Demand response (DR) can compensate for imbalances in variable renewable energy supplies. This possibility is particularly interesting for electrochemical processes, due to their high energy intensity. To determine the technical feasibility and economic viability of DR, we chose the chlor-alkali process with subsequent polyvinyl chloride production, including intermediate storage for ethylene dichloride. We estimate the maximum possible cost savings of implementing load flexibility measures. A process model is set up to determine the system characteristic. Subsequent optimizations result in the facility's best possible dispatch depending on additional and minimum power load, storage volume, and cost of a load change. Real plant data are used to specify model parameters and validate the system characteristic and the plant dispatch. An economic evaluation reveals the economic advantages of efficiency and flexibility. The approach can be used to analyze the DR potential of other chlorine value chains or facilities with high electricity demand in general.
Combined heat and power (CHP) plants are efficient regarding fuel, costs, and emissions compared to the separate generation of heat and electricity. Sinking revenues from sales of electricity due to sinking market prices endanger the economically viable operation of the plants. The integration of heat pumps (HP) and thermal energy storages (TESs) represents an option to increase the flexibility of CHP plants so that electricity can be produced only when the market conditions are favorable. The investigated district heating system is located in Germany, where the electricity market is influenced by a high share of renewable energies. The price-based unit-commitment and dispatch problem is modeled as a mixed integer linear program (MILP) with a temporal resolution of 1 h and a planning horizon of 1 yr. This paper presents the optimal operation of a TES unit and a HP in combination with CHP plants as well as synergies or competitions between them. Coal and gas-fired CHP plants with back pressure or extraction condensing steam turbines (STs) are considered, and their results are compared to each other.
Reduced models of combined heat and power plants are required for different applications. Among other usages, they are implemented as mixed integer linear programs (MILP) in energy market models or price-based unit commitment problems to study the economic feasibility and optimal operation strategies of different units. Generic models are particularly useful when limited information is available for each considered plant. This paper presents a MILP modeling approach for combined heat and power (CHP) plants. The approach is based on energy and exergy balances and a few typical plant characteristics for different operating conditions. The reduction of electrical power output due to heat extraction is estimated by the transferred exergy to the district heating network. Furthermore, the accuracy, strengths and limitations of this approach are investigated for various CHP plant types with extraction condensing turbines designed for district heating systems. Therefore, detailed thermodynamic cycle simulations of CHP plants including part load operations are used to obtain the real plant operating conditions to compare them to the results of the described generic approach. The validation of the reduced, generic model shows that the accuracy mainly depends on the effectiveness of the heat extraction from the CHP plant. In addition, it can be seen that the main advantage of the presented exergy-based method is the inherent consideration of the feed flow temperature for the calculation of the power reduction due to heat extraction.
The prospect of clean electrical energy generation has recently driven to massive investments on renewable energies, which in turn has affected operation and profits of existing traditional thermal power plants.
In this work several coal-fired and combined cycle power units are simulated under design and off-design conditions to adequately represent the behavior of all modern thermal units included in the German power system. A dynamic optimization problem is then solved to estimate the short-run profits obtained by these units using the spot prices of the German electricity market (EEX) in years 2007–2010. The optimization model is developed using a Mixed Integer Linear Programming approach to take the on-off status into account and reduce computational effort. New market scenarios with increasing renewable shares (and consequently different spot prices) are finally simulated to analyze the consequences of a larger capacity of renewable energies on the optimal operation of traditional thermal power plants.
The global demand for wireless, mobile communication, and data services has grown significantly in the recent years. Consequently, electrical energy consumption to provide these services has increased. The principal contributors to this electricity demand are approximately 7 million telecommunication base stations (TBS) worldwide. They act as access points for mobile networks and have typical electrical loads of 2–3 kW. Whereas for most of the TBS, the electricity is supplied by the grid, approximately 15% are located in remote areas or regions with poor grid accessibility, where diesel generators (DG) supply the required electricity. Based on a dynamic simulation model the application of a latent heat storage (LHS) using phase change material (PCM) in existing off-grid TBS has been analyzed. The LHS unit has been modeled as an air-based storage with phase change temperatures between 20 °C and 30 °C with the PCM being macro-encapsulated in slabs. This paper demonstrates the potential to reduce the primary energy consumption in off-grid TBS through the following methods: optimization of the DG operating point, of the air conditioning unit operation schedule and the utilization of photovoltaic (PV) energy.
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