Annual Cost Of System Research Articles

Multi-criteria performance analysis and optimization of a solar-driven CCHP system based on PEMWE, SOFC, TES, and novel PVT for hotel and office buildings

Solar-powered multi-generation systems contribute to efficiently reducing the consumption of fossil fuels and lowering greenhouse gas emissions. This study proposes a solar-driven CCHP system combined with a novel photovoltaic thermal collector, proton exchange membrane water electrolyzer, solid oxide fuel cell, and thermal energy storage to meet the user's multiple dynamic energy demands. Multi-criteria performance analysis of the CCHP system is conducted from the perspectives of energy efficiency, sustainability, energy savings, environmental benefits, and economy for typical hotel and office buildings. The multi-objective optimization is carried out to optimize the parameter configurations and equipment capacities of the proposed system. The results demonstrate that the PV coverage ratio of the partially covered parabolic trough photovoltaic thermal (PCPTPVT) collector has noteworthy influences on the PCPTPVT outputs, the determination of the equipment capacities of the CCHP system, and further affects the overall comprehensive performance. The sustainability indicators of the hotel and office rise with the increasing PV coverage ratio, and that of the office is gradually larger than that of the hotel. The optimal comprehensive performance and annual total cost of the CCHP system from the multi-objective optimization are 1.004 and 87601 $ for the hotel and 1.049 and 92759 $ for the office, respectively. The PV coverage ratios of the preferred optimal solution for the hotel and office are 0.659 and 0.859, respectively.

Techno-economic optimization of hybrid solar system with energy storage for increasing the energy independence in green buildings

The optimal design and optimization of the hybrid renewable energy system powered by photovoltaic panels (PV) with appropriate backup energy storage is the essential for increasing the energy independence in green buildings. This paper designs and compares hybrid PV panel with two main energy storage systems in remote areas (PV/battery and the off-grid PV/hydrogen system). These hybrid renewable energy systems are capable for producing steady output to the grid at the least total annual cost (TAC) of system, with maximum acceptable lack of power supply probability. A particle swarm optimization (PSO) has been developed using MATLAB to optimally design a hybrid PV/battery/hydrogen system. To confirm the superiority of the PSO method, the optimization problem was implemented in 1 to 30 independent executions and the best result was reported. Actual meteorological data in China is selected to test the concept of the off-grid solar energy system. The effect of changes in system reliability, number of run, and interest rate on the design results of two systems are compared and analyzed. The research found that the PV/battery system in remote areas becomes more economical than the off-grid PV/hydrogen system as reliability decreases and interest rate increases. Also, the total configured capacity of solar panel in the PV/battery structure is smaller (by 44.8 %) than that of the PV/hydrogen structure. Moreover, with the increase of number of run from 1 to 20, the number of components, in the PV/hydrogen system is adjusted to decrease the TAC (by 2.2 %), and the TAC of the PV/battery also decreases by 0.23 %.

Optimization on building combined cooling, heating, and power system considering load uncertainty based on scenario generation method and two-stage stochastic programming

The energy demand uncertainty is a complex issue for design tasks of building combined cooling, heating, and power (BCHP) systems. To overcome this problem, the characteristics of energy demand uncertainty need to be precisely described by generating massive scenarios. Here, the aim of the research is to study the effects of scenario generation methods on BCHP optimization considering energy demand uncertainty. Four scenario generation methods were compared and studied—two conventional probability-based methods using Monte-Carlo simulation and the Latin hypercube method to sample the basic scenario, as well as simulation-based methods based on building performance simulation. Two optimization models, including an independent scenario optimization (ISO) model and a two-stage stochastic programming (TSSP) model, were used to minimize the total annual cost of the BCHP system. Dynamic time warping (DTW) was applied for investigating differences between scenario generation methods. The results show that Monte Carlo building performance simulation (MCBPS) is the most similar to the basic scenario. The system cost obtained by the uncertainty based optimization method is 1.5% - 3.6% higher than that of the deterministic optimization method. This is mainly due to the capacity increase of peak shaving equipment. From the perspective of anti risk, relatively higher internal combustion engine (ICE) capacity has stronger anti risk ability, which can effectively reduce the total cost of the system. This study can provide a theoretical reference for architectural design and operation research based on uncertainty.

