Journal of Energy Engineering

An increased penetration of wind energy into the power system will lead to instability of local voltage and global frequency in Japan. Power flow simulation is a powerful tool for understanding the electrical behavior in the power system caused by wind energy; however, plausible and various wind power profiles are required to perform a meaningful simulation to evaluate the effect of wind generators. This paper proposes a procedure of generating synthetic wind power profiles that involve the plausible short-term fluctuation for a power flow simulation based on the spatial kriging method and the bootstrap method.

To reduce greenhouse gases, the high penetration of photovoltaic (PV) generation has been greatly anticipated in Japan. However, local distribution networks face voltage-rise problems when numerous PV systems are connected. In particular, rooftop-type PVs on detached houses can be widely installed in Japan. In that case, the voltage rise in low-voltage wires or service wires is significant because of the high resistance of these wires. In terms of network operators, spatial distribution scenarios for PV installation cannot be prespecified because each PV installation is determined by the particular customer. This paper evaluates PV-installable capacity from a systematic perspective under voltage constraints in medium- and low-voltage networks with a consideration of voltage control equipment [under-load tap changer (ULTC) and step voltage regulator (SVR)]. Through the use of optimal parameters for ULTC and SVR, PV-installable capacity can be improved. In particular, PV-installable capacity around the end of a feeder can be significantly increased by installing a SVR. In addition, this paper analyzes the effect of load sharing of pole transformers for reducing voltage rise in terms of PV-installable capacity to compare with an installation of a SVR. Through numerical simulations, the SVR is shown to be more advantageous than the load sharing of pole transformers for increasing PV-installable capacity.

This paper proposes a voltage control method during service restoration in the distribution networks with photovoltaic (PV) generator systems. In the current distribution automation system (DAS) process in Japan, voltage dips and surges occur during service restoration because PVs are disconnected simultaneously after a fault and subsequently reconnected after service restoration. However, in the current DAS, voltage regulators such as an on-load tap changer (OLTC) and step voltage regulators (SVRs) are not controlled during service restoration. The proposed DAS estimates the voltage in a distribution network during service restoration, and it controls the tap position of OLTC and/or SVRs according to the predicted voltage. The numerical simulation results using a real-world distribution system model on a real map and PV output profiles derived by actual square kilometer solar radiation data will be shown. Those results indicate that the proposed DAS prevents voltage deviation that occurs as long as the current DAS is used. The results also show high spatial resolution PV output data are needed to prevent voltage deviation absolutely.

After the Fukushima nuclear accident, nuclear policy has become uncertain in Japan, and alternatively, variable renewable (VR) energy, such as wind and photovoltaic (PV), is highlighted for addressing climate change and energy security issues. This paper attempts to assess the massive integration of VR into Japan’s long-term power-generation mix, employing the dynamic multiregional optimal power-generation mix model, which is a large-scale linear programming model including 200 million constraints. The feature of the model enables explicit consideration of the actual variability of wind and PV outputs in a 10-min temporal resolution and to analyze the impact of those variabilities on long-term expansion planning of power plants. Simulation results show that both nuclear decommission and carbon regulation policies make VR economically justified and encourage its expansion in Japan’s long-term power-generation mix. When nuclear is totally decommissioned and ${\mathrm{CO}}_2$ is mitigated by 50% from 2010 levels by 2050, the power-generation cost in 2050 shows a doubling compared with that in the scenario where nuclear power is not decommissioned and carbon regulation is not assigned.

Distributed energy systems such as solar power photovoltaics (PV) and cogeneration systems (CGS) are expected to play a main role in future energy systems. However, consumers employ these distributed energy systems based on individual decisions rather than top-down installation planning, so even if the expansion of PV and other renewable energy sources is a national energy policy, it remains uncertain how and when PV installation targets will be realized. Furthermore, when consumers extensively deploy distributed energy systems, the power-expansion planning of utilities will be affected by changes in daily load patterns. In this paper, the authors develop a two-stage model focusing on interactions between the energy system adoption behavior of customers and power-expansion planning of a utility. In the first stage, the authors disaggregate Japan’s Kanto region into 38 areas and then develop an optimum energy system model including PV and CGS for consumers. In the second stage, the demand for electric power from the utility is transferred to the power-expansion planning model of the Tokyo Electric Power Company. The authors observe how well the results for PV penetration agree with the cost and the market projection scenarios given by governmental plans. The effects of subsidy scenarios for PV are also evaluated. The authors find that PV penetration will not meet installation targets unless additional PV promotion policies are implemented. The power-expansion model in Stage 2 shows how consumer behavior affects long-term expansion. These findings suggest the need for an integrated energy policy promoting a low-carbon society.

