Power system expansion planning under global and local emission mitigation policies
Introduction
Emission taxes can be an efficient way of reducing fossil fuel energy use, improving energy efficiency, and promoting the development of renewable energy [1]. However, it may also decrease economic growth and social welfare, create distortions on power system investments, have distributive effects, and lead to emission leakage [2], [3]. Thus, looking closely at the expansion-planning-level consequences of pollutant emission taxes is an essential task in determining the optimal long-term allocation of resources.
Determining the optimal expansion planning of the electric system is a complex problem because competitive electricity markets represent, perhaps, the most challenging supply chain. The commodity is subject to complex physical laws (e.g., Kirchhoff’s laws), is non-storable (at an affordable cost, although this is currently changing), demand is uncertain and highly correlated with the weather, and all demand must be satisfied instantaneously with a high level of reliability. In addition, service is provided over a network that is prone to congestion, flows over transmission lines cannot be directly controlled as in a transportation system, and the market is encumbered by numerous externalities. On top of that, the integration of intermittent renewable energy, the increase of storage devices, smart grid technologies, and electrification of the transportation and heat sectors rises many new challenges and opportunities. Ignoring these features of power systems may considerably distort long-term investment decisions in the power sector [4].
Several authors have studied the optimal expansion planning problem in the power sector. Some authors have approached the expansion of generation and transmission capacity separately, using approaches such as dynamic [5], mixed-integer [6], [7] and nonlinear programming [8], [9]. To incorporate uncertainty, probabilistic methods [10], [11] and Monte Carlo simulations [12], [13] have been successfully implemented. Solving methods include Benders Decomposition [14], [15], Branch and Bound algorithm [16], heuristic methods [17], [18], and game theory [19]. The same techniques can be applied when studying the expansion of both systems simultaneously [20], [21], [22], [23], [24]. Due to computational limitations, some authors have approached this problem using a sequential algorithm solution, although this method has proven to give sub-optimal solutions [25].
As more countries have become interested in the incorporation of taxes and other environmental and economic instruments to the energy sector, environmental penalizations and constraints have been incorporated into various expansion optimization models. For example, Wang et al. [26] have recently developed a linear generation expansion planning model to analyze the impact that Carbon Dioxide (CO2), Sulfur Oxides (SOx), Nitrogen Oxides (NOx), and Particulate Matter (PM) taxes will have on China’s power sector. Park and Baldick [27] developed a stochastic mixed-integer generation expansion planning model that considers various levels of carbon taxes. These models, however, do not consider transmission constraints. Kazerooni and Mutale [28] explored the consequences of carbon emission trading on the transmission network planning. Guerra et al. [29] addressed the expansion of both systems simultaneously, including mitigation options and reserve margin and CO2 emission constraints in a deterministic model. Alizadeh and Jadid [15] formulated a dynamic model for transmission and generation capacity expansion that restricts the emissions of SOx and NOx.
Other authors have focused on the impact of renewable energy integration on the system. Pereira et al. [30] developed a deterministic generation expansion planning model integrating a unit commitment problem. Their approach contrasts the effects of incorporating renewable energy sources into the system while minimizing costs (carbon taxes) and minimizing emissions. The impact of the transmission expansion decisions on the capacity of attractive wind power plants was studied by Jadidoleslam et al. [31], highlighting the importance of the selection of new lines on the attractiveness of new renewable projects. Li et al. [32] analyze the impact of inter-regional transmission grid expansion on the renewable energy dispatch. Lumbreras et al. [33] developed an efficient model to optimally solve the transmission expansion problem while dealing with the stochastic nature of renewable energy. Similarly, other authors have studied the impact of renewable distributed generation on the transmission system [34], and on the expansion of the transmission and generation systems [35]. In addition, Aguado et al. [36] studied the interaction of energy storage systems and the transmission network, finding that a deferral on the construction of new lines is possible when additional storage capacity is added to the system.
The current literature, however, lacks an in-depth analysis of the effectiveness and distributive effects of a comprehensive pollutant tax policy (i.e., affecting CO2, SOx, NOx, and PM emissions), while planning the long-term investments of the generation and transmission systems simultaneously. This is of particular relevance when considering that a joint capacity expansion of the transmission and generation systems provides a more economically efficient solution for the network update [37] and a more effective impact of the taxation due to the elimination of some transmission bottlenecks that affect the operation of existing and new generation [38]. Furthermore, none of the abovementioned works analyze the spatial distributive effects of implementing such pollutant taxes.
