Distributed Energy Supply Research Articles

Optimal Allocation of Distributed Energy Supply System Under Uncertainty Based Improved Gray Wolf Algorithm

In order to improve the economical performance of distributed energy supplysystem under uncertainty, the improved gray wolf algorithm is constructed foroptimal allocation of distributed energy supply system. The relating researchprogress is summarized firstly, and effect of improved gray wolf algorithmon optimal allocation of distributed energy supply system are studied. Theoptimal allocation model of distributed energy supply system is constructedconsidering fuel consumption, operation and maintenance cost, environmentpenalty cost, and power grid energy exchange function, and the uncertainfactor is processed based on scienario method. And then the improved graywolf algorithm is designed, and the initial strategy of population and the reg-ulated method of main parameters are improved. Finally, simulation analysisis carried out, simulation results show that the proposed model can obtainbest optimal allocation effect of system.

An almost robust model for minimizing disruption exposures in supply systems

This paper studies two-stage disruption exposure minimization problems, motivated by the supply disruption issues in the energy and water supply systems. In particular, we address the ambiguity in both the probability distribution and risk preference of decision-makers towards disruption exposures. First, we propose a two-stage distributionally robust model with adjustable uncertainty sets, which solves a supply system solution with the least possible disruption exposures. We show that this two-stage robust disruption exposure model can be reduced to a computationally attractive single-stage mixed-integer linear program. We then propose an extended almost-robust disruption guarantee model to account for the ambiguity in the risk preference of decision-makers. We demonstrate that this almost-robust guarantee model can reveal clear preferences of most decision-makers under limited distribution information, which however does not resort to any particular disutility function specification and can be solved efficiently using a binary search algorithm. A decision support framework is also developed to guide users on how to apply the proposed disruption exposure models. Finally, we apply the proposed models to a distributed energy supply system design problem. Numerical results show that our models significantly outperform a risk-neutral model in hedging against a broad set of supply distributions. Moreover, the almost-robust guarantee model exhibits its advantages in hedging against high disruption levels, and performs the best under the vast majority of distributions regarding all tested statistical criteria.

Research on Dynamic Evaluation of Distributed Energy Supply Cost-Benefit for Integrated Energy Service in Campus

Zones are natural test fields for integrated energy services. The main operating mode of distributed energy supply business is “energy equipment leasing”, which means that users only have the right to use the equipment, and the power distribution company has the ownership of the equipment. Distributed energy supply business uses energy with lower cost and more environmentally friendly processes, in conjunction with related energy equipment, to provide users with daily required cold, heat, electricity, and gas energy for production and daily use. It not only effectively reduces the energy cost of users, but also achieves good environmental protection effect, and it can ensure that the distribution company can recover the initial investment and earn reasonable income. Therefore, this article analyses the cost-benefit structure of the distributed energy supply business based on the working characteristics.

Blockchain and AI-Based Natural Gas Industrial IoT System: Architecture and Design Issues

With the development of energy interconnection and increasing consumption of natural gas, the distributed energy supply and trusted-transaction- based natural gas Industrial Internet of Things (IIoT) has become one of the hottest research spots in the energy industry. This article puts forward natural gas IIoT architecture based on blockchain and AI, in order to address the defects of centralized energy supply architecture. The proposed architecture is introduced in detail from three aspects of infrastructure, side-chain of natural gas block based on data dimension, and backbone of natural gas block based on value dimension. Then the design issues on the integration existence of blockchain and AI in an actual natural gas IIoT scenario are discussed, including data association and interaction of blockchains, trusted identity authentication and management, energy source and virtual currency transformation, and so on. Next, an LSTM-based natural gas load prediction model is proposed by virtue of AI technology. The transaction model based on natural gas value and supply-demand relationship is also proposed by choosing the common natural gas application scenarios and taking advantage of blockchain technology. Experiments show that the proposed models can predict demand and output load of natural gas, while achieving the balance of interests of natural gas suppliers, users, and market in the transaction scenarios.

Schottky-Contacted Nanowire Sensors.

