Optimal short-term coordination of water-heat-power nexus incorporating plug-in electric vehicles and real-time demand response programs
Introduction
Under the hot weather condition, the consumption of the fresh water and electricity increases. In south of Iran, a huge value of seawater is available. But, the water scarcity and the electricity cascaded outages occurs in summer. Because, the seawater desalination plants and the power generation units should optimally be co-dispatched and the interdependence of the power procurement and water purification processes should be considered [1]. Meanwhile, population growth has caused the transmission scale power systems are operated in stability boundaries [2,3]. If the uncertainties of the water/heat/electricity demands are not considered in short-term or day-ahead scheduling of trigeneration hub networks, the load-generation imbalance may occur and led to water shortages and wide-spread power outages. Hence, some preventive actions such as forced interrupts [4,5] and incentive based demand response programs (DRPs) [6,7] can be implemented on residential [8], industrial [9,10], and commercial [11] end users. Another way to avoid from the water and energy crises is to use the energy storages such as aggregated electric vehicles [12].
Recently, researchers proposed the interesting methods for designing and co-optimizing the interconnected water and power hub systems. In Ref. [13], the authors investigated the economic performance of the wind powered water-energy hybrid network by determining the amount of the surface/embodied/groundwater requirement for generating 1 kW electricity and the value of the energy consumption in gross water desalination process. The use of the surplus electricity production of wind farm for salted water purification cycle results in a significant cost saving. Moreover, the fluctuations of the wind speed and power could be modelled in long-term (1 year) operating problem. In Ref. [14], the coupled water and energy network of Jordan is assess from technical and political viewpoints. Some key parameters such as physical distance and interconnection of water and power distribution systems and dominant stakeholders of power and water policy makers are merged. The increase of the water/energy efficiency in domestic applications has not the considerable economic benefit. More energy saving can be achieved by reducing the water leakage, replacing the old pumps with new ones, and using the renewable energy sources such as solar and wind for driving the water pumps. Scholars of [15] presented a global scale water-energy trade model based on ecological network analysis (ENA). The ENA algorithm models the trajectories of water and electricity trades for dominant competitors such as China, South and Central America, Middle East, Africa, and Australia. Studies show that China is equal to USA in utility mutual relationships. The synergism factors and the grid mutualism proves that the economic decisions mitigate the potential effects of the global electricity trade in solving the water shortage of China. Reference [16] developed a bi-level water-power management (BLWPM) program for minimizing the operation cost of the wastewater treatment and power generation plants. The optimization problem is restricted by the mass balance constraint, limitation of fossil fuels, load-generation balance, production capacity, electricity consumption in desalination, fresh water consumption in power plants, limited access to water sources, and emissions of pollutant gases. The BLWPM approach does not consider the site and the water shedding in the distribution scale. Although, the treatment of the waste water has a significant economic impact on combined water and power generation systems, but there is no gross water management strategy in BLWPM model.
In Ref. [17], a water-food-power hub system is studied over a 1-year period. In this model, the grey water is treated and reused in household sector. Moreover, the anaerobic digestion of the waste food for generating the biofuels is used for power generation. The water and electricity demands depends on seasonal conditions, while the waste food production and the food demand is less sensitive to weather variations. The probability of the water shortage is reduced by reusing the treated waste water for non-potable applications such as agricultural sector. In addition, the geographical location, food habits and culture should be discussed. In Ref. [18], the risk of the power curtails under the low river water flow and the high ambient temperature is minimized by smart utilizing the desalination systems and hydrothermal units. When the mass flow rate of the river water is low, the small increase in temperature may lead the conventional hydrothermal power plants shutdown. Hence, the load-generation mismatch may cause the voltage drop in the power system and cascading failures and catastrophic blackouts. The vulnerability of the hydrothermal units could be assessed in tropical regions. Authors of [19] introduced a policy-constrained model for cogeneration of water and power from river basin hosting hydrothermal units. The abnormal mass flow rate and temperature of the river water has more effect on electricity production of hydrothermal units. The river water could be used for cooling the pumps, transformers, motors, and turbines and increasing the system efficiency. Researchers of [20] optimized the short-term generation schedule of the combined heat and power systems in low-income and stand-alone networks. At off-peak time intervals, the additional heat and power can be used for generation and distribution of pure water.
