Demand Side Management Research Papers (original) (raw)

This paper sets out features of traditional Energy Key Performance Indicators (KPIs) employed in energy management programs; then, new indicators are proposed based on Advanced Metering Infrastructure (AMI) usage. These indicators make it possible to directly relate the amount of energy, type of end use and user consumption patterns. Analysis of AMI system information enables planning for differentiated Demand-Side Management (DSM) strategies. A case study developed at Universidad Nacional de Colombia - Bogotá campus is presented, which proposes new Energy Key Performance Indicators in Real Time. These indicators enable information analysis and DSM strategies that are appropriate for new technologies and that are aimed at increasing energy efficiency. Additionally, this paper presents the factors that have to be taken into account when implementing KPIs (Key Performance Indicators) and the decision-making process. This results in variable overall energy savings between 5 and 40%, ac...

While the relations between climate variables and sectoral water demand have been well established in the literature, few studies have attempted to quantify changes in urban water usage with climate change. Concentrating on the city of Hamilton, New Zealand, we investigate possible water use and infrastructure needs for a range of climate and population projections. We find that water demand (at the monthly aggregate level) is largely driven by changes in population, and not significantly affected by changes in climate. However, as population increases, the effect of climate variables on per capita consumption will be magnified. Monthly aggregate changes may further mask potenially significant short-term shortages. In several scenarios, water supply shortages in 2030 occur with a 30-40% probability, suggesting needs for long-term capacity expansion or aggressive demand side management, rather than implementation of short-term management of water demand.

- by Matthias Ruth
- •
- Climate Change, Water resources, Climate variability, Water Resources Management

Demand response (DR) program through tariff initiative has been established in Malaysia since 1990. The available time of use (TOU) tariff focuses on providing price signals to consumers, especially from industrial and commercial sectors. In achieving a certain standard for off-peak tariff rider (OPTR) initiative to receive discount rate, consumers must improve load factors compared to the baseline declared. However, not all consumers are able to commit. In Universiti Teknikal Malaysia Melaka (UTeM), the TOU (C1-OPTR) tariff is proposed and applied when the available cost discount of 20% can be enjoyed by sustaining the load factor improvement (LFI). A simulator projected a flexible optimal load profile referred by the energy management team to achieve the university's sustainable energy management goal. Thus, securing the LFI would allow the energy consumption (kWh) and peak demand (kW) to be managed concurrently. As for testing results for two buildings, the load factor improves to 0.40, and the maximum demand reduces by about 35 kW. When getting the 20% discount for the OPTR scheme, the total cost saving is forecasted approximately USD 29,441.40 yearly. The current pilot project presents a positive sign with the peak demand reduction and load factor improvement close to the simulator's optimal profile.

- by beei iaes and +1
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- Energy Management, Demand Response, Demand Side Management

The balancing approach of electricity generation and consumption is an
essential part of a reliable power system. The mismatch between supply
and demand may also cause fluctuation in the power system. This study
proposes an incentive and penalty-based demand response (I&P-DR) program
for improving the profitability of both LSE and customers. First, we use
a parameter that weighs the financial benefits of LSE and customers and
provides considerable economic benefits to both sides. Second, an incentive
and penalty (I&P) price scheme have been employed to recompense and
penalize customers and reduce the electricity demand at peak hours. Finally,
the study analyzes the importance of (I&P-DR) and its impact on customers’
sensitivity during peak intervals. Simulation results showed that the flexibility
to consumption can be brought through the application of the proposed
(I&P-DR) program and also provide the financial benefits to both, customers
and LSEs.

- by Muhammad Hussain and +1
- •
- Demand Response, Demand Side Management, Dynamic Pricing, Energy Managment