This paper presents a geographic information-based mixed integer linear programming model for a district heating system design. The model minimizes the annualized investment and operation costs of the system, with the key results showing the optimal distribution network structure and optimal capacity and dispatch of heat plants. A network topology of nodes and edges, providing accurate geographic representation of the district, is generated using a geographic information system and acts as a constraint. A case study is conducted for a district in Hirosaki city, located in the northernmost prefecture of mainland Japan. The results demonstrate the considerable economic benefits of integrating locally available woodchips in heat-only boilers instead of using city gas due to lower fuel costs. Low temperature operation reduces the fuel costs due to less network heat loss compared to medium temperature operation, but it is overcome by the cost of the larger pipe size and the pumping power. Implementation of the district heating system to the case area encourages sustainable development through economic favorability, decreased primary energy consumption, and considerable ${\mathrm{CO}}_2$ emissions reduction, compared to the current heat supply structure.

As environmental issues become more prominent, electric vehicles (EV) have attracted an increasing amount of attention. However, the continuous cruising distance of an EV is limited to approximately 160 km, which is insufficient for everyday use. Battery capacity is the limiting factor in long-distance EV travel, because the vehicles need to stop at EV recharging stations multiple times. In Japan, there are more than 2,000 EV charge stations, but there are, at most, two rapid chargers. When multiple users converge at the station, a queuing (or waiting) condition is created, which may lead to a call-loss condition. In other words, an appropriate number of chargers must be installed at each station when planning the EV infrastructure. Therefore, the number of vehicles entering the station must be estimated. In this study, a mathematical model based on the supporting infrastructure for widespread EV use is proposed to estimate the number of vehicles arriving at each charge station.

To increase the convenience of electric vehicles under current technological situations, fast battery chargers should be densely installed so that the driving distances and durations of electric vehicles are not excessively longer than those of gasoline vehicles. A driving simulator is developed to determine driving routes of electric vehicles and evaluate the corresponding driving distances and numbers of charges in case electric vehicles run by charging their batteries using fast battery chargers. Methods using adjacent and distance matrices based on the graph theory and dynamic programming are proposed to search the optimal driving route with the minimum number of battery charges and the minimum driving distance, respectively, in a rational, systematic, and efficient manner. Through a fundamental analysis using the line distance model, the driving distances and the energy consumption of electric vehicles are clarified in relation to the distance between fast battery chargers. Through a practical analysis using an approximate road distance model with Osaka Prefecture, Japan, selected as the target area, it is clarified how the allocation of existing and additional fast battery chargers affects the driving distances and the energy consumption of electric vehicles and the utilization of the chargers.

It is crucial for the Japanese government to establish a new energy mix plan since the previous plan was subject to review after the Fukushima nuclear accident in March 2011. The Japanese government proposed a new energy mix option in June 2015. However, the high degree of uncertainty will impair the robustness of energy mix options decided based on predictions. This paper uses robust decision making (RDM) to take uncertainty into account and determine robust energy mix options. An hourly electricity dispatch and power plant renewal simulation covering 2016–2035 in Japan is conducted to analyze the economic and environmental impacts of several energy mix options. The results show that the options with greater use of coal-fired and wind power plants have robustness against future uncertainties and that the current government plan is inefficient.

In recent decades, climate change and resource limitations have become serious problems. To overcome these problems, many countries promote the introduction of renewable energy. However, the diffusion of renewable energy requires a novel supply and demand system for electricity. One remarkable method of controlling electricity demand is a demand-side control based on dynamic pricing. This study analyzes electricity consumption behavior using laboratory experiments. In particular, the authors focus on the effect of supply limitations on consumption behavior. The results of the experiment include significant findings that help provide an understanding of electricity consumption behavior. More specifically, the announcement of a supply limitation affects the decision to consume electricity. Results of this study indicate that cooperative people tend to decrease electricity consumption more when they are aware of the possibility of an electrical outage. This finding implies that researchers need a better understanding of the psychological aspects of electricity consumption behavior.

With smart grid, the power supply will shift from the $1:N$ tree structure with centralized power plants to the $M:N$ structure with various kinds of distributed energy resources based on renewable energy, batteries, and so on. Deregulation of the electricity market will yield a truly competitive market, where anyone can become a power seller or buyer, which will necessitate a real-time multiseller–multibuyer power trading system. However, it is difficult to realize such a system without centralized control, because of the additional trade complexity created by a large number of sellers, including ordinary homes. In this paper, the authors propose a novel distributed power cooperation algorithm that maximizes each home’s welfare based on local information. The proposed algorithm enables each home to calculate the same electricity market price from only local household information, to trade, and to maximize all members’ satisfaction in smart grid by balancing consumption against supply. The authors formulate a distributed optimization problem and logically prove that the authors’ algorithm can obtain the same optimal user welfare as the global optimal approach but within a much shorter time.