The work presented in this paper analyzes the impact of implementing CO2 and local pollutant emission taxes on the expansion planning of a power system. To do this, an optimization model based on a mixed-integer linear program is formulated and implemented to determine the optimal expansion of the power system considering the installation of both large-scale power plants and renewable-based distributed generation. The analysis considers a 10-year horizon and five policy-relevant scenarios. These scenarios were selected to combine the analysis of the impact of pollutant emission taxes and the study of the effects of other incentive policies, leading to some alternative, and plausible, evolutions of power sector investments. Differently than existing literature, special attention is given to the analysis of the spatial-temporal distributive effects of pollutant taxes. We apply this method to the main Chilean power system [39] and show that some regions obtain significant environmental benefits from implementing pollutant taxes while others suffer environmental damages. Understanding these spatial distributive effects is crucial both to the success, and general acceptance, of pollutant taxes implementation and to guide any area-specific compensation policy.
Differently than previous literature studying pollutant taxes effects (see [1], [2], [40]), the method proposed in this work employs a detailed model of the power system, including physical power flow laws (Kirchhoff’s Current Law and Kirchhoff’s Voltage Law), uncertainty of demand, network congestion, lumpiness of network investments, power generation externalities, integration of renewable energy, and distributed generation resources. These features are essential to avoid distortions in long-term investment decisions in the power sector [4].
This work is established as an alternative to the current modeling efforts to address the transmission and generation capacity expansion problem and jointly considers emission tax policies on local pollutants and CO2. Specifically, our proposed modeling approach allows planners and policy makers to consider the impact of the underlying global and local emission policy outcomes simultaneously while connecting long-term investment and short-term operation decisions. The present work is aligned with current industry practices, which rely on simulation-based models for accounting for the impact of emission policies in a given power system setup. In addition, the present work endogenously incorporates the impact of global and local emission policies in the long-term generation and capacity planning. In summary, the contributions of this work are twofold:
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Formulating a detailed model for long-term power system planning considering local and global tax emission policies. The proposed model is stated as a finite-dimension mixed-integer linear optimization model that guarantees the globality of the optimal solution of the model by means of any commercial off-the-shelf solver.
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Analyzing the impact of different emission policies in the Chilean power system. In particular, the analysis focuses on five scenarios driven by different emission policies, which are carefully studied from the viewpoints of their economic (cost-based) effectiveness and their distributive effects in 13 regions of Chile.
As a result of the aforementioned contributions, the proposed manuscript provides to policy makers, regulators, and energy planners an effective computational tool for assessing the spatial-temporal impacts of emission policies on additional capacity updates in power systems.
The remainder of the paper is organized as follows. Section 2 provides a detailed description of the proposed optimization model and its main features. Section 3 presents a brief overview of the Chilean power system and the details of the case studies considered. Section 4 shows the main simulation results and a discussion of them. Finally, Section 5 concludes the paper.
Section snippets
Description of the model
We formulate the power expansion planning problem as a mixed-integer linear program. We should note that, by using a linear model formulation, the optimal solution obtained from the proposed model is indeed the globally optimal solution of the system expansion planning problem [41]. The objective minimizes the total system cost, which is composed of four terms: the annualized investment capital cost of new generating units and lines to be built (CC), operations and maintenance cost (OM), load
Application of the proposed model to case studies
In this section, we first provide a brief overview of the Chilean power system, used in our case studies, and then we define each of the five scenarios employed in our analysis.
Simulation results
Using the previously mentioned information, a joint optimal generation and transmission expansion plan for a 10-year horizon has been obtained for each scenario that is analyzed. In this section, the main simulation results are described and compared.
Table 3 summarizes the aggregated results of the new power capacity added to the system in each case scenario. Fig. 1 shows the fraction (percentage) of the total capacity available to install during the entire horizon that corresponds to the
Conclusions
This work analyses the effects of global and local pollutant taxes on the joint transmission and generation expansion plan. In doing this, we analyze five scenarios representing different trends and energy policies for the next decade. Particularly, we have considered emission taxes for CO2, PM, SOx, and NOx, the possibility of having a strong incentive to hydropower development, and the possibility of facing a highly electrified demand. Our analysis is based on the formulation and
Acknowledgments
The research reported in this paper was partially supported by the CONICYT, FONDECYT/Regular 1161112 grant, by CONICYT, FONDAP 15110019 grant (SERC-CHILE) and by Skoltech NGP Program (Skoltech-MIT joint project). The authors especially thank the comments of two anonymous reviewers.
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