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ردیف | عنوان | نوع |
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1 |
Annealing-based Quantum Computing for Combinatorial Optimal Power Flow
محاسبات کوانتومی مبتنی بر بازپخت برای جریان قدرت بهینه ترکیبی-2022 This paper proposes the use of annealing-based
quantum computing for solving combinatorial optimal power
flow problems. Quantum annealers provide a physical com-
puting platform which utilises quantum phase transitions to
solve specific classes of combinatorial problems. These devices
have seen rapid increases in scale and performance, and are
now approaching the point where they could be valuable for
industrial applications. This paper shows how an optimal power
flow problem incorporating linear multiphase network modelling,
discrete sources of energy flexibility, renewable generation place-
ment/sizing and network upgrade decisions can be formulated as
a quadratic unconstrained binary optimisation problem, which
can be solved by quantum annealing. Case studies with these
components integrated with the ieee European Low Voltage
Test Feeder are implemented using D-Wave Systems’ 5,760
qubit Advantage quantum processing unit and hybrid quantum-
classical solver. Index Terms— Distribution Network | D-Wave | Electric Vehicle | Optimal Power Flow | Power System Planning | Quantum Annealing | Quantum Computing | Smart Charging. |
مقاله انگلیسی |
2 |
Reconfiguration of electrical distribution network-based DG and capacitors allocations using artificial ecosystem optimizer: Practical case study
پیکربندی مجدد تخصیص DG و خازن مبتنی بر شبکه توزیع الکتریکی با استفاده از بهینه ساز اکوسیستم مصنوعی: مطالعه موردی عملی-2021 In this article, a new implementation of Artificial Ecosystem Optimizer (AEO) technique
is developed for distributed generators (DGs) and capacitors allocation considering the Reconfiguration of Power Distribution Systems (RPDS). The AEO is inspired from three energy transfer
mechanisms involving production, consumption, and decomposition in an ecosystem. In the production mechanism, the production operator allows AEO to produce a new individual randomly,
whereas the search space exploration can be improved as illustrated in the consumption mechanism
and exploitation can be performed in the decomposition. A practical case study of 59-bus Cairo distribution system in Egypt is simulated with different loading percentages. For optimizing the performance of that practical network, the AEO algorithm is employed for different scenarios. Besides,
the results obtained by recent optimization techniques which are Jellyfish Search Optimizer (JFS),
Supply Demand Optimizer (SDO), Crow Search Optimizer (CSO), Particle Swarm Optimization
(PSO), Grey Wolf Optimizer (GWO) and Whale Optimization Algorithm (WOA) are compared
with the developed AEO. The simulation results demonstrate the efficacies and superiority of the
AEO compared to the others. It surpasses the other algorithms in terms of obtaining the best, mean,
worst, and standard deviations. After optimal RPDS and DGs placements, the power losses are
decreased by 78.4, 77.84 and 71.4% at low, nominal and high levels, respectively. However, the best
scenario with its application prospects is mentioned after optimal RPDS, DGs, and capacitors
where the power losses are decreased by 68.8, 85.87 and 89.91% at low, nominal and high levels,
respectively.
KEYWORDS: Artificial ecosystem optimizer | Distributed generators | Electrical systems | Power losses | Reconfiguration |
مقاله انگلیسی |
3 |
Managing expert knowledge in water network expansion project implementation
مدیریت دانش تخصصی در اجرای پروژه توسعه شبکه آب-2021 The implementation of expansion projects of water networks supplying growing cities
is deemed to be a complex decision-making problem involving both technical aspects and expert
knowledge. Management and control processes must rely on experts in the field whose knowhow must be coupled with techniques able to deal with the natural subjectivity that affects
input evaluations. Given the presence of many decision-making elements, the choice of proper
hydraulic technical parameters may be linked to the main aspects of analysis requiring formal
expert evaluation. In this contribution, the simulation of hydraulic indicators is integrated with
a multi-criteria approach able to eventually determine those areas of a water network through
which organising the expansion may be more beneficial. The software EPAnet 2.0 is first used
for hydraulic simulations, whereas the Technique for Order of Preference by Similarity to Ideal
Solution (TOPSIS) will eventually rank network’s nodes. A case study is solved to demonstrate
the applicability and effectiveness of the proposed approach.
