As the use of sewage sludge as a fertilizer in agriculture is increasingly restricted in the European Union, other ways to utilize this waste stream need to be developed. Sewage sludge is an ideal input material for the process of hydrothermal carbonization, as it can convert wet biomass into a solid energy carrier with increased mechanical dewaterability. Digested sewage sludge was hydrothermally carbonized at 160−200 °C for 30−60 min with initial pH levels of 1.93−8.08 to determine optimal reaction conditions for enhanced dewaterability and phosphorus release into the liquid phase. Design of experiments was used to develop response surface models, which can be applied to optimize the process conditions. For optimal dewaterability and phosphorus release, low initial pH values (pH 1.93) and mild temperatures around 170 °C are favorable. Because holding time had no statistically relevant effect, a dependency of reaction time was investigated. Though it did not yield substantially differ... [more]

Setting reasonable circuit parameters is an important way to improve the quality of inverters, including waveform quality and power loss. In this paper, a circuit system of line voltage cascaded quasi-Z-source inverter (LVC-qZSI) is built. On this basis, the double frequency voltage ripple ratio and power loss ratio are selected as optimization targets to establish a multi-objective optimization model of LVC-qZSI parameters. To simplify the calculation, an integration optimization strategy of LVC-qZSI parameters based on GRA-FA is proposed. Where, the grey relation analysis (GRA) is used to simplify the multi-objective optimization model. In GRA, the main influence factors are selected as optimization variables by considering the preference coefficient. Then, firefly algorithm (FA) is used to obtain the optimal solution of the multi-objective optimization model. In FA, the weights of objective functions are assigned based on the principle of information entropy. The analysis results ar... [more]

The goal of this work is to compute the eco-driving cycles for vehicles equipped with internal combustion engines by using a genetic algorithm (GA) with a focus on reducing energy consumption. The proposed GA-based optimization method uses an optimal control problem (OCP), which is framed considering both fuel consumption and driver comfort in the cost function formulation with the support of a tunable weight factor to enhance the overall performance of the algorithm. The results and functioning of the optimization algorithm are analyzed with several widely used standard driving cycles and a simulated real-world driving cycle. For the selected optimal weight factor, the simulation results show that an average reduction of eight percent in fuel consumption is achieved. The results of parallelization in computing the cost function indicates that the computational time required by the optimization algorithm is reduced based on the hardware used.

A key challenge for future energy systems is how to minimize the effects of employing demand response (DR) programs on the consumer. There exists a diverse range of consumers with a variety of types of loads, such as must-run loads, and this can reduce the impact of consumer participation in DR programs. Multi-energy systems (MES) can solve this issue and have the capability to reduce any discomfort faced by all types of consumers who are willing to participate in the DRPs. In this paper, the most recent implementations of DR frameworks in the MESs are comprehensively reviewed. The DR modelling approach in such energy systems is investigated and the main contributions of each of these works are included. Notably, the amount of research in MES has rapidly increased in recent years. The majority of the reviewed works consider power, heat and gas systems within the MES. Over three-quarters of the papers investigated consider some form of energy storage system, which shows how important ha... [more]

The partial shading of photovoltaic (PV) modules due to clouds or blocking objects, such as buildings or tree leaves, is a common problem for photovoltaic systems. To address this, maximum power point tracking (MPPT) is implemented to find the global maximum power point (GMPP). In this paper, a new hybrid MPPT is proposed that combines a modified grasshopper optimization algorithm (GOA) with incremental conductance (IC). In the first stage, the proposed modified GOA is implemented to find a suitable tracking area where the GMPP is located. Then the system moves to the second stage by implementing IC to get the correct GMPP. IC is a fast-performing and reliable algorithm. By combining GOA and IC, the proposed method can find the GMPP accurately with a short tracking time. Various experimental results show that the proposed method yields the highest tracking efficiency and lowest tracking time compared to some of the state-of-the-art MPPT algorithms, such as particle swarm and modified f... [more]

The economic emission dispatch (EED) is a highly constrained nonlinear multiobjective optimization problem with a convex (or nonconvex) solution space. These characteristics and constraints make the EED a difficult problem to solve. Several approaches for a solution have been proposed, such as deterministic techniques, stochastic techniques, or a combination of both. This work presents the use of an algebraic (deterministic) technique, the numerical polynomial homotopy continuation (NPHC) method, to solve the EED problem. A comparison with the sequential quadratic programming (SQP) algorithm and the nondominated sorting genetic algorithm II (NSGA-II) is also presented. Results show that the NPHC algorithm finds all the roots (solutions) of the problem starting from any initial point and assures an accurate solution with a good convergence time. In addition, the NPHC algorithm provides a more accurate solution than the SQP algorithm and the NSGA-II.