Optimal configuration of wind storage capacity based on VMD and improved GWO

In view of the fluctuation of the output power of wind power generation, a hybrid energy storage capacity optimization configuration strategy combining variational mode decomposition (VMD) and improved Grey Wolf Optimizer (GWO) is proposed, taking the wind storage joint system as the research object. The sliding average method is used to obtain the target power of the wind power grid connection and use the VMD decomposition processing to allocate the energy storage target power to the different energy storage devices in the hybrid energy storage system. The capacity optimization model of hybrid energy storage system with the minimum annual configuration cost of energy storage system as the target function is established, and the improved Grey Wolf Optimizer is used to solve the model, and the simulation and analysis are conducted on Matlab / Simulink, so as to verify the effectiveness and economy of the proposed capacity optimization configuration method.

Design and analysis of a photovoltaic‐powered charging station for plug‐in hybrid electric vehicles in college campus

Photovoltaic-powered electric transportation systems are gaining global momentum owing to their superior enactment and zero carbon emissions. With a growing number of electric vehicles (EVs) on the road, implementation of efficient and well-organised charging stations is extremely indispensable. The authors investigate the feasibility of creating a charging station for plug-in-hybrid EVs at an educational institution, E.G.S. Pillay Engineering College, Nagapattinam, Tamil Nadu, India (10°48.2′N, 79°50.1′E). The statistics related to the solar radiations of the Nagapattinam region are employed to find out the energy availability for the EV charging station (EVCS) and the requirement for grid connection. The authors use a hybrid optimisation model for an electric renewable (HOMER) simulator to determine the optimum specification of the proposed EVCS. Also, the authors carry out a techno-economic study against the specified load requirement to evaluate the potential of the charging station. The solar irradiance data obtained from NASA ground climatology and the solar power dataset of the designated site are used to realise the precise fallouts. The optimisation results provide minimum annual system cost and reliable power to the EVs. Based on these results, an EVCS is erected in the college campus to charge plug-in hybrid electric vehicles. The established EVCS contains 3 kW EV charger operating as a microgrid and includes nine solar panels with 335 W each, 48 V, 150 Ah specification. The authors use solar photovoltaic (PV) panels using Copper Indium Selenide-Zinc sulfide (CISZS) quantum dots for maximising energy yield from the EVCS. The authors consider that eight different charging profiles for different months are employed for estimating the solar irradiance probability density in the designated site. From this study, the authors can conclude that Gaussian mixer model (G4) profile is optimum for the Nagapattinam region to install a potential and reliable EVCS.

Operation mode performance and optimization of a novel coupled air and ground source heat pump system with energy storage: Case study of a hotel building

The problem of soil heat imbalance in traditional ground source heat pump (GSHP) systems in cold regions hinders the utilization of geothermal energy. This paper takes a hotel building energy supply system as an example to study the feasibility of a coupled air and ground source heat pump system with energy storage. The design intention of the proposed system was to add an air source heat pump (ASHP) and a water source heat pump (WSHP) as auxiliary heat sources to undertake part of the energy supply function of a GSHP. In winter, the system uses the ASHP as the low temperature heat source of the WSHP, so that its heating performance is basically not affected by extremely low outdoor temperatures, with an average system COP of 2.3. Combined with the energy storage (cold and heat storage), the “peak load shifting” of the power grid and the minimization of the system operation cost are realized. The simulation model of the novel system is established and verified by the monitoring data of the system. The operation mode is optimized to maximize the COP of the system, and the defrosting mode of the ASHP and soil heat balance were analyzed. The results show that the optimized defrosting control can increase the heating capacity of the ASHP by 13.9%. In addition, the proposed system can not only maintain the soil heat imbalance rate to 2.6%, but also reduce the operating cost. The calculation shows that compared with the traditional GSHP system, the annual operation cost of the novel system is only 58%, and the carbon emission can be reduced by 7.14%, which has good economic and environmental benefits. The popularization and application of this form of building system in cold regions has a high value.