The progress of the Internet-of-Things in the past few years has necessitated the support of high-performance sensors. Schottky-contacted nanowire sensors have attracted considerable attention owing to their high sensitivity and fast response time. Their progress is reviewed here, based on several kinds of important nanowires, for applications such as bio/chemical sensors, gas sensors, photodetectors, and strain sensors. Although Schottky-contacted nanowire sensors deliver excellent performance in these fields, they can be further improved by various methods, including defect engineering, surface modification, the piezotronic effect, and the piezophototronic effect, all of which are discussed here. With regard to practical applications, further efforts are required to address challenges such as the stability, selectivity, ultrafast response, multifunctionality, flexibility, distributed energy supply, and sustainability of Schottky-contacted nanowire sensors. Finally, future perspectives and solutions are discussed.

Synergetic cascade-evaporation mechanism of a novel building distributed energy supply system with cogeneration and temperature and humidity independent control characteristics

Low and medium grade heat sources, such as geothermal energy, solar energy, and various waste heat sources, can only usually meet the independent demand of electricity, cooling or heating in the building. However, the demand for different forms of energy exists simultaneously. Therefore, a novel distributed building energy supply system is presented and cascade evaporation is used for combined cooling, heating and power. Two-stage evaporation is adopted to realize the temperature and humidity independent control. The coupling effect of the cascade evaporation and the building energy supply ability is illustrated through the multi-parameter optimization of system power generation and refrigeration performance as well as the simulation analysis of cooling and power control strategies. The results show that the organic Rankine cycle (ORC) as the power source of the vapor compression cycle (VCC) eliminates the mechanical work and electrical energy conversion process between the ORC and VCC. The low-temperature stage of VCC dehumidifies the outdoor fresh air, while the high-temperature stage cools the indoor return air, realizing the independent control of temperature and humidity and increasing the equivalent evaporation temperature of VCC. The proposed energy supply system can simultaneously meet the cooling, heating and electricity demand of the building, so it can be promoted in practical engineering applications.

Development of a Decision-Making Framework for Distributed Energy Systems in a German District

The planning and decision-making for a distributed energy supply concept in complex actor structures like in districts calls for the approach to be highly structured. Here, a strategy with strong use of energetic simulations is developed, the core elements are presented, and research gaps are identified. The exemplary implementation is shown using the case study of a new district on the former Oldenburg airbase in northwestern Germany. The process is divided into four consecutive phases, which are carried out with different stakeholder participation and use of different simulation tools. Based on a common objective, a superstructure of the applicable technologies is developed. Detailed planning is then carried out with the help of a multi-objective optimal sizing algorithm and Monte Carlo based risk assessment. The process ends with the operating phase, which is to guarantee a further optimal and dynamic mode of operation. The main objective of this publication is to present the core elements of the planning processes and decision-making framework based on the case study and to find and identify research gaps that will have to be addressed in the future.

Coordination and Optimization of Muti-region Building Virtual Power Plant with Photovoltaic and Wind-power Units

In order to solve the unstable or economical shortages of power grids and realize the coordinated optimization of distributed energy supply systems in different regions of virtual power plant (VPP), a coordinated optimization scheduling model for multi-region building virtual power plants with wind-power and photovoltaic units is established. The VPP is made up of wind turbine, household photovoltaic, energy storage system (ESS) and electric vehicles (EV). Through inter-regional comprehensive energy interconnection, multi-regional VPP power is complemented. In order to make the electric energy sharing within VPP reasonable, the optimal model with the objective function of reducing the transaction cost between VPP and distribution network, the maintenance cost of wind-power and photovoltaic units and the maintenance cost of EV was established. Finally, the validity of the proposed model is verified by a case study of a typical building VPP with a residential building and a commercial building. The simulation results show that the proposed method can realize the coordinated and optimal power scheduling of different regions and different types of aggregation units, and effectively reduce the net cost of VPP.