In this paper, a multi-objective hybrid firefly and particle swarm optimization (MOHFPSO) was proposed for different multi-objective optimal power flow (MOOPF) problems. Optimal power flow (OPF) was formulated as a non-linear problem with various objectives and constraints. Pareto optimal front was obtained by using non-dominated sorting and crowding distance methods. Finally, an optimal compromised solution was selected from the Pareto optimal set by applying an ideal distance minimization method. The efficiency of the proposed MOHFPSO technique was tested on standard IEEE 30-bus and IEEE 57-bus test systems with various conflicting objectives. Simulation results were also compared with non-dominated sorting based multi-objective particle swarm optimization (MOPSO) and different optimization algorithms reported in the current literature. The achieved results revealed the potential of the proposed algorithm for MOOPF problems.

The lack of electricity access is increasingly concentrated in rural areas of developing countries, in which mini-grids are often a suitable solution; however, given the high risks, it is crucial to minimize costs. This paper aims at analyzing existing methodologies for the optimal design of mini-grids combined with different operating strategies. Typical system operations, like the load-following (LFS) and cycle charging (CCS) strategies, are compared with the more demanding predictive strategies based on Mixed-Integer Linear Programming (MILP). The problem is formulated and solved with Particle Swarm Optimization (PSO), so to simulate traditional and predictive operating strategies. Two reformulations based on the proposed Search Space Update are also detailed and compared with the so-called one-shot MILP model, which is able to con-jointly optimize both the design and the operation of the system, in order to reduce computational requirements with the predictive strategy. The results... [more]

Optimization of heat transfer systems (HTSs) benefits energy efficiency. However, current optimization studies mainly focus on the improvement of system design, component design, and local process intensification separately, which may miss the optimal results and lack reliability. This work proposes a synergetic optimization method integrating levels of the local process, component to system, which could guarantee the reliability of results. The system-level optimization employs the heat current method and hydraulic analysis, the component level optimization adopts heuristic optimization algorithm, and the process level optimization applies the field synergy principle. The introduction of numerical simulation and iteration provides the self-consistency and credibility of results. Optimization results of a multi-loop heat transfer system present that the proposed method can save 16.3% pumping power consumption comparing to results only considering system and process level optimization.... [more]

Combined heat and power (CHP) in a single and integrated device is concurrent or synchronized production of many sources of usable power, typically electric, as well as thermal. Integrating combined heat and power systems in today’s energy market will address energy scarcity, global warming, as well as energy-saving problems. This review highlights the system design for fuel cell CHP technologies. Key among the components discussed was the type of fuel cell stack capable of generating the maximum performance of the entire system. The type of fuel processor used was also noted to influence the systemic performance coupled with its longevity. Other components equally discussed was the power electronics. The thermal and water management was also noted to have an effect on the overall efficiency of the system. Carbon dioxide emission reduction, reduction of electricity cost and grid independence, were some notable advantages associated with fueling cell combined heat and power systems. Des... [more]

The adoption of Electric Vehicles (EVs) will revolutionize the storage capacity in the power system and, therefore, will contribute to mitigate the uncertainty of renewable generation. In addition, EVs have fast response capabilities and are suitable for frequency regulation, which is essential for the proliferation of intermittent renewable sources. To this end, EV aggregators will arise as a market representative party on behalf of EVs. Thus, this player will be responsible for supplying the power needed to charge EVs, as well as offering their flexibility to support the system. The main goal of EV aggregators is to manage the potential participation of EVs in the reserve market, accounting for their charging and travel needs. This work follows this trend by conceiving a chance-constrained model able to optimize EVs participation in the reserve market, taking into account the uncertain behavior of EVs and their charging needs. The proposed model, includes penalties in the event of a... [more]

A model has been developed for the optimization of the share structure of an investment portfolio in high-tech projects supported by the leaders of the leading industry companies in Russia. Several indicators (financial leverage, integrated rating of companies, industry rating) were applied in the decision support system for the shared distribution of investments. High-tech production is based on innovative technologies for saving resources, the resiliency of systems for transporting and transferring raw materials and finished products within Russia, so the main income will remain within the country. It is possible to export high-tech products, rather than raw materials, which will increase export revenues. Investors will invest in high-tech projects of Russian companies, taking into account the targeting of investment development. The guarantee is the stable financial position of the companies and the competitiveness rating. Methods: The authors propose a new approach that does not co... [more]