فشصه تیشیذه یبّ ذٌتسّ . یاشجا یاشب ِهبًشب يیا بّ صا شٍس یبّ یتٍبفته ُدبفتسا ُذض داذعت بلغا ِک تسا یه صضَپ ظبخ عًَ ذٌچ سد اس بّسبب صا یدٍذحه .ذٌّد ِلبقه يیا سد صا شٍس ییبجببج سبب فشصه تیشیذه یاشب ِکبضضیس ذٌوضَّ ی ِک ُذض ُدبفتسا ِلئسه يیا ا بب کيپ صّبک فاذّ سبب ٍ نتسيس ٌِیضّ یبّ یاشب ييکشتطه طسَت ِکبض سد عٌَته یبّسبب یسٌَيسک ٍ یسٌَيس بیاشض بب تاسر مبحدصا نتیسَگلا ( H-PSO-SCAC ) 1 لح ُذض ، س شب یدبٌْطيپ ِهبًشب یاشجا شثا سپ ذيلَت ِکبضضیس ساصبب سد بّ فذّبب یعبوتجا ُبفس حطس دَبْب یسسشبدسَه تسا ِتفشگساشق . ِيبض یصبس ِکبض یٍس بّ ِکبضضیس ِس لهبض یذٌوضَّ ی یتعٌص ٍ یسبجت ،یگًبخ ی مبجًا ُذض ِک یبّسبب صا یفلتخه عاًَا یاساد لببق لشتٌک ذٌتسّ ِهبًشب ِک تسا ىآ صا یکبح جیبتً . کيپ صّبک بجَه یدبٌْطيپ ی ،سبب ٌِیضّ ی يکشتطه ٌِیضّ ٍ ي سبب لدبعت ٍ ُذض ذيلَت یبّ ٍ س حطس دَبْب ُشْب ذید صا یعبوتجا ُبف سادشب لببًد ِب اس دساد . ُطاٍ بّ ی لک ي ذ ی : لببق یبّسبب ِکبض ،لشتٌک ،ذٌوضَّ ی یعبوتجا ُبفس نتیسَگلا ، H-PSO-SCAC توس تیشیذه ، بضبقت DSM 2

- by Javad Ebrahimi
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- Business, Power Systems, Power Management, Microgrid

Demand Side Management (DSM) results in energy consumption reduction accompanied by lower cost according to the feasibility study for each project. In Egypt, DSM projects are scarce due to lack of good studies proving their underlining profitability. This paper studies the major types of DSM programs and their availability to be executed in Egypt. Tips to measure feasibility for these projects are given using the Net Present Value (NPV), Internal Rate of Return (IRR), Profitability Index (PI), Payback Period (PP) and Discounted Payback Period(DPP). Different factors affecting the projects to study like the inflation factor and the discount rate are studied. This paper also investigates a new sustainable way for natural illumination called the sun tunnel. This method is presented with its different types: rigid and flexible as a case study.

Many new demand response strategies are emerging for energy management in smart grids. Real-Time Energy Pricing (RTP) is one important aspect of consumer Demand Side Management (DSM), which encourages consumers to participate in load scheduling. This can help reduce peak demand and improve power system efficiency. The use of Intelligent Decision Support Systems (IDSSs) for load scheduling has become necessary in order to enable consumers to respond to the changing economic value of energy across different hours of the day. The type of scheduling problem encountered by a consumer IDSS is typically NP-hard, which warrants the search for good heuristics with efficient computational performance and ease of implementation. This paper presents an extensive evaluation of a heuristic scheduling algorithm for use in a consumer IDSS. A generic cost model for hourly pricing is utilized, which can be configured for traditional on/off peak pricing, RTP, Time of Use Pricing (TOUP), Two-Tier Pricing (2TP) and combinations thereof. The heuristic greedily schedules controllable appliances to minimize smart appliance energy costs and has a polynomial worst-case computation time. Extensive computational experiments demonstrate the effectiveness of the algorithm and the obtained results indicate the gaps between the optimal achievable costs are negligible.

- by Fathi abugchem
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- Engineering, Economics, Decision Support Systems, Smart Grid
- by Nevenka Hrovatin
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- Economics, Energy Policy, Demand Side Management, Electricity

The problem of load modeling for Demand Side Management ( E M ) purposes is addressed in this paper. The proposed load models rely on information about both the physical characteristics of elemental load devices at the distribution level,... more

In the last few years, the reduction of energy consumption and pollution became mandatory. It became also a common goal of many countries. Only in Europe, the building sector is responsible for the total 40% of energy consumption and 36% of CO2 pollution. Therefore, new control policies based on the forecast of buildings energy behaviors can be developed to reduce energy waste (i.e. policies for Demand Response and Demand Side Management). This paper discusses an innovative methodology for smart building indoor air-temperature forecasting. This methodology is based on a Non-linear Autoregressive neural network. This neural network has been trained and validated with a dataset consisting of six years indoor air-temperature values of a building demonstrator. In detail, we have studied three characterizing rooms and the whole building. Experimental results of energy prediction are presented and discussed.

In the face of the current electricity supply deficiency facing Nigeria, there is indeed an overwhelming need to deploy several out of the box strategies towards closing the widening electricity supply/demand gap and to provide succor for the people. It is therefore the opinion of the author as expressed in this paper that decision makers in the Nigerian power sector should undertake a holistic review of their strategies towards making power available to all Nigerians and adopt a policy that must include promotion of energy efficiency, its conservation, demand side management and energy saving for the country in addition use of other technological innovation towards increasing the quantum of generated electric power across the country.
Therefore, the innovation in electric power solution from a Nigerian perspective and presented in this paper proposes;
The exploration of energy efficiency , energy conservation/energy saving and demand side management (DSM) towards improving electricity supply in Nigeria; optimizing electricity supply through use of energy efficiency, energy conservation/energy saving and demand-side management technologies.

