A system dynamics model to analyze future electricity supply and demand in Iran under alternative pricing policies

Highlights

• A system dynamics model of electricity supply and demand is presented.

• The behavior of key variables in four subsystems is simulated under price policies.

• The results show that power supply fails to meet demand fully with current trend.

• In case of 90% rise in power and gas prices, demand is wholly met in all scenarios.

• In case of 90% rise in the prices, the allocated subsidy decreases by about 20%.

Abstract

Ensuring sustainable electricity supply is a key issue facing decision-makers. Due to its impact on system reliability, balancing supply and demand is essential. Electricity subsidy policies in many countries have led to high consumption and low power plant efficiency, and may cause an imbalance in the future. This research analyzes different electricity subsystems using system dynamics to investigate how and when low energy prices lead to an unstable situation. Simulation results using Iran's data show demand surpasses supply with a continuation of current trends. However, when the prices increase 90%, demand is met, and subsidy decreases by about 20%.

Introduction

As an infrastructure industry, electricity has a fundamental impact on sustainable development and the comprehensive growth of any region (Qudrat-ullah, 2014). Policy-makers generally justify granting subsidies to ensure the poor's access to electricity, and see it as a way to achieve social and distributional objectives (Komives et al., 2007).

In, 2017, the value of fuel subsidies was estimated at more than $ 300 billion, with Iran, China and Saudi Arabia having the most energy subsidies, respectively. Additionally, Table 1 indicates the top ten countries in the allocation of subsidies to the electricity sector (International Energy Agency (IEA), 2017). However, by distorting price signals, energy subsidies can increase energy consumption and reduce the incentive to save energy. For instance, the former Soviet Union, where electricity prices were much lower than their costs, faced high per capita consumption and low energy efficiency (Sterner, 2007). Energy subsidies also hurt the environment, decrease motive to invest in the energy sector, and they are not an effective way to support low-income groups (Coady et al., 2016). These issues make the economic and environmental sustainability of electricity generation worse (Akber et al., 2017). Therefore, countries with this structure may be involved with problems such as the gap between supply and demand and high emissions of greenhouse gases in the coming years.

Many countries prepare to diminish or eliminate subsidies to address these problems. However, energy subsidies are among the most pervasive and controversial financial policy tools due to their impacts on many sectors (Elkatiri and Fattouh, 2017). Considering the importance of the electricity industry and the effect of subsidized prices on electricity supply and demand, environment and system sustainability in general, models helping to better understand the interactions among the subsystems seem necessary for energy planners. Accordingly, a system dynamics approach is used in this paper to analyze the future behavior of a regulated electricity system and examine different pricing policies. The electricity system is challenging to model due to the complexity of feedback processes among the modules and its interactions with the economy and the environment (Qudrat-ullah and Seong, 2010). According to energy researchers, system dynamics is a suitable tool to model the dynamics and feedback structure of energy policy system (Ansari and Seifi, 2012). Many have used the system dynamics method for energy system planning and the development of models in various types of energy, including oil and natural gas (NG) (Hosseini and Shakouri, 2016; Pan et al., 2017; Kiani and Pourfakhraei, 2010), renewable energy (Tang and Rehme, 2017), environmental emissions (Liu et al., 2015; Saysel and Hekimoğlu, 2013), a specific industry (Chen et al., 2014) and electricity (Xiao et al., 2016; Wang et al., 2019).

Among the system dynamics models for energy systems, some of them are designed to analyze supply and demand and related policy interventions in deregulated power systems. Ochoa and Van Ackere (2009) considered the important dynamics of capacity expansion in the Swiss electricity market and the impact of different policies such as nuclear withdrawal and management of electricity exchanges. Simulation results indicated that international electricity exchanges are needed to meet demand, maintain low electricity costs and generate revenue for electricity companies. Olsina et al. (2006), Assili et al. (2008), De Vries and Heijnen (2008), and Kadoya et al. (2005) have also applied the system dynamics to model the dynamics of investment in the power industry, emphasizing the cyclic behavior. Using system dynamics, Verhoog et al. (2018) investigated the impact of low European electricity prices on electricity supply and demand sectors in Switzerland. They concluded that the current low electricity prices, which are mainly due to overinvestment in generation capacity, are likely to persist for another decade. Zapata et al. (2019) adopted a system dynamics method to simulate the effect of investment incentives in renewable and conventional energies on the supply and demand of Colombian electricity market. Their study showed that renewable complementarities help the security of supply at a lower cost than thermoelectricity plants, and that in the mid-term the system becomes much cleaner and more balanced.