Electromagnetic design problems are generally formulated as nonlinear programming problems with multimodal objective functions and continuous variables. These can be solved by either a deterministic or a stochastic optimization algorithm. Recently, many intelligent optimization algorithms, such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC), have been proposed and applied to electromagnetic design problems with promising results. However, there is no universal algorithm which can be used to solve engineering design problems. In this paper, a stochastic smart quantum particle swarm optimization (SQPSO) algorithm is introduced. In the proposed SQPSO, to tackle the premature convergence problem in order to improve the global search ability, a smart particle and a memory archive are adopted instead of mutation operations. Moreover, to enhance the exploration searching ability, a new set of random numbers and control parameters are introduced. E... [more]

The present trend of aerospace industries is being shifted towards a “More Electric Aircraft” system which needs to be high power dense. For this purpose, the integration technologies have gained massive interest, providing the benefits of reduced losses, weight, volume and cost. In this article, the integration concept of a passive filter inductor is presented for a permanent magnet synchronous motor. The integrated motor eliminates the need of an external inductor, thus, eliminates the added inductor losses, mass, volume and cost associated with it. The motor utilizes its’s inherent inductance to use it as a filter inductor instead of implementing a discrete inductor that is commonly placed between inverter and the motor terminals. Optimization study is carried out, where the filter branch windings are tapped, in terms of improving mass and volume and performance parameters such as power losses and torque ripple. From the optimization study, the motor with minimum weight and volume i... [more]

Energy costs account for a significant proportion of total costs in production systems. Since energy is becoming an increasingly expensive resource, therefore, it is critical to consume it as efficiently as possible. Focusing on energy efficiency is also important in terms of reducing greenhouse gas (GHG) emissions and the effects of other pollutants on the environment. One of the possible ways for businesses to reduce energy consumption is to use available transportation means as efficiently as possible. In the operational phase, this can be achieved by reducing unnecessary transport, selecting the most efficient delivery routes, and by optimized assignment of available vehicles to transportation orders. We present in this article a novel dynamic assignment of transportation orders to fleet with energy minimization criterion in internal transport system of a printing company. The novelty of the proposed model is that, in contrast to most existing models, it can handle a heterogeneous... [more]

This paper proposes an original multi-criteria decision-making optimization algorithm to select the best solar panels in an existing market and optimally size the photovoltaic (PV) system for an electric vehicle parking lot (EVPL). Our proposed algorithm is called rank-weigh-rank (RWR), and it is compared to the well-known technique for order of preference by similarity to ideal solution (TOPSIS) optimization algorithm under the same conditions for validation purposes. Results show that the speed of our proposed algorithm (RWR) in finding the best solution increases exponentially compared to TOPSIS when the numbers of alternatives and criteria increase. Moreover, 77% is the probability of obtaining results with more than 80% accuracy compared to TOPSIS, which validates the efficiency of our algorithm. In addition, we were able to design an EVPL with a power self-sufficiency ratio of 60.8%, the energy self-sufficiency ratio of 74.7%, and a payback period of 10.58 years. Moreover, the re... [more]

Solar Photovoltaics (PV) is seen as one of the renewable energy technologies that could help reduce the world’s dependence on fossil fuels. However, since it is dependent on the sun, it can only generate electricity in the daytime, and this restriction is exacerbated in electricity grids with high PV penetration, where solar energy must be curtailed due to the mismatch between supply and demand. This study conducts a techno-economic analysis to present the cost-optimal storage growth trajectory that could support the dynamic integration of solar PV within a planning horizon. A methodology for cost-optimal assessment that incorporates hourly simulation, Monte Carlo random sampling, and a proposed financial assessment is presented. This approach was tested in Japan’s southernmost region since it is continuously increasing its solar capacity and is at the precipice of high PV curtailment scenario. The results show the existence of a cost-optimal storage capacity growth trajectory that bal... [more]

Required refrigerant charge in heat pump systems with propane is analyzed. Two systems are compared: the first a direct heat pump, with fin-and-tube heat exchangers, and the second an indirect system, with plate heat exchangers with an additional brine-to-air heat exchanger. Each system was considered to be able to work reversibly, with 5 kW design cooling capacity in summer and 8 kW design heating capacity in winter. Two separately developed simulation codes were used to calculate the required refrigerant charge and the efficiency of each of the systems. The charge was reduced by the use of microfinned tubes up to 22% in direct system reduced using microfinned tubes compared to the smooth tube. For the indirect system using specially designed plate heat exchangers with the minimum internal volume, their charge was reduced by up to 66% compared to normal plate heat exchangers.