Deployment of CO2 capture and storage in Europe under limited public acceptance—An energy system perspective

In this paper we analyse how in Europe large-scale deployment of CO2 capture and storage (CCS) technology may be hindered by limited public acceptance. We develop scenarios for how public acceptance may constrain the diffusion of CCS, either by reducing the overall amount of installable CCS capacity or by delaying its introduction, and show with an integrated assessment model how the type of limitation in CCS acceptance can critically impact the development of all sectors in the overall energy system over time. We also demonstrate that a reduction or delay in CCS diffusion as a result of critical public opinion can have substantial energy system impacts that differ across not only the nature of acceptance profile but also the sector(s) in which limited public acceptance materializes. Applying a constraint to CCS deployment in both industry and the power sector simultaneously leads to an energy system that is fundamentally different from the one that emerges if the constraint is only applied to the power sector. Depending on how and where CCS diffusion is constrained, net additional annual energy system costs in 2050 can vary between -50 billion up to nearly 800 billon $/yr.

Decarbonizing the electricity sector in Qatar using PV combined with ice thermal and battery storage

High daytime electricity demand from space cooling synergetic with predictable and reliable solar insolation creates a unique opportunity to exploit solar PV-enabled decarbonization solutions in Qatar. This paper examines the economic viability of combining utility-scale PV with ice thermal and battery storage to decarbonize the electricity sector in Qatar, which exclusively runs on gas generation. The problem is formulated in a two-stage stochastic linear programming that minimizes annual system costs at a given gas price. Under the current gas price of $3.3/MMBtu (gas-generated electricity at $37/MWh), PV and ice storage deployed in Qatar could reduce gas generation use and peak demand by 43% and 18%, respectively, and cut the annual system costs by 20%. At a gas price of $6.5/MMBtu (equivalent to carbon pricing at $60/ton of CO2), gas generation can be reduced by 60% using PV and ice storage. Reducing gas generation further is challenging since both cooling and non-cooling demands peak in August, whereas PV generation peaks in June, producing less surplus generation at a time of need, and ice thermal storage cannot cost-effectively outcompete already existing gas generations for highly seasonal cooling needs. Battery storage becomes cost-effective above a gas price of $9.2/MMBtu (equivalent to carbon pricing at $110/ton of CO2); it is primarily used to manage the diurnal behavior of non-cooling loads and could decarbonize the electricity sector by around 90%.

Scrutinizing the Intermittency of Renewable Energy in a Long-Term Planning Model via Combining Direct Integration and Soft-Linking Methods for Colombia’s Power System

The large-scale integration of variable renewable energy sources into the energy system presents techno–economic challenges. Long–term energy system optimization models fail to adequately capture these challenges because of the low temporal resolution of these tools. This limitation has often been addressed either by direct improvements within the long–term models or by coupling them to higher resolution power system models. In this study, a combined approach is proposed to capitalize on the advantages and overcome the disadvantages of both methods. First, the temporal resolution of an energy model was enhanced by approximating the joint probability of the electricity load and the supply of intermittent sources. Second, the projected electricity mix was simulated by a power model at an hourly resolution. This framework was used to analyze mid–century deep decarbonization trajectories for Colombia, subject to future uncertainties of hydroclimatic variability and the development of the bioeconomy. The direct integration method is found to consistently reduce the overestimation of the feasible penetration of VRES. However, its impact is marginal because of its inability to assess the short–term operation of the power system in detail. When combined with the soft–linking method, the reliable operation of the power system is shown to incur an additional overhead of 12–17% investment in flexible generation capacity, 2–5% of the annual energy system cost, and a 15–27% shortfall in achieving the aspired GHG mitigation target. The results obtained by combining both methods are found to be closer to the global optimum solution than using either of these methods individually.