- by Goody Oguzie
- •
- Energy Conservation, Energy efficiency, Demand Side Management, Energy savings

High fuel costs, increasing energy security and concerns with reducing emissions have pushed governments to invest in the use of renewable energies for electricity generation. However, the intermittence of most renewable resources when renewable energy provides a significant share of the energy mix can create problems to electricity grids, which can be minimized by energy storage systems that are usually not available or expensive. An alternative solution consists on the use of demand side management strategies, which can have the double effect of reducing electricity consumption and allowing greater efficiency and flexibility in the grid management, namely by enabling a better match between supply and demand.

- by Carlos Augusto Santos Silva
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- Mechanical Engineering, Renewable Energy, Energy, Energy Security

Peak energy demand is made of people’s simultaneous activities around the same period of the day. In the past, utilities made a profit out of peak demand, but the integration of renewable sources of energy and changing patterns in demand mean that peaks are increasingly seen as a problem in terms of cost of energy and carbon emissions. Demand Side Response consists of a set of programmes aimed at shifting peak demand to periods of the day when demand is lower and generation is cheaper.
Whilst in the U.S. Demand Side Response has been used for decades, this is a relatively recent phenomenon in Europe. Following studies in the first decade of the 2000s, which demonstrated future imbalances between demand and supply due to more intermittent renewables and higher peaks from electric vehicles and heat pumps, the regulatory space for Demand Side Response has been expanding. The number of businesses, such as energy aggregators, providing Demand Side Response services has been growing and gaining more and more traction also thanks to national roll-out of smart meters and plans to introduce Capacity Markets in most European countries.
Despite the widespread optimism on Demand Side Response, a comprehensive account of the evidence on the impacts of programmes aimed at shifting peaks of energy demand is missing. This book covers this gap by presenting evidence on a set of Demand Side Response activities, ranging from price-based to incentive-based programmes and policies. It also looks at the actual energy saving impacts of smart meters, collecting evidence from over 30 trials. The book draws on examples of different programmes for both residential and non-residential sectors of electricity demand, including Time of Use tariffs, Critical Peak Pricing Automated Demand Controllers and Ancillary Services. What constitutes peak energy demand? Can price influence the timing of electricity demand? Will automated controllers replace manual forms of Demand Side Response intervention?

- by Jacopo Torriti
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- Business, Electrical Engineering, Economics, Climate Change
- by Antonia Sonia A C Diniz and +1
- •
- Engineering, Renewable Energy, Energy Management, Demand Side Management

Back cover text: Real Social Science presents a new, hands-on approach to social inquiry. The theoretical and methodological ideas behind the book, inspired by Aristotelian phronesis, represent an original perspective within the social sciences, and this volume gives readers for the first time a set of studies exemplifying what applied phronesis looks like in practice. The reflexive analysis of values and power gives new meaning to the impact of research on policy and practice. Real Social Science is a major step forward in a novel and thriving field of research. This book will benefit scholars, researchers, and students who want to make a difference in practice, not just in the academy. Its message will make it essential reading for students and academics across the social sciences.

- by Bent Flyvbjerg and +1
- •
- Screenwriting, Critical Theory, Critical Theory, Critical Theory

Negli ultimi anni, l’integrazione di programmi di Demand Side Management è stata relativamente poco diffusa nei mercati energetici europei. Il Demand Side Management può essere definito come un ampio insieme di azioni che possono venire intraprese dal cliente in risposta a condizioni particolari nel sistema energetico (come ad esempio: periodi di congestione e di picco o prezzi elevati). Questo capitolo si prefigge di esaminare le ragioni che hanno portato ad un basso livello di penetrazione del Demand Side Management in Europa con riflessioni sui fattori che potrebbero influire una maggiore penetrazione in futuro, soprattutto in seguito alll’introduzione di Capacity Mechanisms. A questo scopo, il capitolo si avvale di una revisione della letteratura anche empirica su programmi di Demand Side Management già in essere. I risultati evidenziano come cambi nel sistema normativo, nella regolazione e nella tipologia di investimenti potrebbero modificare il ruolo del Demand Side Management in Europa. Per esempio, l’esperienza britannica indica che un cambiamento nella durata dei contratti di carico potrebbe favorire la partecipazione di una ben più ampia gamma di clienti di quelli attualmente impegnati nei mercati di Demand Side Management.