Hardware in the loop experimental study for the combined cooling, heat and power system controller

ABSTRACT Distributed power supply system has the advantages of energy saving, environmental protection, high reliability, high stability and so on. The combined cooling, heat and power (CCHP) system based on gas turbine is a distributed energy supply system which adopts the strategy of power cascade utilization. It can provide electric power, air conditioning chilled water and domestic hot water at the same time. In this paper, the construction scheme of the CCHP system based on gas turbine is proposed firstly. Afterward, a comprehensive dynamic model of the CCHP system based on gas turbine is established. The model consists of four mutually coupled sub-models. Then, the controller of the CCHP system is designed. In the operation mode of “electricity determines cold and heat“, three sets of PI algorithm with feedforward compensation are adopted to ensure the stability of combustion engine speed, temperature of chilled water outlet and domestic hot water outlet. Finally, a HIL simulation test of the CCHP system based on gas turbine is carried out. The test results show that the speed overshoot does not exceed 0.5% when the gas turbine is unloaded. The temperature of chilled water outlet of bromine cooler can achieve stable control. The temperature of domestic hot water outlet has a small overshoot and no steady state error. Therefore, the correctness of the control algorithm, the feasibility and effectiveness of the controller are verified.

Planning and Design of a Micro energy network for seawater desalination and regional energy interconnection

With the rapid development of the economy, the continuously increasing population, and ongoing climate change, the shortage of freshwater resources has become an increasingly important global problem. Seawater desalination technology can effectively alleviate the pressure on freshwater supplies and has been investigated in many countries. However, the majority of existing projects focus on the research and development of desalination equipment and the use of new technologies and pay less attention to the operation optimization of the desalination process. The micro energy network (MEN) designed in this study is an efficient distributed energy supply system that can be used to simultaneously supply electricity, cooling, heating, and freshwater as photovoltaic power, wind power, combined heat and power (CHP), electric cooling and heating, and a seawater desalination device are integrated into the MEN. In this study, a model for operation optimization of a MEN for seawater desalination was developed and the influences of the electric cooling and heating ratios and the operation optimization of the seawater desalination device were studied with the aim of minimizing the life cycle cost. Based on the results of this study, MENs can reduce the operation cost of desalination devices and improve the efficiency of renewable energy sources.

Township-based bioenergy systems for distributed energy supply and efficient household waste re-utilisation: Techno-economic and environmental feasibility

Sustainable waste management and climate change have been two of the major challenges worldwide. This study designed township-based bioenergy systems to treat solid waste in Glasgow based on anaerobic digestion and gasification technologies. The economic feasibility and environmental impacts (i.e. global warming potential, eutrophication potential, and acidification potential) were evaluated using Monte Carlo simulation-based cost-benefit analysis and life cycle assessment. It was found that township-based bioenergy systems could save over 300 kg of CO2 per tonne of municipal solid waste treated when biogenic carbon is excluded. It was shown that the proposed systems have profitability chances ranging from 68 to 98%, when the sale of by-products (digestate and biochar) is considered. This study also explored the effects of by-product selling and carbon tax on the economic feasibility of township-based bioenergy systems. The township-based bioenergy system can satisfy 20–23% of electricity demands and 4–5% of heat demands of each township served. The study can facilitate investors and policymakers to make informed decisions about planning distributed Waste-to-Energy (WtE) systems.

Assessment of tools for urban energy planning

In recent years, studies and policies have encouraged the diffusion of distributed energy supply technologies and large integration of renewable sources. This increases the need for new professionals in energy planning. Several computational tools for energy planning have been developed as described in the technical literature. However, energy planners of urban/district areas engaged in the transition towards smart systems related to buildings energy services require well-documented tools to evaluate the combination of available energy sources by proper conversion technologies. With this, after a scientific review, we selected 17 tools targeted on an urban/districts scale that can evaluate several energy services, sources and/or technologies, and provided with detailed and easily accessible documentation. These tools were classified based on their defined features: analysis type, operation spatial scale, outputs time scale, energy service, and licence. Among them, 6 user-friendly tools were identified (energyPRO, HOMER, iHOGA, EnergyPLAN, SIREN, WebOpt) that can provide hourly energy calculations and can be considered as viable for widespread use. Specifically, the general information, functionalities, structure, graphic user interface, required input data, and outputs were described. Therefore, the energy planners are guided towards choosing the most suitable tool based on their skills, aims, and data availability for a specific application.