Heat requirement in an indoor recirculating aquaculture system

Due to the benefits of the recirculating aquaculture system (RAS), many fish farmers are choosing this system. Some farmers chose indoor RAS, where fish tanks are kept inside buildings or greenhouses. Heating the buildings and the makeup water requires a substantial amount of energy since optimum growth temperatures exceed the normal temperature of supply water. In this paper three different heating systems are analyzed: ground source heat pump, natural gas boiler and wood pellet boiler. The annual running cost of the water heating system in both cases (with heat recovery and no heat recovery) is the lowest for the ground source heat pump, followed by the wood pellet boiler and the natural gas boiler.

A metaheuristic algorithm based on simulated annealing for optimal sizing and techno-economic analysis of PV systems with multi-type of battery energy storage

The battery energy storage unit is one of the main components of hybrid photovoltaic (PV)/battery systems to ensure the economy and reliability of the system to satisfy the electrical loads of green building, especially in remote areas. The main objective of this study is the establishment of a method for optimal design of PV arrangements based on multi-type of battery, in which the annual system cost (ASC) and the loss of load supply probability of the hybrid systems are simultaneously minimized. The hybrid method with simulated annealing and a harmony search methods is suggested in the sizing of the hybrid systems based on three types of energy storage which are lithium-ion, absorbed glass mat, and lead-acid. To calculate the future performance of the hybrid scheme, the effect of reliability index variations and the battery unit cost variations on the sizing problem, ASC, and also loss of power probability are calculated. The simulation results show that the battery storage level increases by increasing the ideal unite of PV and storage values to maintain the system reliability level. Also, it is found that an efficient battery type with the optimal size is techno-economically more beneficial, and leads to greater system reliability.

Modelling and multi-objective optimization of hybrid energy storage solution for photovoltaic powered off-grid net zero energy building

This paper investigates the modelling and multi-objective optimization (using Non-dominated Sorting Genetic Algorithm (NSGA-II)) of a photovoltaic-battery-hydrogen hybrid renewable energy system (HRES) for a net zero energy building (NZEB) that is a five-bedroom duplex detached residential house located in the heart of Lagos, Nigeria. Three battery technologies: lithium iron phosphate (LFP) battery, retired electric vehicle battery (REVB) and Ortsfest - stationary PanZerplatte - tubular plate Verschlossen - closed lead acid (OPzV) battery, were investigated for their economic viability. An in-house simplified degradation model was used to evaluate the capacity loss (as this can have significant impact on cost calculations if not done) of the batteries with cycling and calendar aging. This addresses the lack of implementation of battery degradation modelling by many authors optimizing for HRES due to inapplicability of the models in literature for different battery chemistries. Also, this work evaluated battery-fuel cell hybrid configurations on the three objectives: annualized cost of system (ACS), loss of power supply probability (LPSP) and potential energy waste probability (PEWP) and the results were contrasted with the battery only configurations to identify scenarios where hybrid energy storage system might be more economical. The results showed that LFP and REVB are the best battery options. LFP and REVB battery only configurations are better for LPSP constraints >1 % whereas for LPSP of 1 % and below LFP-hydrogen and REVB-hydrogen are more economical.

Sizing Assessment of Islanded Microgrids Considering Total Investment Cost and Tax Benefits in Colombia

This paper deals with the optimal sizing of islanded microgrids (MGs), which use diesel generators to supply energy in off-grid areas. The MG under study integrates photovoltaic (PV) and diesel generation, a battery energy storage System (BESS), and an inverter for the connection between AC and DC voltage buses. Levelised cost of energy (LCOE) and annual system cost (ASC) are considered economic indicators, while the loss of power supply probability (LPSP) is used as a reliability indicator. Fiscal incentives such as the tax benefits and accelerated depreciation applied in Colombia are considered for the optimally sizing of each MG element. Solar measurements were taken at a weather station located in the main campus of Universidad de Antioquia in Medellin, Colombia at a latitude of 6.10 and longitude of −75.38. The objective function is the minimization of the total energy delivered from the power sources that successfully meets the load. The model was implemented in Python programming language considering several scenarios. Two cases were evaluated: the first one considered PV panels, a BESS and a diesel generator, while the second one only considered PV panels and a BESS. The option that does not include the diesel generator turned out to be the most expensive, since additional PV and BESS resources are required to meet the load profile. Furthermore, it was found that the LCOE was lower when tax benefits were taken into account.

