and Cornish-fisher expansion (CCP-CMCF) to solve the real-time dispatch with renewable uncertainty and frequency regulation, in which the cumulants of random variables and Cornish-fisher expansions are adopted to calculate the probability of holding chance constraints.…”

Optimal Scheduling of Integrated Energy Systems with Combined Heat and Power Generation, Photovoltaic and Energy Storage Considering Battery Lifetime Loss

“…At the same time, the release of the electricity could be calculated from the rate of discharge depth and the rate of the discharge rate, which is called the total effective throughput, and each discharge event could be converted into effective ampere hours, when the total ampere hours reaching the total effective throughput, the battery scrap. In [11,12] an optimization model of a hybrid energy system with RE and BESS, which aims at the optimal dispatch of regulated resources considering the non-negligible frequency offset and system economic benefits was addressed. In short, the output capacity of the BESS would change under different energy states, which is reflected by the ampere hours, and it is crucial to take the lifetime loss into calculation at the time of considering the operation cost of a BESS.The optimization objectives have a significant effect on the scheduling of the IES, so different aims would lead to the diverse dispatch of each component, so studies focusing on the optimization of the IES cover many aspects, but are mainly concentrated on the improvement of multi-target energy efficiency [13,14], economic dispatch [15] and robust optimization [9].…”

Derivation and Application of a New Transmission Loss Formula for Power System Economic Dispatch

“…The economic dispatch (ED) problem [1][2][3][4][5] in a modern power system involves allocating the output power of each generator to minimize the total cost of the power generation satisfying load demand and transmission loss (TL) under the constraints of the generators' limits, line congestion, emission, renewable energy resources, and demand response. In a large interconnected power system, power is transmitted over long distances to distribution systems; consequently, TL is the dominating factor in power system ED.…”