“…Equation ( 13) is the objective function, where the overall costs of generating power from generators and storage units are minimized. The power balance in Equation (14) ensures that for all times t, all power consumed by demands D(z) at zone z equals the sum of all power generated from generators Ĝ(z), the net power output of storage units Ŝ(z), and the sum of flows F zy,t going into zone z from adjacent zones y ∈ Z(z). Equation (15) ensures that imports F zy,t to zone z from zone y equal exports F yz,t from zone z to zone y.…”
Section: Methodsmentioning
confidence: 99%
“…[13] find that a country such as Germany with a diverse supply and demand structure can benefit from keeping a zonal pricing scheme, as it helps them maintain a relatively low electricity price level throughout the entire country. The need to combine market and grid models in order to perform studies that can assess the increased integration of renewable energy sources (RESs) into the electricity system is stressed in [14]. When exploring future scenarios for the power system, the market perspective can only be a starting point, as especially grid extension and operational issues will play a vital role in the future evolution of the system.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In order to calculate LMPs, one has to solve a large optimization problem. We formulate the problem as an economic dispatch model [14,[32][33][34][35][36], which in its full formulation reads:…”
The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and temporal resolution that is solved in sequences. The sequenced problem is guided through soft constraints that are enforced with different sets of penalty factors. The proposed methodology allows for adjustments to congestions on short timescales and proves to perform well in comparison to other approaches to this issue suggested in the literature. Following the input profile closely on a long timescale renders good results for the nodal model.
“…Equation ( 13) is the objective function, where the overall costs of generating power from generators and storage units are minimized. The power balance in Equation (14) ensures that for all times t, all power consumed by demands D(z) at zone z equals the sum of all power generated from generators Ĝ(z), the net power output of storage units Ŝ(z), and the sum of flows F zy,t going into zone z from adjacent zones y ∈ Z(z). Equation (15) ensures that imports F zy,t to zone z from zone y equal exports F yz,t from zone z to zone y.…”
Section: Methodsmentioning
confidence: 99%
“…[13] find that a country such as Germany with a diverse supply and demand structure can benefit from keeping a zonal pricing scheme, as it helps them maintain a relatively low electricity price level throughout the entire country. The need to combine market and grid models in order to perform studies that can assess the increased integration of renewable energy sources (RESs) into the electricity system is stressed in [14]. When exploring future scenarios for the power system, the market perspective can only be a starting point, as especially grid extension and operational issues will play a vital role in the future evolution of the system.…”
Section: Literature Reviewmentioning
confidence: 99%
“…In order to calculate LMPs, one has to solve a large optimization problem. We formulate the problem as an economic dispatch model [14,[32][33][34][35][36], which in its full formulation reads:…”
The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and temporal resolution that is solved in sequences. The sequenced problem is guided through soft constraints that are enforced with different sets of penalty factors. The proposed methodology allows for adjustments to congestions on short timescales and proves to perform well in comparison to other approaches to this issue suggested in the literature. Following the input profile closely on a long timescale renders good results for the nodal model.
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