Optimal Allocation of BESS in Distribution Network Based on Improved Equilibrium Optimizer

The battery energy storage system (BESS) can accommodate the uncertainties of renewable energy sources (RESs) and load demand. Proper allocation of the BESS in the distribution network (DN) can bring cost-effectiveness and enhance system stability. To realize the reliable and economic operation of BESS in the DN, a multi-objective optimization model for optimal BESS allocation is established, which aims at minimizing the annual overall cost of the whole system, including life cycle cost (LCC), power loss cost, peak-shaving cost, tie-line fluctuation penalty, and voltage deviation penalty. Then, a novel implementation of the improved equilibrium optimizer (IEO) algorithm is proposed to solve the optimal BESS allocation scheme. In order to verify the effectiveness of the proposed method, the simulation experiment based on the IEEE 33-bus test system is performed. Simulation results prove that the IEO algorithm is capable of rapid stable convergence and efficient searching for optimum in the multidimensional space. By the end of the iteration, the annual overall cost of the whole system records a minimum value of $1.8692e+06 every year. A meticulous techno-economic analysis demonstrates that the obtained BESS allocation scheme not only effectively ensures cost-effectiveness of BESS but also significantly reduces power loss, load peak-valley difference, tie-line power fluctuation, and voltage deviation.

Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer

Hybrid renewable energy microgrid has become an attractive solution to electrify urban areas. This research proposes a microgrid design problem including photovoltaic (PV) arrays, wind turbine, diesel, and batteries for which Harris hawk optimization (HHO), a metaheuristic technique, is applied. Based on a long-term techno-economic assessment, the HHO approach is used to determine the best hybrid microgrid size for a community in Saudi Arabia’s northern region. The efficacy of HHO is investigated, and its performance was compared with seven metaheuristic techniques, grasshopper optimization algorithm (GOA), cuckoo search optimizer (CSO), genetic algorithm (GA), Big Bang–Big Crunch (BBBC), coyote optimizer, crow search, and butterfly optimization algorithm (BOA), to attain the HRE microgrid optimal sizing based on annualized system cost (ASC) reduction. Some benchmarks (optimum and worst solutions, mean, median, standard deviation, and rate of convergence) are used to distinguish and analyze the performance of these eight metaheuristic-based approaches. The HHO surpassed the other seven metaheuristic techniques in achieving the best HRE microgrid solution with the lowest ASC (USD 149229.9) followed by GOA (USD 149380.5) and CSO (USD 149382.5). The findings revealed that the HHO, GOA, CSO, and coyote have acceptable performance in terms of capturing the global solution and the speed of convergence, with only minimal oscillations. The BBBC, crow search, GA, and BA, on the other hand, have unacceptably poor performance, trapping to the local solution, oscillations, and a long convergence time. In terms of optimal solution and convergence rate, the BBBC and GA both perform poorly when compared to the other metaheuristic techniques.

Optimisation of the national grain reserve system using a two-phase algorithm

ABSTRACT The local grain reserve system is widely recognised as the key to ensure Chinese grain security in response to emergency events. Hence, the government should optimize the amounts and locations of grain reserves. Nevertheless, the grain supply process for emergencies is hard to be analytically model due to the complexity and uncertainty. In this paper, we propose an off-site storage structure to balance the high storage cost and the lack of storage capacity. Based on the off-site storage structure, we build a simulation model of the local grain reserve system and develop a systematic two-phase optimisation algorithm to achieve the optimal scheme. The numerical results show that the optimal off-site grain storage scheme can reduce the total annual operation cost of the entire system by 16%. Finally, other managerial suggestions are proposed for the government to build a more efficient local grain reserve system.