- by Jacopo Torriti
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- Demand Response, Demand Side Management, Energy demand
- by Nikolaos Zahariadis
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- Critical Theory, Business, Entrepreneurship, Organizational Behavior

Residential sector provides focused mitigation opportunities. Energy efficient space cooling is the main technology transition required. Almost 26% residential load could be reduced by DSM measures. Myriad barriers limit penetration of... more

- by Diptiranjan Mahapatra
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- Energy Policy, Multidisciplinary, Demand Side Management, Air Conditioning

Because of globalization, industrialization, and development due to technology, the demand for electrical energy is on the increase. There is therefore a need for efﬁcient energy measures to ensure conservation, thereby saving costs. Demand-side management (DSM) deals with conversion of energy demand of consumers into activities/programs/tactics (e.g. ﬁnancial incentives and public awareness/education), which brings about less use of energy by the consumers. Gellings and Parmenter gave a history of DSM in the United States and its inﬂuence on energy resources. They also explained the role of DSM in integrated resource planning, the main elements of DSM programs and summarized the key best practices for program design and delivery. Palensky and Dietrich (2011) described DSM as using measures such as sophisticated real-time control of distributed energy resources, better materials, smart energy tariffs with incentives for certain consumption patterns to improve energy efﬁciency. Various types of DSM were analyzed, and an overview of modern DSM projects was given. Haney et al. (2010) highlighted how integrated government DSM policies, targeting residential demand for electricity and heat are more likely.

—Smart city applications are developed to facilitate the urbanization and massive development all over the world. This is achieved with real time responses to challenges faced by different sectors, such as health, transportation, water and energy. Smart meter is one of the smart city applied solutions, which facilitates to overcome the increased demand on electricity. This research examines smart meter in the context of energy sector to exploit its related features in the process of Demand Side Management (DSM) to facilitate energy efficiency. A smartphone application is developed that facilitate integration of client in DSM for energy efficiency. The feasibility of such application is reflected on the smart meter business model adopted in Abu Dhabi. Consequently, fundamentals are established to initiate cost-benefit analysis to evaluate the rolling out of advanced metering infrastructure. Keywords— smart meter; smartphone application; energy efficiency; demand side management; advanced metering infrastructure.

- by Salam Khanji and +2
- •
- The Internet of Things, Energy efficiency, Smart Grid, Demand Side Management

Electricity systems models are software tools used to manage electricity demand and the electricity systems, to trade electricity and for generation expansion planning purposes. Various portfolios and scenarios are modelled in order to compare the effects of decision making in policy and on business development plans in electricity systems so as to best advise governments and industry on the least cost economic and environmental approach to electricity supply, while maintaining a secure supply of sufficient quality electricity. The modelling techniques developed to study vertically integrated state monopolies are now applied in liberalised markets where the issues and constraints are more complex. This paper reviews the changing role of electricity systems modelling in a strategic manner, focussing on the modelling response to key developments, the move away from monopoly towards liberalised market regimes and the increasing complexity brought about by policy targets for renewable energy and emissions. The paper provides an overview of electricity systems modelling techniques, discusses a number of key proprietary electricity systems models used in the USA and Europe and provides an information resource to the electricity analyst not currently readily available in the literature on the choice of model to investigate different aspects of the electricity system.

- by Aoife Foley
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- Mechanical Engineering, Decision Making, Renewable Energy, Energy

Phronetic organizational research is an approach to the study of management and organizations focusing on ethics and power. It is based on a contemporary interpretation of the Aristotelian concept phronesis, usually as ‘prudence’. Phronesis is the ability to think and act in relation to values, to deliberate about ‘things that are good or bad for humans’ in the words of Aristotle (1976:1140a24–b12). Phronetic organizational research effectively provides answers to the following four value-rational questions, for specific problematics in management and organization studies: 1. Where are we going with this specific management problematic? 2. Who gains and who loses, and by which mechanisms of power? 3. Is this development desirable? 4. What, if anything, should we do about it?

- by Bent Flyvbjerg
- •
- Screenwriting, Critical Theory, Business, Entrepreneurship

Demand side management (DSM) is one of the important functions in a smart grid that allows customers to make informed decisions regarding their energy consumption. It helps the energy providers reduce the peak load demand and reshape the load profile. This results in increased sustainability of the smart grid, as well as reduced over all operational cost and carbon emission levels. Most of the existing demand side management strategies used in traditional energy management system is with specific techniques and algorithms. In addition, the existing strategies handle only a limited number of controllable loads of limited types. DSM techniques are based on improvement of the load factor and load curve, whereas lowering the expenses.