keywords: Complex Systems | Management and Control | Water Distribution Networks | Expansion Project | EPAne | software 2.0 | TOPSIS. |
مقاله انگلیسی |
4 |
A Multi-Objective Green Hub Location Problem with Multi Item-Multi Temperature Joint Distribution for Perishable Products in Cold Supply Chain
یک مشکل مکان یابی Green Hub چند هدفه با توزیع مشترک چند ماده ای - چند دما برای محصولات فاسدشدنی در زنجیره تامین سرد-2021 This paper investigates a bi-objective green hub location problem, in which multiple perishable products with various storage temperatures can be distributed simultaneously in a cold supply chain (CSC).
The objectives of this problem include minimizing the system’s total cost (including transportation, hub
establishment, adjustment of the storage compartments’ temperatures, and carbon emission costs) and
maximizing the quality of the delivered product to the customer via the proposed model. Mixed-integer
linear programming (MILP) in the GAMS software was employed to formulate this problem. Then, the
ε-Constraint method was adopted to solve the presented bi-objective model to obtain the Pareto frontier
and consequently, a numerical example based on the CAB (Civil Aeronautics Board) database is presented
to validate the applicability of the model. The solutions of the model provide information regarding the
hub location (HL), allocating customers to the hubs, allocating customers to the vehicles, and the sequence of vehicles’ services for the Multi Item-Multi Temperature Joint Distribution of perishable products in CSCs. Moreover, the final results revealed the existence of a contradictory exchange between the
two objectives of this paper, implying that the higher is the quality of the delivered perishable product to
the customer, the greater is the system’s total cost. The novelty of the proposed model compared to other
hub location problems (HLPs) lies in the integration of the tactical/operational decisions with strategic
decisions to provide logistic solutions in CSCs by considering the carbon emissions as an environmental
factor in the transportation systems for the simultaneous distribution of dissimilar storage temperatures
perishable products within a CSC. The proposed model in this research can help the distributers of perishable products by maintaining the quality of the delivered items and reducing the system’s total costs
and considering the carbon emissions of transportation systems. This study has practical implications
for the logistics and CSCs managers to not only establish a distribution network for multiple perishable
products on the basis of the findings, but also respond to the environmental sustainability. Keywords: Hub Location | Perishable Products | Cold Supply Chain | Transportation | Multi-objective |
مقاله انگلیسی |
5 |
Environmental impacts of animal-based food supply chains with market characteristics
تأثیرات زیست محیطی زنجیره های تأمین مواد غذایی حیوانی با ویژگی های بازار-2021 Animal-based food supply chains lead to significant environmental impacts, which can be influenced by
production systems, distribution networks and consumption patterns. To develop strategy aimed at
reducing the environmental impact of animal-based food supply chains, the common environmental
hotspots among different types of food, the role of transport logistics and the consequence of end market
need to be better understood. Life cycle assessment was adopted to model three types of animal-based
food chains (beef, butter and salmon), with specific technologies, high spatial-resolution logistics and
typical consumption patterns for three markets: local, regional (intra-European) and international. The
results confirmed that the farm production stage usually had the greatest environmental impact, except
when air transport was used for distribution. Potentially, the role of end market also can significantly
influence the environmental impacts. To understand more, three improvement options were examined
in detail with regard to hotspots for climate change: novel feed ingredients (farm production stage), sustainable aviation fuel (transport and logistics stage) and reduction of wasted food (consumption and end
of life stage). Significant reduction was achieved in the salmon system by sustainable aviation fuel (64%)
and novel feed (15%). Minimizing food waste drove the greatest reduction in the beef supply chain (23%)
and the international butter supply chain can reduce 50% of GHG mission by adopting sustainable
aviation fuel. Combined interventions could reduce GHG emission of animal-based food supply chains
by 15% to 82%, depending on market, transport and food waste behaviour. The results show that ecoefficiency information of animal-based foods should include the full supply chain. The effective mitigation strategy to achieve the greatest reduction should not only consider the impacts on-farm, but also
detail of the downstream impacts, such as food distribution network and consumption patterns. Keywords: Sustainability | Life cycle analysis | Animal-based food supply chain | Spatial-resolution |
مقاله انگلیسی |
6 |
Zero-net energy management for the monitoring and control of dynamically-partitioned smart water systems
مدیریت انرژی صفر خالص برای نظارت و کنترل سیستم های اب هوشمند تقسیم شده -2020 The optimal and sustainable management of water distribution systems still represent an arduous task.