The combination of system dynamics with other methods has also used to enrich the electricity supply and demand model. Pereira and Saraiva (2013) used a hybrid system dynamics and optimization model to simulate long-term behavior of electricity markets and the evolution of electricity price and demand. A feedback mechanism was defined between the individual expansion plans and the long-term dynamic model of the system. They applied a mixed-integer optimization as the input of the system dynamics model for updating the price and demand. A model based on system dynamics and dynamic systems was constructed by Morcillo et al. (2018) to simulate demand growth scenarios in the Colombian electricity market. Their study showed that Colombia is in dire need of new investment. Zhu et al. (2020) developed a system dynamics model of a tripartite evolutionary game to investigate the policy effects of the renewable portfolio standard. By simulating the strategic evolution of participants in the electricity market, they concluded that a stronger incentive is more effective than a heavier punishment.

A number of researchers have modeled generation expansion capacity under dynamic supply and demand conditions. These models assume a deregulated and fully competitive market. Qudrat-Ullah (2013) considered the issue of electricity generation capacity in Canada. According to the simulation results, he concluded that the current level of investment would not adequately meet the demand in the coming years. So, there is a need to increase investment which was simulated in another scenario. Qudrat-Ullah (2015) also investigated the impact of privatization and the investments made by independent producers in Pakistan's electricity sector. He proposed an alternative energy policy focused on indigenous resources to provide cheaper and cleaner electricity considering the problem of the severe gap between demand and supply and high greenhouse gas emissions from its current electricity generation. A comprehensive study of the system dynamics models about simulating the capacity expansion of the deregulated electricity markets was carried out by Teufel et al. (2013).

Additionally, among the generation capacity expansion models, some have also dealt with the issue of the capacity payment mechanism, which is used as an incentive to expand generation capacity. Hasani and Hosseini (2011) investigated the capacity investment in a decentralized market-based model, considering the complementary capacity mechanism. The long-term capacity investment decisions in the liberalized electricity market were evaluated, and investment decisions were fundamentally based on total revenues gained by investors. The system dynamics concepts were applied to model the structural characteristics of the electricity market, as the long-term behavior of firms and relationships among variables. Hasani-Marzooni and Hosseini (2013) suggested a complementary capacity mechanism with different payments for each region based on the reliability index to avoid shortages by comparing different payment schemes. The problem of the adequacy of electricity generation after liberalization reforms in a power system was investigated by Hary et al. (2016). They assessed the dynamic effects of capacity remuneration mechanisms for fewer shortages and lower generation costs. Ahmad et al. (2016) conducted a comprehensive overview of the application of the system dynamics in the electricity industry, which divided the models into six categories of policy assessment, generation capacity expansion, financial instruments, mixing-methods, demand-side management and micro-world.

In this study, a system dynamics model of the electricity industry is presented to analyze the supply and demand, the total subsidy allocated for electricity and gas consumption, as well as the amount of gas consumption in four subsystems. The model simulation is carried out using data from Iran's electricity industry under the policies of changing electricity and gas prices and various demand scenarios. The model examines the current policies as to whether or not they are suitable for the country's sustainable development. The distinctions between this study and the similar research are in the characteristics of the electricity industry's structure and the purpose of the study, both of which affect the problem modeling. The model is applicable to countries where the price of energy is not a function of supply and demand, unlike the way it is in a deregulated power industry. In such countries, pricing policies are determined by government strategies (Daneshzand et al., 2018).

Furthermore, governments allot subsidies to energy carriers to make them more affordable for consumers in this system. The modeled electricity industry also has a centralized and regulated structure in which competitive market rules do not necessarily work, and state-owned companies carry out the operational activities to supply electricity demand. To the best of our knowledge, none of the previous studies has modeled how the subsidized prices of electricity and power plants’ fuel affect electricity supply and demand in a centralized power industry. Moreover, another distinction of this study is the aim to model the effect of increasing electricity and gas prices on the amount of consumed gas and allocated subsidies. A suitable country case of the mentioned structure is Iran, where the government spends vast amounts every year to maintain low electricity prices, resulting in over-consumption, a dearth of investment, low power plant efficiency and severe air pollution.