Leveraging renewable oversupply using a chance-constrained optimization approach for a sustainable datacenter and hydrogen refueling station: Case study of California

This work evaluates the sustainability of using curtailed renewable energy to power data centers and provide hydrogen to hydrogen refueling stations. An optimization problem is formulated to minimize the annual system costs for various case scenarios with a chance-constrained optimization approach to handle uncertainties. System components included natural-gas–powered combined cooling, heating, and power systems, electrolyzers, hydrogen fuel cells, heat pumps, hydrogen tanks, and battery energy storage systems. The results revealed that powering data centers with a mix of curtailed renewable energy and fossil fuels (Case 2) was the most economical option. Using only renewable sources (Case 3) allowed for a zero-emission alternative but was the most expensive; the data center powered by fossil fuels had 49,009 tons of annual CO2 emissions. From a sizing perspective, combined cooling, heating, and power systems dominated in Case 2, and for Case 3, a fuel cell was the major power source and a heat pump was the only cooling option. Sensitivity analysis demonstrated that the annual costs were most sensitive to the technology costs and may reduce capital expenditures in the near future. Overall, this work presents a comprehensive step toward economic and environmentally friendly data centers comprising both operator and investor perspectives.

Design optimization of a stand-alone green energy system of university campus based on Jaya-Harmony Search and Ant Colony Optimization algorithms approaches

The use of renewable energy resources in the production of electrical energy is becoming prevalent due to the decreasing installation costs of these resources and increasing environmental concerns. A Hybrid Renewable Energy System (HRES) is beneficial for meeting load demands, but optimal sizing is the main problem in the process of obtaining a cost-efficient system based on certain load demands and techno-economic parameters. In this article, the Harmony Search (HS) algorithm was used for the optimal sizing of components and compared to other methods. The HRESs consisted of photovoltaic (PV), wind turbine, battery, diesel generator and inverter components. A powerful rule-based energy management scheme was introduced to manage the power flow between system parts which constitute the microgrid that will minimize the annual system cost and reliably meet the energy demand. The decision variables for this optimization were the PV panel power, wind power, and the number of batteries. Simulation results revealed that HS provided the optimum sizing among the other methods including HOMER, Ant Colony Optimizer and Jaya. The time performances of the algorithms were also examined, and the HS algorithm had better performance and convergence properties. The optimization process was programmed using the MATLAB simulation package.

Optimal Design of a Distributed Ship Power System with Solid Oxide Fuel Cells under the Consideration of Component Malfunctions

In the shipping industry, solid oxide fuel cells (SOFCs) are a much-discussed technology due to their high energy efficiency, fuel versatility, and emissions reduction potential. In contrast to internal combustion engines, modular SOFC units allow for distributed system configurations without drastically reducing the overall efficiency. Decentralizing the power system with regard to the electrical consumers’ demands reduces both grid size and transmission losses, leading to a reduction of investment and operating costs. Additionally, a modular approach significantly benefits required redundancy aspects. A case study based on a cruise ship with nine fire zones is used to quantify the advantages of a distributed approach from an economic point of view. For this, a design optimization with variable installation location is conducted both with and without component failure considerations. Compared to a central configuration, annual transmission system costs in a distributed approach are reduced by 76% without and 55% with component failure consideration. However, the cost reduction potential proves to be small compared to other matters of expense. The modular system characteristic ensures that minor modifications suffice for component redundancy, resulting in an investment cost increase of less than 2% for both central and distributed configurations.

Analyzing Intersectoral Benefits of District Heating in an Integrated Generation and Transmission Expansion Planning Model

In the field of sector integration, the expansion of district heating (DH) is traditionally discussed with regard to the efficient integration of renewable energy sources (RES) and excess heat. But does DH exclusively benefit from other sectors or does it offer advantages in return? So far, studies have investigated DH only as a closed system or determined intersectoral benefits in a highly aggregated approach. We use and expand an integrated generation and transmission expansion planning model to analyze how the flexibility of DH benefits the energy system and the power transmission grid in particular. First of all, the results confirm former investigations that show DH can be used for efficient RES integration. Total annual system cost can be decreased by expanding DH, due to low investment cost and added flexibility, especially from large-scale heat storage. The high short-term efficiency of heat storage—in combination with electric heating technologies—can be exploited to shift heat demand temporally and, using multiple distributed units, locally to solve electric grid congestion. Although it is unclear whether these results can be replicated in the real world, due to the aggregation and detail of the model, further research in this direction is justified.