Evaluation of the feasibility of distributed energy supply system for existing multi-family housing in Nagoya City

The possibility of introducing distributed energy system consisting of combining heat and power generation (CHP) for existing multi-family housing is discussed in order to make an academic ground for calling for the spread of distributed energy systems in existing multi-family houses. Case study was conducted to evaluate energy conservation effect of the distributed energy supply system and obtain the findings concerning on its feasibility. The case study was focusing on all municipal multi-family housing in Nagoya city, Japan, and it was evaluated based on primary energy consumption reduction, CO2 emission reduction, simple pay-back period, and recurring expenses merit by introducing the system. Annual energy consumption was estimated for nine typical municipal multi-family houses with different average occupied floor area and number of dwelling for each individual building unit. Based on the results of the case study, it was found that the effect of the distributed system varies depending on the average occupied floor area and the number of residences, and the generator capacity of CHP. In addition, when assuming adapting a distributed energy supply system into a type of housing has occupied floor area of 30m2-50m2 per a dwelling that accounts for 83.5% of the total municipal housing in Nagoya, at least the overall reduction of 16.7% CO2 emission reduction rate could be expected.

A Making method of Time-series energy demand data of non-residential buildings for urban energy analysis

Urban energy supply systems are changing to distributed energy supply systems according to the spreading of renewable energy. In order to effectively arrange and operate distributed energy supply systems in the city, it is necessary to (1) predict energy demands for each use in each building, (2) consider operation technology such as interchange or storage, and (3) study on a city scale rather than a building scale. Therefore, we aim to construct a method to calculate the optimal energy supply system with renewable energy based on data from geographical information systems (GIS). This paper describes the development of an energy-demand prediction method for non-residential buildings and a demand analysis in Japanese business areas by using this method. For the demand analysis, we developed a method to predict the demand of electricity and heat (heating, cooling and hot water) of non-residential buildings for one year. This program fluctuations in demand by five-minute intervals depending on the type of buildings (office, hospital, hotel, store, restaurant and school), total floor area, outdoor air temperature and so on. The standard demand amount of each type of buildings is based on statistical data and measurement data about energy consumption of non-residential buildings in Japan. Furthermore the fluctuation method of the demand incorporates random number simulation and probability distribution to reproduce an actual fluctuation. We predicted and accumulated the demand for hundreds of buildings by three districts for the demand analysis in the whole district. One of these analyses showed that there are large fluctuations in the demand of each building, and these fluctuations decrease by grouping the buildings in the block. Moreover, we analyzed the gap of peak demand between aggregated individual buildings and districts. This analysis revealed that some of peak demand in districts are less than 40% of aggregated individual.

Multi-Objective Planning Research on Micro Energy Network Considering Desalination

With the rapid development of economy, the lack of freshwater resources has become increasingly urgent in many areas of China. Desalination can ease some of the pressure on freshwater supply, especially in coastal areas and isolated islands. The micro energy network is an efficient distributed energy supply system that can be used to supply electricity, cooling, heat and freshwater simultaneously. In this paper, wind turbine, photovoltaic(PV), combined cooling, heating and power(CCHP) system and desalination unit are integrated into the micro energy network. A multi-objective optimization research is conducted on the key equipment capacity and the operation of the desalination unit, with the goal of optimizing the life cycle cost and annual CO2 emissions simultaneously. And through the study of cases, the impact of the operation of desalination unit on the planning solutions of micro energy network is researched.

Optimizing Photovoltaic Operation Control for Community with CCHP under Economy Scales

With the rapid development of industry, carbon emissions and other environmental problems have become increasingly prominent due to the consumption of fossil fuels, which can be alleviated by changing the mode of energy utilization and utilizing renewable energy. Because of its high energy efficiency, less pollution and the ability to realize the cascade utilization of energy, the combined cooling heating and power (CCHP) system will become the development trend of the distributed energy supply system in the future. In this paper, solar energy refrigeration mode, photovoltaic power supply mode, and waste heat refrigeration technology are used to construct the control method of the power supply mode of CCHP system with solar energy in the park and establish two kinds of energy supply modes including fuel cost and electricity purchase cost respectively. Considering the deviation of solar power output prediction, the stochastic objective functions are described by α-super-quantile method and the optimization model is established. The simulation results are solar energy parameters. The economic benefit of CCHP system running in cooling mode is higher than that of power supply mode, which can provide new ideas for the efficient and rational utilization of renewable energy under the background of smart grid.