In this work, we address the problem of providing fast and on-line households appliance load detection in a non-intrusive way from aggregate electric energy consumption data. Enabling on-line load detection is a relevant research problem as it can unlock new grid services such as demand-side management and raises interactivity in energy awareness possibly leading to more green behaviours. To this purpose, we propose an On-line-NILM (Non-Intrusive Load Monitoring) machine learning algorithm combining two methodologies: i) Unsupervised event-based profiling and ii) Markov chain appliance load modelling. The event-based part performs event detection through contiguous and transient data segments, events clustering and matching. The resulting features are used to build household-specific appliance models from generic appliance models. Disaggregation is then performed on-line using an Additive Factorial Hidden Markov Model from the generated appliance model parameters. Our solution is implemented on the cloud and tested with public benchmark datasets. Accuracy results are presented and compared with literature solutions, showing that the proposed solution achieves on-line detection with comparable detection performance with respect to non on-line approaches.

Prevailing approaches of planning and strategy making, which traditionally deal with the states of systems in terms of fixed goals, fail to acknowledge the process nature of sustainable development. Using a system dynamics approach and relying on the concept of viability loops, the paper aims to illustrate a practical implementation of sustainable development with an urban water system as an example. It argues that planning for sustainable development should be 'process-based' -rather than 'fixedgoal' -oriented. Unlike the traditional approaches of strategy making to set fixed goals related to either supply-side and/or demand-side management, it is argued that triggering a social learning process with full involvement of all stakeholders and planners in the process would be the most suitable strategy for sustainable development. To this end, backcasting is recommended as a suitable tool and the process of model building is regarded as a means of learning rather than forecasting.

- by ali bagheri
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- Sustainable Development, Forecasting, System Dynamics, Social learning

In recent years, the continuous increase of greenhouse gas emissions has led many companies to investigate the activities that have the greatest impact on the environment. Recent studies estimate that around 10% of worldwide CO 2 emissions derive from logistical supply chains. The considerable amount of energy required for heating, cooling, and lighting as well as material handling equipment (MHE) in warehouses represents about 20% of the overall logistical costs. The reduction of warehouses' energy consumption would thus lead to a significant benefit from an environmental point of view. In this context, sustainable strategies allowing the minimization of the cost of energy consumption due to MHE represent a new challenge in warehouse management. Consistent with this purpose, a two-step optimization model based on integer programming is developed in this paper to automatically identify an optimal schedule of the material handling activities of electric mobile MHEs (MMHEs) (i.e.,...

ntelligent energy management strategy for cost optimization offers a new paradigm for energy users in Nigeria. This research developed Arduino based energy consumption rate meter for residential homes using multidisciplinary concepts in Mechatronics. The system features real time demand side management using composite design methodology (CDM). It comprises the metering and cloud server cluster units. The work introduced ACS712 Hall Effect current sensor, Arduino Uno (with ATmega328 chipset), and SIM800L GSM modules to achieve the system functionalities. The design description on editor run-time environment enabled direct debugging in the open source Integrated Development Environment (IDE). The approach was evaluated through selected case studies and usability experiments. With the latter, the suitability of the system provided an efficient means of monitoring energy consumption with minimal errors. The results showed that when the meter was switched-ON with no load, an output of 0.00kWh was read. By connecting i-core7 Dell Inspiron laptop to it, an output of 10.75kWh was then observed on the cloud web application (real time). The output kept increasing whilst the load was still connected to the meter as expected. Utilities can smartly provide value-added services using the system, thereby increasing their revenues while ensuring customers satisfaction.

This article presents results from the first statistically significant study of cost escalation in transportation infrastructure projects. Based on a sample of 258 transportation infrastructure projects worth US$90 billion and representing different project types, geographical regions, and historical periods, it is found with overwhelming statistical significance that the cost estimates used to decide whether such projects should be built are highly and systematically misleading. Underestimation cannot be explained by error and is best explained by strategic misrepresentation, that is, lying. The policy implications are clear: legislators, administrators, investors, media representatives, and members of the public who value honest numbers should not trust cost estimates and cost-benefit analyses produced by project promoters and their analysts.

- by Bent Flyvbjerg
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- Critical Theory, Business, Entrepreneurship, Organizational Behavior

In this study, a significant literature review on peak load shaving strategies has been presented. The impact of three major strategies for peak load shaving, namely demand side management (DSM), integration of energy storage system (ESS), and integration of electric vehicle (EV) to the grid has been discussed in detail. Discussion on possible challenges and future research directions for each type of the strategy has also been included in this review. For the energy storage system, different technologies used for peak load shaving purpose, which include their methods of operation and control have been elaborated further. Finally, the sizing of the ESS storage system is discussed. For the demand side management system, various management methods and challenges associated with DSM implementation have been thoroughly explained. A detailed discussion on the electric vehicle strategy has also been included in the review, which considers the integration, control and operation techniques for implementing the peak load shaving.

