Elsevier

Computers & Operations Research

Volume 96, August 2018, Pages 244-255
Computers & Operations Research

A long-term capacity expansion planning model for an electric power system integrating large-size renewable energy technologies

https://doi.org/10.1016/j.cor.2017.10.006Get rights and content

Highlights

  • A new model with large-scale renewable energy technologies (RETs) is proposed.

  • The proposed stochastic model overcomes the drawbacks of existing models.

  • A heuristic-embedded sample average approximation method is proposed.

  • Uncertain RETs require more capacity to meet the target reliability of a system.

Abstract

The recent interest in reducing greenhouse gas emissions and the recent technical evolution of energy networks to smart grids have facilitated the integration of renewable energy technologies (RETs) into the electricity sector around the world. Although renewable energy provides substantial benefits for the climate and the economy, the large-size deployment of RETs could possibly hurt the level of power system reliability because of the RETs’ technical limitations, intermittency, and non-dispatchability. Many power system planners and operators consider this a critical problem. This paper proposes a possible solution to this problem by designing a new stochastic optimization model for the long-term capacity expansion planning of a power system explicitly incorporating the uncertainty associated with RETs, and develops its solution by using the sample average approximation method. A numerical analysis then shows the effects of the large-scale integration of RETs on not only the power system’s reliability level but also, and consequentially, its long-term capacity expansion planning. From the results of the numerical analysis, we show that our proposed model can develop a long-term capacity expansion plan that is more robust with respect to uncertain RETs and quantify the capacity the system requires to be reliable.

Introduction

The recent campaign to reduce greenhouse gas (GHG) emissions and the recent technical evolution of energy networks to smart grids have facilitated the integration of renewable energy technologies (RETs) into the electricity sector around the world. The International Energy Agency (IEA) reports that investment in RETs significantly increased in 2014, by up to 85% year on year, and RETs became the second-largest form of electricity in the world in 2014 (IEA, 2015). This report also projects RETs as the largest source of electricity worldwide in 2040 mainly due to the growth of wind power, hydropower, and solar photovoltaics (PV).

Following the global trend, the Korean government announced the strategic expansion of RETs in their biennial report on the plan for long-term electricity supply and demand (KPX, 2015). The strategic plan decided to dramatically increase the portion of RETs from 3.5% in 2015 to 13% by 2020 in Korea. This anticipated large-scale deployment of RETs made it necessary to consider them in the long-term capacity expansion plans that optimally determine when, how much and which type of power generation capacity to be expanded to meet the demand for electricity over a time span of several-decades. The Korean government’s capacity expansion plan attempts to minimize a specific economic value (e.g., total investment and expected generation costs) subject to capacity and several policy constraints, such as GHG reduction and generation mix.

However, an additional important part of the policy constraints is to attain the target system reliability, which is measured by the probability of demand-induced failures. An unreliable power system could lead to massive blackouts and high societal and economic costs. Therefore, system reliability is a crucial part of capacity expansion in the power generation industry, and many studies have considered the system reliability constraint in their optimization models for planning long-term capacity expansion (Bloom, 1982, Gote, Laughton, 1980, Noonan, Giglio, 1977, Scherer, Joe, 1977, Stremel, 1982). From the system reliability perspective, RETs have some well-known technical limitations such as intermittency and non-dispatchability. These RET characteristics result in supply uncertainty and weaken the power system reliability. Therefore, RETs increase the risks of system reliability and the challenging problems of planning and operating power systems when the capacity volume of RETs becomes large owing to the long-term plan of the Korean government.

In regards to the large-scale integration of RETs, this paper has a threefold purpose: First, we design a new optimization model incorporating the short-term uncertainty associated with RETs. The newly proposed model should develop an economically optimized plan and satisfy the target system reliability for the large-scale deployment of RETs. The Korean government currently uses a commercial software package, WASP1, which has been widely used in many countries although it fails to properly address the uncertainty in power capacity expansion decisions. Similarly, much recent literature on evaluating RET policies in the Korea electricity sector, including our previous works (Choi, Park, Hong, 2015, Park, Yun, Yun, Lee, Choi, 2016), ignores the uncertainty. This work is mainly motivated by this observation and aims to narrow the gap between practical needs and theoretical support.