In many instances, especially in aging water net-works, pressure management is imperative for reducing
breakages and leakages. Therefore, optimal District Metered Areas represent an effective solution to
decreasing the overall energy input without performance compromise. Within this context, this paper
proposes a novel adaptive management framework for water distribution systems by reconfiguring the
original network layout into (dynamic) district metered areas. It utilises a multiscale clustering algorithm
to schedule district aggregation/desegregation, whilst delivering energy and supply management goals.
The resulting framework was tested in a water utility network for the simultaneously production of
energy during the day (by means of the installation of micro-hydropower systems) and for the reduction
of water leakage during the night. From computational viewpoint, this was found to significantly reduce
the time and complexity during the clustering and the dividing phase. In addition, in this case, a
recovered energy potential of 19 MWh per year and leakage reduction of up to 16% was found. The
addition of pump-as-turbines was also found to reduce investment and maintenance costs, giving
improved reliability to the monitoring stations. The financial analyses to define the optimal period in
which to invest also showed the economic feasibility of the proposed solution, which assures, in the
analysed case study, a positive annual net income in just five years. This study demonstrates that the
combined optimisation, energy recovery and creation of optimized multiple-task district stations lead to
an efficient, resilient, sustainable, and low-cost management strategy for water distribution networks. Keywords: Water distribution systems | Micro-hydropower systems | Sustainable and smart cities | Water-energy nexus | Water leakage reduction | Financial return-on-investment |
مقاله انگلیسی |
7 |
Internet-of-things-based optimal smart city energy management considering shiftable loads and energy storage
مدیریت انرژی بهینه شهر هوشمند مبتنی بر اینترنت اشیا با توجه به بارهای قابل تغییر و ذخیره انرژی-2020 Formulating a novel mixed integer linear programing problem, this paper introduces an optimal
Internet-of-Things-based Energy Management (EM) framework for general distribution networks in
Smart Cities (SCs), in the presence of shiftable loads. The system’s decisions are optimally shared between
its two main designed layers; a “core cloud” and the “edge clouds”. The EM of a Microgrid (MG),
covered by an edge cloud, is directly done by its operator and the Distribution System Operator (DSO) is
responsible for optimising the EM of the core cloud. Changing the load consumption pattern, based on
market energy prices, for the edge clouds and their peak load hours, the framework results in decreasing
the total operation cost of the edge clouds. Using the optimal trading power of the MGs aggregators as
the input parameters of the core cloud optimisation problem, the DSO optimises the network’s total
operation cost addressing the optimal scheduling of the energy storages. The energy storages are charged
in low energy prices through the purchasing power from the market and discharged in high energy
prices to meet the demand of the network and to satisfy the energy required by the edge clouds. As a
result, the shiftable loads and the energy storages are used by the DSO and the MGs to meet the energy
balance with the minimum cost. Keywords: Energy management | Internet-of-Things | Microgrids | Optimal scheduling | Renewable energy sources |
مقاله انگلیسی |
8 |
Flexibility management model of home appliances to support DSO requests in smart grids
مدل مدیریت انعطاف پذیری لوازم خانگی برای پشتیبانی از درخواست DSO در شبکه های هوشمند-2020 Several initiates have been taken promoting clean energy and the use of local flexibility towards a more sustainable
and green economy. From a residential point of view, flexibility can be provided to operators using
home-appliances with the ability to modify their consumption profiles. These actions are part of demand response
programs and can be utilized to avoid problems, such as balancing/congestion, in distribution networks.