- by Moslem Uddin
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- Renewable Energy, Electric Vehicles, Microgrid, Demand Response
- by Mark Bergen and +1
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- Strategic Management, Applied Economics, Demand Side Management, Competitive Analysis

The paper provides a review of the incentives and barriers of a successful adoption of innovative energy services (IES) in the energy market. Although IES can have different attributes and roles, they still have a lot in common with each other. On the other hand, the literature suggests that to achieve large market penetration rates of IES, the consumers must be firstly aware of them. They must be also supported by the access to reliable information and advice to limit their confusion of choice. The perceived difficulty of adoption has to be reduced to encourage consumers to get interested in the services. Also the distribution channels of the innovations, namely social influence in the consumers' social networks and advertisement in mass-media should be effectively used to boost the diffusion. We analyze a great number of research studies, field experiments and mathematical models in order to firstly summarize the findings related to incentives and barriers of IES adoption among customers, then to recognize recent trends in examining these services and modeling and finally to propose some strategies that could boost the diffusion of IES. We argue that to overcome the barriers of adoption, the entities involved in creating and offering IES (e.g. policy makers, energy suppliers and power system operators) should find a way to offer and promote these services together. Such a strategy can bring a synergic effect and increase the financial and non-financial benefits to the consumers and hence increase their interest and engagement.

Având originile în logistică, managementul lanţului de aprovizionare / distribuţie (SCM) este un concept larg ce acoperă toate aspectele manageriale ale fluxurilor informaţionale şi fizice de la producător la consumatorul final, fiind cuprinse astfel operaţiunile de manevrare a produselor, transportul acestora de-a lungul canalului de distribuţie al firmei. În turism, aceste aspecte se referă la întregul proces al asigurării serviciilor turistice, de la aprovizionare (cu materii prime, produse sau servicii diverse), la prestare şi distribuţie, iar performanţa SCM poate fi în final evaluată prin satisfacţia clienţilor. Astfel, o componentă importantă a SCM în turism o reprezintă managementul cererii.
Din aceste considerente, prezentul studiu îşi propune să scoată în evidenţă adaptarea conceptului de SCM şi ale managementului cererii în turism, cu o particularizare pe un lanţ hotelier din România, pe baza unei cercetări şi analize a indicatorilor de trafic turistic, precum şi a evaluărilor satisfacţiei clienţilor. Informaţiile utilizate sunt oferite atât de statisticile interne ale societăţii comerciale analizate, cât şi de diverse portaluri de rezervări hoteliere care oferă şi feedback-ul clienţilor. Rezultatele studiului oferă o imagine a modului în care managementul cererii hoteliere poate influenţa performanţele SCM în turism.

- by Calaretu Bogdan
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- Supply Chain Management, Demand Side Management

The common driver of the 'green-warehouse' strategy is based on the reduction of energy consumption. In warehouses with 'picker-to-part' operations the minimization of energy due to material handling activities can be achieved by means of different policies: by adopting smart automatic picking systems, by adopting energy-efficient material handling equipment (MHE) as well as by identifying flexible layouts. In most cases, these strategies require investments characterized by high pay-back times. In this context, management strategies focused on the adoption of available equipment allow to increase the warehouse productivity at negligible costs. With this purpose, an optimization model is proposed in order to identify an optimal control strategy for the battery charging of a fleet of electric mobile MHE (e.g., forklifts), allowing minimizing the economic and environmental impact of material handling activities in labor-intensive warehouses. The resulting scheduling problem is formalized as an integer programming (IP) problem aimed at minimizing the total cost, which is the sum of the penalty cost related to makespan over all the material handling activities and the total electricity cost for charging batteries of MHE. Numerical experiments are used to investigate and quantify the effects of integrating the scheduling of electric loads into the scheduling of material handling operations.

- by Francesco Facchini and +1
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- Integer Programming, Optimization techniques, Energy Management, Demand Side Management

Permintaan adalah salah satu aspek yang penting dalam ekonomi manajerial, karena perusahaan tidak akan ada dan berkembang jika tidak ada permintaan terhadap produknya. Kita juga memperkenalkan konsep elastisitas. Yaitu mengukur kepekaan perubahan dalam kuantitas yang diminta terhadap perubahan dari setiap faktor-faktor yang memengaruhi permintaan.

Megaproject Planning and Management: Essential Readings contains the seminal articles from the growing body of research on megaproject planning and management along with an original introduction by the editor, Bent Flyvbjerg. The leading and most cited authority in the field, Flyvbjerg has used crowdsourcing and 25 years of experience to cherry-pick from several hundred articles and books the writings that define the field. This volume will be an indispensable source for those wishing to speak with authority about how megaprojects are prepared, delivered, and fought over. The target audience is students, academics, practitioners, and media pundits alike, as well as communities affected by megaprojects.