Optimal ([formula omitted])-reliable design of distributed energy supply systems

Distributed energy supply systems are most efficiently designed by mathematical optimization. However, optimization models often assume availability of all components at any time. In practice, security of energy supply is crucial; thus, reliability is mandatory but often neglected in optimization and only implemented subsequently employing expensive rules of thumb.In this work, we propose an exact optimization approach to identify (n−1)-reliable designs for energy systems. The approach guarantees energy supply during the failure of 1 component at any time and is independent of probabilities and the selection of scenarios. (n−1)-reliability is also necessary to allow for maintenance of components. For problems with high computational effort, we propose the inexact but computationally efficient (n−1max)-reliability approach which also guarantees energy supply but allows overproduction. A real-world case study shows that both approaches identify reliable designs at only a small increase of the total annualized costs compared to the unreliable base case.

Multi-criteria integrated evaluation of distributed energy system for community energy planning based on improved grey incidence approach: A case study in Tianjin

Community energy planning is necessary for sustainable development of energy systems. However, given a series of energy sources and energy utilization technologies, it is crucial to select the optimal energy supply system to obtain the maximum comprehensive benefits. This study attempts to extend a multi-criteria integrated evaluation method that considers the aspects of technology, economy, environment, and society for evaluating the planning schemes of distributed energy supply systems. First, the rank correlation analysis and entropy information method are adopted to obtain subjective and objective weights, respectively. A combination of the maximum entropy principle and the minimized weighed generalized distance to the ideal scheme are employed to obtain optimal weighting coefficients. Second, based on the different priorities of evaluation indexes, the optimal schemes are established based on the improved grey incidence evaluation method, and under the integrated evaluation, the optimized combined cooling/heating and power system is proven to be the best option for the given case study. The results show that the proposed multi-criteria integrated evaluation method is a simple and practical tool for community energy planning.

Comprehensive Comparative Analysis of Different Regional Energy Supply Schemes

A comprehensive comparative analysis of different energy supply schemes is carried out to solve the coordinated supply problem in regional multi-energy complementary systems. Firstly, two distributed energy supply schemes, respectively gas turbine CCHP system and environment-source heat pump system, are proposed, and corresponding operation strategies are formulated; next, the safety and environmental performances of the municipal centralized energy supply scheme and the above two distributed energy supply schemes are analyzed; then, a probabilistic life-cycle cost model is established, and the calculation methods for the economic efficiencies of the three energy supply schemes are presented; finally, in the case of one certain commercial region in northern China, the comprehensive evaluation on the three energy supply schemes considering economy, safety and environmental performance is carried out. Based on sensitivity analysis, the impacts of natural gas price and electricity price on the economic efficiency of different energy supply schemes are obtained, which indicate that as the natural gas price and electricity price change, the scheme with the optimal economic efficiency will change correspondingly. As a result, a rational energy supply scheme in practical projects should be formulated considering the focus of the planning area and the local energy prices.

Optimization of 4th generation distributed district heating system: Design and planning of combined heat and power

Abstract This study applies a mathematical programming procedure to model the optimal design and planning of a new district which satisfies two features of the 4th generation district heating systems: energy reciprocity and on-site generation. The aim of the computational model is to investigate the effect of energy reciprocity (energy exchange among the buildings) as well as to find the best way to select the equipment among various candidates (capacities), the pipeline network among the buildings, and their electrical connections. The objective function includes the annualized overall capital and operation costs for the district along with the benefits of selling electricity to the grid. The distributed energy supply consists of heating, cooling, and power networks, several CHP technologies, solar array, chillers, and auxiliary boilers. The performance of the model for poly-generation was evaluated for designing the new part of Suurstoffi district situated in Risch Rotkreuz, Switzerland with seven residential and office complexes under four different scenarios. Allowing heat exchange among the buildings leads to 25% reduction in total annualized cost and 5% reduction in emission compared to the conventional districts. Removing the network and installation of PV and CHPs results in 9% reduction in emission and 11% reduction in cost. Simultaneous heat and electricity exchange results in a higher reduction in total annualized cost equal to 40% of the base scenario.