This paper formulates the problem based on the decisions made by the Korean government. The Korean government is currently in charge of making nationwide capacity expansion decisions, referring to a centralized planning system. 2 Therefore, the mathematical model proposed in this paper solves a single optimization problem that covers generation capacity and gross demand across the nation in the context of Korean electricity market. Utilizing the practical model, we attempt to provide meaningful insights to practitioners who consider a centralized planning system like in Korea.

Referring to the decision process in Korea and other literature that ignores the transmission factors (Min, Chung, 2013, Pineda, Morales, 2016, Vithayasrichareon, MacGill, 2012, Zhu, Chow, 1997), we exclude transmission capacity decisions with aims to focus on the research purpose and simplify the problem. It is customary to sequentially carry out generation and transmission expansion planning, and transmission expansion planning generally follows a generation expansion plan (Pozo et al., 2013). Thus, the results of the model developed in this study can be used for planning a transmission expansion decision.

Third, we illustrate the effects of unreliable RETs on the level of the power system reliability and the long-term capacity expansion plan by comparing our proposed model with the existing residual load duration curve (RLDC) approach which prevails in the literature. Much literature has assumed a simple normal distribution or employed equivalent load duration curve (ELDC) or RLDC to address uncertainty and system reliability. It is noteworthy that we contribute to the literature by developing a model and its solution procedure, which explicitly considers the empirical distributions without making any impractical assumptions on the distributions. In regard to the use of empirical distributions, we extend the sample average approximation method to include a heuristic solution approach for handling constraints on system reliability. We conduct a series of numerical analyses to examine whether the traditional modeling approach suffices to address unreliable RETs and to emphasize the necessity of its improvement.

The rest of this paper is organized as follows. Section 2 reviews the previous literature on traditional capacity expansion planning for an electric power system and the recent efforts to consider renewable energy resources for future planning. Section 3 describes our suggested model, and Section 4 introduces our approach to finding a solution. Section 5 provides a numerical example to emphasize the differences in the suggested model. Finally, Section 6 presents some of our conclusions and discussions.

Section snippets

Literature review

The earliest research on the long-term capacity expansion plan for power systems was in the late 1960s. In the early 1970s, some works established basic optimization models for the planning decision-making problem. For example, Bessiere (1970) summarized the main features, objective function, and constraints of the optimization model. A deterministic linear programming (LP) model (Anderson, 1972) and a deterministic dynamic programming model (Peterson, 1973) were then introduced. However, these

Modeling a capacity planning problem considering system reliability

The purpose of this paper is to evaluate the effects of large-scale integration of RETs on reliable power generation and a long-term capacity expansion plan. We address this issue in the context of a long-term capacity expansion planning model, which optimizes not only the extent to which the nationwide capacity should be expanded but also the mix of generation technologies over the planning horizon. Unlike the existing models in the literature, we propose a mathematical model explicitly

Sampling-based approximation

Much literature summarized in this paper has simply assumed normal distributions or employed ELDC to obtain a closed form for the distribution of βtξ so as to formulate the problem as a formal optimization approach. Unlike the literature, we use the Sample Average Approximation(SAA) procedure to accommodate empirical distributions without making any impractical assumptions on the distribution. Particularly, we propose a heuristic procedure as a part of the SAA to explicitly consider a binomial

Numerical analysis

Referring to the Korean electricity market, this section develops an electricity system to validate the proposed model and provide valuable insights to practitioners. In addition, we define some test case scenarios and find an optimal capacity expansion plan under each case through numerical analysis.

By a comparative analysis using the decision results as well as the corresponding total cost and LOLP level of the sector, we describe the effects of the uncertainty caused by the renewable energy

Conclusion

Renewable energy resources have been rapidly integrated into the electricity sector across the world. Although renewable energy provides substantial benefits for both the climate and the economy, renewable energy supplies appear to be unreliable. Thus, the large-scale deployment of RETs might lower the level of system reliability. This paper attempts to contribute to the literature on long-term generation capacity plans by developing a new optimization model that explicitly considers system

Acknowledgment

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5A2A03925732). We thank Young-Sik Park at Power Planning Team in Korea Power Exchange for his helpful comments on this study.

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