- by Bent Flyvbjerg
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- Critical Theory, Entrepreneurship, Organizational Behavior, Information Systems
- by Philip Southey
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- Supply Chain Management, Operations Management, Manufacturing, Logistics
- by Adnan Kisa
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- Health Economics, Economic Policy Evaluation, Primary Health Care, Health Outcomes

Back cover text: Megaprojects and Risk provides the first detailed examination of the phenomenon of megaprojects. It is a fascinating account of how the promoters of multi-billion dollar megaprojects systematically and self-servingly misinform parliaments, the public and the media in order to get projects approved and built. It shows, in unusual depth, how the formula for approval is an unhealthy cocktail of underestimated costs, overestimated revenues, undervalued environmental impacts and overvalued economic development effects. This results in projects that are extremely risky, but where the risk is concealed from MPs, taxpayers and investors. The authors not only explore the problems but also suggest practical solutions drawing on theory, experience and hard, scientific evidence from the several hundred projects in twenty nations and five continents that illustrate the book. Accessibly written, it will be the standard reference for students, scholars, planners, economists, auditors, politicians and interested citizens for many years to come.

- by Bent Flyvbjerg
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- Critical Theory, Business, Entrepreneurship, Entrepreneurship

Energy management systems are designed to monitor, optimize, and control the smart grid energy market. Demand-side management, considered as an essential part of the energy management system, can enable utility market operators to make better management decisions for energy trading between consumers and the operator. In this system, a priori knowledge about the energy load pattern can help reshape the load and cut the energy demand curve, thus allowing a better management and distribution of the energy in smart grid energy systems. Designing a computationally intelligent load forecasting (ILF) system is often a primary goal of energy demand management. This study explores the state of the art of computationally intelligent (i.e., machine learning) methods that are applied in load forecasting in terms of their classification and evaluation for sustainable operation of the overall energy management system. More than 50 research papers related to the subject identified in existing literature are classified into two categories: namely the single and the hybrid computational intelligence (CI)-based load forecasting technique. The advantages and disadvantages of each individual techniques also discussed to encapsulate them into the perspective into the energy management research. The identified methods have been further investigated by a qualitative analysis based on the accuracy of the prediction, which confirms the dominance of hybrid forecasting methods, which are often applied as metaheurstic algorithms considering the different optimization techniques over single model approaches. Based on extensive surveys, the review paper predicts a continuous future expansion of such literature on different CI approaches and their optimizations with both heuristic and metaheuristic methods used for energy load forecasting and their potential utilization in real-time smart energy management grids to address future challenges in energy demand management.

- by Seyedeh Narjes Fallah and +1
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- Artificial Intelligence, Machine Learning, Renewable Energy, Energy efficiency

The article first describes characteristics of major infrastructure projects. Second, it documents a much neglected topic in economics: that ex ante estimates of costs and benefits are often very different from actual ex post costs and benefits. For large infrastructure projects the consequences are cost overruns, benefit shortfalls, and the systematic underestimation of risks. Third, implications for cost–benefit analysis are described, including that such analysis is not to be trusted for major infrastructure projects. Fourth, the article uncovers the causes of this state of affairs in terms of perverse incentives that encourage promoters to underestimate costs and overestimate benefits in the business cases for their projects. But the projects that are made to look best on paper are the projects that amass the highest cost overruns and benefit shortfalls in reality. The article depicts this situation as ‘survival of the unfittest’. Fifth, the article sets out to explain how the problem may be solved, with a view to arriving at more efficient and more democratic projects, and avoiding the scandals that often accompany major infrastructure investments. Finally, the article identifies current trends in major infrastructure development. It is argued that a rapid increase in stimulus spending, combined with more investments in emerging economies, combined with more spending on information technology is catapulting infrastructure investment from the frying pan into the fire.

- by Bent Flyvbjerg
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- Critical Theory, Business, Entrepreneurship, Organizational Behavior

Businesses must use their resources optimum in order to minimize their costs. Thus, it is important to prepare the strategic plans made as the closest to the truth. Furthermore, in order their works to be sustainable, the companies should plan the future not the present; must take necessary measures to manage the cost of the inventory, labor, time, and financial resources in the best way and to avoid wastage. Demand forecasting systems, besides providing the company keeping up with changing market conditions easily, provides convenience to the company in operational applications with its strategic and managerial level plans. As the demand forecasting performance goes down, the rate of fulfillment the demands of the customer on time goes down. As a result, the companies head for accelerated services with quickly obtainable results, and other costly actions.
The starting point of short-and long-term plan is the forecast demand. Also, as the deviations in long-term plans are high, the determination of the control frequency and methods of the plans are very significant for a successful demand forecasting system. No matter how successful strategic plannings are done, the mistakes in the practice can drag all of the plans towards failure. Therefore, in our study, numerical and non-numerical of demand forecast models will be referred, and there will be comments about a demand forecasts method in a business with the case analysis method and suggestions for improvement.