This paper contains the basic definition and application of the physical optimum as a method for process evaluation and optimization. By means of the exemplary balance of a wood pellet-fired boiler, the conventional efficiency is compared to the PhO. Furthermore, this study demonstrates the possibility of applying the thermodynamic state variable exergy as a physical reference property of a system within the PhO method. To explain the approach, the heat generation in the wood pellet-fired boiler is compared to the supply from a heat pump, which itself is connected to a power plant. Furthermore, the process-independent PhO is explained in order to illustrate the limitations of feasible optimization. Additionally, possible research topics such as the integration of dynamic behavior in the method are approached. As a conclusion, the differences between the methods outline the advantage of the PhO in the optimization process.

Integrals that are of interest in the analysis, design, and optimization of concentrating solar thermal systems (CST), such as the annual optical efficiency of the light collection and concentration (LCC) subsystem, can be accurately computed or estimated in two distinct ways: on the time domain and on the spatial domain. This article explores these two ways, using a case study that is highly representative of the commercial CST systems being deployed worldwide. In the time domain, the computation of these integrals are explored using 1-min, 10-min, and 1-h solar DNI input data and using The Cyprus Institute (CyI)’s High-Performance Computing (HPC) system and an open-source ray tracer, Tonatiuh++, being actively developed at CyI. In the spatial domain, the computation of these integrals is explored using SunPATH, another open-source software tool being actively developed at CyI, in tandem with Tonatiuh++. The comparison between the time and spatial domain approach clearly indicate that... [more]

There is a necessity to design a three-phase squirrel cage induction motor (SCIM) for high-speed applications with a larger air gap length in order to limit the distortion of air gap flux density, the thermal expansion of stator and rotor teeth, centrifugal forces, and the magnetic pull. To that effect, a larger air gap length lowers the power factor, efficiency, and torque density of a three-phase SCIM. This should inform motor design engineers to take special care during the design process of a three-phase SCIM by selecting an air gap length that will provide optimal performance. This paper presents an approach that would assist with the selection of an optimal air gap length (OAL) and optimal capacitive auxiliary stator winding (OCASW) configuration for a high torque per ampere (TPA) three-phase SCIM. A genetic algorithm (GA) assisted by finite element analysis (FEA) is used in the design process to determine the OAL and OCASW required to obtain a high torque per ampere without comp... [more]

These days, seamless moving about a city is a determinant of the city’s competitiveness, and is decisive for the life quality in the city. Hence, taking care of appropriate traffic organisation is one of the major tasks of the city authorities. Development of optimal production and spatial interrelations, considering their costs, efficiency and scope of services rendered to individual entities, enables economic and ecological development of the region. Therefore, the issue of major importance for a city is implementing a transport policy that makes it possible to choose a specified method of development (transformation) of the existing transport system in such a way so that it is coherent with the adopted strategy for the city development. The purpose of a transport policy conducted by city authorities should be maintaining the functioning of the urban transport on at least a satisfactory level. The main purpose of the article is to present an innovative solution for optimising the jou... [more]

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against... [more]

This manuscript develops a workflow, driven by data analytics algorithms, to support the optimization of the economic performance of an Integrated Energy System. The goal is to determine the optimum mix of capacities from a set of different energy producers (e.g., nuclear, gas, wind and solar). A stochastic-based optimizer is employed, based on Gaussian Process Modeling, which requires numerous samples for its training. Each sample represents a time series describing the demand, load, or other operational and economic profiles for various types of energy producers. These samples are synthetically generated using a reduced order modeling algorithm that reads a limited set of historical data, such as demand and load data from past years. Numerous data analysis methods are employed to construct the reduced order models, including, for example, the Auto Regressive Moving Average, Fourier series decomposition, and the peak detection algorithm. All these algorithms are designed to detrend th... [more]

In this paper, a thorough framework for multiobjective design optimization of switched reluctance motor (SRM) is proposed. Selection of stator and rotor pole embrace coefficients is an essential step in the SRM design process since it influences torque output and torque ripple in SRM. The problem of determining optimal pole embrace is formulated as a multi-objective optimization problem with the objective of optimizing average torque, efficiency and torque ripple, and response surface models were obtained based on the genetic aggregation method. The results obtained by genetic aggregation response surface (GARS) and the non-dominated genetic algorithm (NSGA-II) were validated with the finite element method (FEM) model of the initial SRM. The optimized model displayed better efficiency profile over a wide speed range. The initial and optimized models recorded maximum efficiencies of 85% and 94.05%, respectively, at 2000 rpm. The efficiency values of 93.97−94.05% were achieved for the th... [more]