This paper aims to apply a multiobjective optimization modeling technique to a power expansion problem evaluating two objectives functions: minimizing the power generating cost and minimizing ${\mathrm{CO}}_2$ emissions, between which there is a tradeoff. A convex curve is obtained representing the relationship between the generating cost ($\mathrm{Rp}/\mathrm{kWh}$) and ${\mathrm{CO}}_2$ emissions (ton). This represents a bad-luck curve where there is an increasing marginal cost to reduce 1 t of ${\mathrm{CO}}_2$ emissions. This is because most of the less-carbon-intensive power plants consume oil, which has the highest fuel cost. Instead of simply minimizing ${\mathrm{CO}}_2$ emissions, this paper argues that Indonesia needs to pursue technology to switch from steam coal subcritical technology to supercritical and ultra-supercritical technology to reduce ${\mathrm{CO}}_2$ emissions. It is further found that the generating cost will increase by less than 1.6% and yearly ${\mathrm{CO}}_2$ emissions can be reduced by about 6.9% by adopting supercritical technology. This implies that adopting ultra-supercritical technology can cut ${\mathrm{CO}}_2$ emissions by more than half. A squeezing effect is also found by adopting more-advanced steam coal technology. Thus, promoting renewable energy and gas utilization also should be enhanced. The green path power system allows both ${\mathrm{CO}}_2$ emissions and the generating cost to increase gradually, but with lower ${\mathrm{CO}}_2$ emissions than by minimizing the generating cost alone. It is thereby proposed that the current feed-in tariff for renewable energy also needs to be supported with an emissions reduction target.

Large amounts of low-temperature and medium-temperature waste heat are produced and often go unused in the petrochemical industry. Low-temperature power generation technology is considered an important solution for waste heat recovery. This paper presents a feasibility analysis for a low-temperature power generation system (LTPGS) based on the organic Rankine cycle (ORC). The paper begins with an introduction to the ORC and makes contrastive analyses of six candidate working fluids, leading to the selection of TY-1 as the best fluid. Secondly, experimental research was used to obtain the relationships between the system parameters. Thirdly, based on long-term experimental data and experiences in engineering applications, the LTPGS was designed taking into account the chemical process. The process of purified wastewater has been taken as a case to subject to feasibility analysis about economic and environmental benefits. The results show that the LTPGS power-generating efficiency is 8.4% in winter and 6.5% in summer, and that the dynamic payback period of the system is 3.8 years. The environment loads of the system decrease significantly compared with traditional thermal power generation. The efficiency of the overall utilization of energy can be improved considerably and the methods of analysis and optimization presented can be widely applied in similar waste heat recovery situations in the petrochemical industry.

Numerical simulations and industrial experiments were conducted to study the effect of the stoichiometric ratio of the fuel-rich flow (0.46, 0.49, 0.51, 0.53, and 0.55) on the flow, combustion, and ${\mathrm{NO}}_x$ emission characteristics in a 600-megawatt electric (${\mathrm{MW}}_e$) supercritical down-fired boiler with multiple-injection and multiple-staging combustion technology. The simulation results indicate that as the stoichiometric ratio of the fuel-rich flow increases from 0.46 to 0.55, the flow fields all form a symmetric W-shaped pattern; this is identical to the symmetric temperature distributions obtained experimentally. The ability of downward coal/air flows to entrain high-temperature gases from the recirculation zone weakens, and the airflow declination angle in tertiary-air regions and the downward flame penetration depth decrease. Coal burnout is enhanced. The temperature in the lower furnace rises, the high-temperature ($\ge \mathrm{1,700}\mathrm{K}$) area gradually increases from 64 to $120{\mathrm{m}}^2$, the carbon in the fly ash at the furnace exit decreases from 9.41 to 4.23%, and ${\mathrm{NO}}_x$ emissions increase from 860 to $\mathrm{1,045}\mathrm{mg}/{\mathrm{m}}^3$ at 6% ${\mathrm{O}}_2$.