- by BATUHAN KOCAOĞLU and +1
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- Production Planning, Demand Side Management, Demand Forecasting

The Handbook responds to the growing need to balance supply-side and demand-side
approaches to managing scarce water resources in catchments and river basins. It recognises
that a plethora of research and methodologies are readily available to assist planners and
managers to assess water resource availability in a catchment yet little is available to assist in
assessing water demand and use. The Handbook therefore aims to fill this gap by bringing
together a range of methodologies, examples of their application, supporting information and
key references.
The Handbook is aimed at professionals and practitioners in the southern African region. It
provides the user with a range of appropriate methods for estimating water demand and use
across a range of water uses including environmental, urban, industrial, rural domestic and
agricultural sectors. Guidance on the advantages and disadvantages of different assessment
techniques are provided and the texts supplemented by worked examples. Methods suitable
for forecasting long-term water demand and use are also included.

Thermal energy storage (TES) is widely recognized as a means to integrate renewable energies into the electricity production mix on the generation side, but its applicability to the demand side is also possible. In recent decades, TES systems have demonstrated a capability to shift electrical loads from high-peak to off-peak hours, so they have the potential to become a powerful instrument in demand-side management programs (DSM). Thermal storage is a technology that ensures energy security, efficiency and environmental quality. Of particular interest are applications where TES systems help manage the mismatch between availability of renewable electricity and the demand for electricity in buildings where hot water, heating and cooling are delivered by heat pumps and air conditioning for example. Thus this paper demonstrates the state of the art of present applications of thermal storage for demand-side management. A particular focus of this work is the attention paid to the characteristics of DSM and their relationship to different thermal storage systems. If TES effectiveness for the abovementioned applications is demonstrated, TES devices have a small percentage of the potential market. Therefore challenges and guidelines for a development plan are suggested.

- by Fabio Polonara
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- Engineering, Economics, Renewable Energy, Energy Security

- by Chris Ogwumike and +1
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- Decision Support Systems, Smart Grid, Demand Side Management, Energy Optimization

A thorough and exhaustive review of relevant literature and associated works is carried out to critically examine energy poverty in Nigeria with respect to ownership and income. Using the desktop approach and empirical formulas, the persistent failure of public infrastructure like healthcare, education and security to the poor electricity generation, transmission and distribution capacity in the country is examined; alongside current government contribution to buoying our generation capacity and electricity access through policies and investment. The findings of the review reveal the urgent need for the smart roll out of distributed generation units in order to stimulate and encourage the ongoing diversification of the economy and also the need for a sustainable road map that incorporates the successes of countries faced with similar challenges. This review paper also proposes the need for palliatives in form of subsidized solar home systems (SHSs) through a sustainable and economically viable means for off grid homes to assuage the effects of non-availability of grid electricity.

- by Chukwuka G Monyei
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- Engineering, Economics, Alternative Energy, Demand Side Management

GESTION ACTIVA DE LA DEMANDA-BENEFICIOS POTENCIALES DE UN PROGRAMA DE RESPUESTA A LA DEMANDA EN EL SECTOR RESIDENCIAL CASO DE ESTUDIO: SECTOR RESIDENCIAL VILLA OLGA, SANTIAGO. Un proyecto presentado como requisito parcial para optar por... more

- by Ramón Emilio De Jesús Grullón and +1
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- Renewable Energy, Energy, Demand Response, Demand Side Management

A coordinated centralized energy management system (ConCEMS) is presented in this paper that seeks to integrate for optimal grid operation—the supply side energy management system (SSEMS), home energy management system (HEMS) and transmission line management system (TLMS). ConCEMS in ensuring the optimal operation of an IEEE 30-bus electricity network harmonizes the individual objective function of SSEMS, HEMS and TLMS to evolve an optimal dispatch of participating demand response (DR) loads that does not violate transmission line ampacity limits (TLMS constraint) while minimizing consumer cost (HEMS constraint) and supply side operations cost (SSEMS constraint). An externally constrained genetic algorithm (ExC-GA) that is influenced by feedback from TLMS is also presented that intelligently varies the dispatch time of participating DR loads to meet the individual objective functions. Hypothetical day ahead dynamic pricing schemes (Price1, Price2 and Price3) have also been adopted alongside an existing time of use (Price0) pricing scheme for comparison and discussion while a dynamic thermal line rating (DTLR) algorithm has also been incorporated to dynamically compute power limits based on real time associated data.

- by Holger Wallbaum
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- Demand Side Management