According to reviewed works, there are many interesting studies on co-optimization of water and power generation systems. But, there is no research on day-ahead economic dispatch of water-heat-power hybrid systems, which consist of thermal power plants, heat only units, co-producers of heat and power, desalination processes, and co-generators of power and potable water. Moreover, participation of aggregated plug-in electric vehicles in water-heat-power nexus has not been studied, yet. As we know, pure electric vehicles with no need to fossil fuel consumption can be used for saving electricity at non-driving and off-peak demand periods and discharging it at plugged and on-peak electricity consumption hours to reduce the output power and fuel cost of the fossil fuels based thermal units and co-generators of heat and power (CHP). The changes of the operating points of CHP and power only units affect the optimum operation of the combined water and power (CWP) generation units. Hence, optimum operating points of desalination plants will vary because they are simultaneously co-dispatched with CWP producers to satisfy the fresh water demand. Meanwhile, the optimum operating points of the boilers, which should be co-scheduled with CHP plants to satisfy the heat demand, will be changed. In other words, incorporation of aggregated electric drive vehicles in energy procurement process will change the optimum operating points of all generation units in water-heat-power tri-generation systems. In addition, demand response programs, which shift a part of heat/water/electrical demands from peak fuel cost periods to less cost hours, have not been applied on integrated water-heat-electricity production systems. Therefore, this paper presents a mathematical model for optimal co-scheduling of water, heat and power producers. The novelties of the current paper consist of:
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Day-ahead optimal co-scheduling of water, heat and power systems is carried out. The fuel cost of the seawater desalination plant, heat extraction and power generation units is simultaneously minimized. The technical limits of the desalination plants, co-generation units, thermal stations, and heat only unit are considered as optimization constraints.
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Optimal charge and discharge decisions of plug-in electric vehicles (PEVs) are scheduled over a 24-h time interval for cost-effective energy management in both water-heat-power nexus and transportation sector. Participation of PEVs in power generation facilities by charging electricity through batteries during off-peak and mid-peak hours and extracting it for satisfying on-peak demand, reduces emissions of greenhouse gases and ozone-depletion substances, significantly.
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A real-time demand response programming strategy is implemented on water, heat and electricity loads for peak clipping, valley filling and load curve smoothing by shifting a part of each load from on-peak hours to mid-peak and off-peak periods.
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Four cases are studied to participate PEVs and implement DRPs on day-ahead economic coordination of water desalination units, power generation systems and heat treatment cycles.
The remainder of the current paper is structured as follows: Section 2 presents the problem formulation. Afterwards, numerical result and analysis are provided in Section 3. Finally, Section 4 concludes the paper.
Section snippets
Water-heat-power grid
The optimal short-term scheduling of the combined potable water, heat and electricity production systems consisting of desalination only processes, combined water and power (CWP) plants, heating cycles, combined heat and power (CHP) producers, and thermal generating units are presented as shown in Fig. 1. The electrical, heat and potable water demands of the test system have been considered to be satisfied by different producers such as power only units, combined heating and power (CHP) plants,
Case study
In this study, a sample water-heat-power production system composed of two CHP units, two heating only processes, three CWP producers, one water desalination plant, and four thermal generating units [27] is comprehensively studied.
Conclusion
This paper proposed a comprehensive model for optimization of water-heat-power trigeneration system over a 24-h study horizon. Moreover, implementation of time-amount based demand response programming strategy on desalinated water, heat and electricity demands of a benchmark tri-generation grid was investigated from an economic viewpoint. In addition, optimal charge and discharge decisions of aggregated plug-in electric vehicles is determined over at each operating time interval for minimizing
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(15 January 2018)