Compound parabolic concentrators (CPCs) are technologies that allow heat exchange between solar radiation and a fluid. Incorporation of a concentric tube receiver has been proposed as a means of improving the performance of CPCs. Such geometry has been used to improve the processes of heat transfer in refrigeration tubes. Here, the authors report mathematical modeling, simulation, design, and construction of four CPCs with concentric tube receivers, as well as experimental study. The study begins with the proposal of a mathematical model based on heat transfer equations, as reported in the literature. Subsequently, the authors designed and built a test bank consisting of four CPCs. The test bank can be operated with the four CPCs, working as either a serial or parallel flow. Based on experimental results, it was possible to obtain the characteristic curves of the solar collector operating in both modes. After validating the mathematical model with the experimental results, a correlation to adjust the simulator removal factor of the CPCs with concentric tubes was added. This setting improved the simulator results by 68%. Once validated, the simulator was used to compare the performance of a concentric tube and a simple receiver tube. The results show that the concentric receiver tube outperforms the simple receiver tube.

Electrostatic charging has the potential to enhance droplet evaporation in liquid-fueled combustion applications. Based on well-established experimental evidence, it is known that as an electrostatically charged droplet evaporates and approaches the Rayleigh limit, it fragments into a residual droplet and a number of other sibling droplets. This process can reduce the total vaporization time. In the context of combustion, the produced sibling droplets will burn, reducing the vaporization time of the charged residual due to heat release; however, this process has not been studied in the literature. In this paper, a traditional droplet-evaporation model is extended to account for the influence of reacting sibling droplets on the vaporization and electrostatic atomization of an electrified residual droplet. The single-droplet modeling approach with and without charge is initially validated against existent experimental data and is in excellent agreement with published results. The sensitivity of the model that accounts for burning sibling droplets is subsequently assessed with respect to key parameters of experimental relevance. These include the number of siblings $n$, initial droplet charge with respect to the Rayleigh limit $Q_0/Q_{\mathrm{ray}}$, and residual droplet charge with respect to the primary droplet charge $Q_1/Q_0$, as well as the Reynolds number. This simple yet new approach highlighted here sheds light on the relevance of different electrostatic and physical parameters on the modeling of electrostatically charged droplet evaporation in reacting and nonreacting settings.

In the current study, a commercial diesel fuel was redistilled and four fuels with different distillation temperatures were obtained. The effects of fuels with different distillation temperatures on combustion, performance, and emissions were investigated on a heavy-duty diesel engine. The measured fuel properties show that with the increase of distillation temperature, aromatics content, viscosity, cetane number and density show an increasing tendency, whereas the low heating values remain almost the same. The results at full load condition indicate that fuel with lower volatility presents lower torque output because of the lower density and consequent lower heat value in volume. The effects of distillation temperature rely on the operating conditions. At low load (1,200 rpm, 25% load), fuel with lower distillation temperature usually exhibits longer ignition delay and higher burning rate for the lower cetane number and higher volatility, and shows higher fuel consumption because of the delayed combustion. Regarding emissions, fuel with lower distillation temperature presents lower soot emissions but ${\mathrm{NO}}_x$, HC, and CO emissions are higher than fuel with higher distillation temperature. At high engine load (1,200 rpm, 75% load), the differences in fuel consumption and emissions become very small for different fuels, although there are obvious differences in cetane number and volatility for four tested fuels. The increase of injection pressure can lead to an obvious decrease in ignition delay and higher heat-release rate (HRR) at the low load condition, and fuel consumption can be improved for the advance of combustion, especially for retarded injection timings. In terms of emissions, although higher injection pressure results in some increase in ${\mathrm{NO}}_x$ emissions, soot can be remarkably improved, and the reduction in soot is more obvious for fuels with higher distillation temperatures.

A single-cylinder, naturally aspirated, air-cooled diesel engine is used to study the effects of variable oxygen-enriched and nitrogen-enriched intake charge on engine combustion features and emission characteristics. The results show that with the increase in intake oxygen concentration from nitrogen-enriched modes, the ignition delay is decreased, and the maximum pressure rise rate and peak pressure are increased. The effect of enriched nitrogen on prolonging ignition delay appears to be more evident than that of enriched oxygen on shortening the ignition delay. As a whole, the increase rate of four types of pollutants show a quadratic polynomial relationship with the increase rate of intake oxygen. In oxygen-enriched modes, the effects of increased oxygen on the reduction of hydrocarbons (HC) and carbon monoxide (CO) emissions and smoke become weak, whereas in nitrogen-enriched modes, the CO and HC emissions and smoke deteriorate rapidly. Nitrogen oxide (${\mathrm{NO}}_x$) emissions are steeply increased in oxygen-enriched modes, but slowly decline in nitrogen-enriched modes. At high loads, the oxygen supply is restricted, so the effect of the intake oxygen variation on CO emissions and smoke is enhanced. However, at low loads, the intake oxygen significantly affects the bulk gas temperature in cylinder, resulting in a more sensitive variation in HC and ${\mathrm{NO}}_x$ emissions.