In this paper, we propose a model for aggregators flexibility provision in distribution networks. The model takes
advantage of load flexibility resources allowing the re-schedule of shifting/real-time home-appliances to provision
a request from a distribution system operator (DSO) or a balance responsible party (BRP). Due to the
complex nature of the problem, evolutionary computation is evoked and different algorithms are implemented
for solving the formulation efficiently. A case study considering 20 residential houses equipped each with seven
types of home-appliances is used to test and compare the performance of evolutionary algorithms solving the
proposed model. Results show that the aggregator can fulfill a flexibility request from the DSO/BRP by rescheduling
the home-appliances loads for the next 24-h horizon while minimizing the costs associated with the
remuneration given to end-users Keywords: Demand response | Flexibility | Home appliances | Local energy management | Smart grids |
مقاله انگلیسی |
9 |
An efficient interactive framework for improving resilience of power-water distribution systems with multiple privately-owned microgrids
یک چارچوب تعاملی کارآمد برای بهبود مقاومت در برابر سیستم های توزیع آب و انرژی با چندین میکروگرید متعلق به بخش خصوصی-2020 Resilience improvement of power distribution networks against natural disasters is an important problem. Water
network similar to other important infrastructures depends on power networks. In this paper, resilience improvement
is defined as increasing the users’ accessibility to water and power after natural disasters. Microgrids
with appropriate operation can provide energy to restore disconnected loads in distribution networks. In the
proposed interactive framework, a stochastic energy management program for microgrids is designed that not
only determines the amount of energy can be delivered to distribution systems, but also considers the reliability
of local loads during emergency conditions. Each microgrid provides a list of bid-quantity energy blocks to the
distribution system operator (DSO) during the emergency period. Then, the DSO chooses the best plan to restore
disconnected loads considering inaccessibility values to power and water and also the damage of power and
water distribution networks. Demand response actions in microgrids are also considered as effective tools for the
energy management program, and their impact on the distribution system resilience is investigated. The proposed
model is tested on the modified IEEE 33-bus distribution system with multiple microgrids, and the effectiveness
of the proposed method is validated accordingly. Keywords: Microgrids | Natural disasters | Resilience | Stochastic linear programming | Water network |
مقاله انگلیسی |
10 |
Residential community with PV and batteries: Reserve provision under grid constraints
اجتماع مسکونی با PV و باتری: تأمین رزرو تحت محدودیت های شبکه-2020 Technological advances in residential-scale batteries are paving the way towards self-sufficient communities to
make the most use of their photovoltaic systems to support local energy consumption needs. To effectively utilize
capabilities of batteries, the community can participate in the provision of short term operating reserve (STOR)
services. To do so, adequate energy reserves in batteries are maintained during prescribed time windows to be
utilized by electricity system operators. However, this may reduce energy sufficiency of the community. Further,
the actual delivery of reserve could create distribution network congestions. To adequately understand the
capability of a community to provide reserve, this work proposed a residential community energy management
system formulated as a Mixed-Integer Linear Programming (MILP) model. This model aims to maximize energy
sufficiency by optimal scheduling of batteries whilst considering reserve constraints. The model also maintains
the aggregate power of houses within export/import limits that are defined offline using an iterative approach to
ensure that the reserve provision does not breach distribution network constraints. The model is demonstrated
on a residential community. The maximum committed reserve power with minimal impact on energy sufficiency
is determined. Results also show that the capability of a community to provide reserve could be overestimated
unless distribution network constraints are adequately considered. Keywords: Batteries | Community management systems | Distribution networks | Energy storage | Photovoltaics | Sufficiency |
مقاله انگلیسی |