Maximum Peak Demand Research Articles

Day-ahead optimal scheduling considering thermal and electrical energy management in smart homes with photovoltaic–thermal systems

The environmental impact on the energy sector has become a significant concern, necessitating the implementation of Home Energy Management Systems (HEMS) to enhance the energy efficiency of buildings, reduce costs and greenhouse gas emissions, and ensure user comfort. This paper presents a novel approach to provide optimal day-ahead energy management plans in smart homes with Photovoltaic/Thermal (PVT) systems, aiming to achieve a balance between energy cost and user comfort. This multi-objective problem employs the Non-dominated Sorting Genetic Algorithm III as the optimization algorithm and the Nonlinear Auto-regressive with External Input to forecast the day-ahead meteorological variables, which serve as inputs to predict the PVT electrical and heat production in the thermal resistance model. The HEMS benefits from the time-of-use tariff due to the flexibility provided by the energy storage from a battery bank and a boiler. Furthermore, it performs a load scheduling for 10 controllable loads based on three feature parameters to characterize occupant behavior. A study case analysis revealed a cost reduction of approximately 66% in the solution close to the knee of the Pareto curve (S3 solution). The environmental impact on the energy sector has become a The PVT heat production was sufficient to meet the thermal demand of the showers. The proposed hybrid battery management model effectively eliminated the export of electricity to the grid, reducing consumption during peak periods and the maximum peak demand.

Coordinated control strategy assessment of a virtual power plant based on electric public transportation

With the rapid development of the public transportation industry in recent years, electric public transportation (EPT) with regular operating times and fixed load demands has considerable potential for energy storage. Aiming to solve the problem of insufficient large-scale energy storage and ensure renewable energy development, this study builds the dynamic simulation model of a virtual power plant (VPP) consisting of EPT groups, large-capacity public distributed generations (PDGs) containing a photovoltaic (PV) unit, and a coal-fired unit. Then, the coordinated control strategy, which includes the time-sharing plan part and execution part with multi-section, is proposed to make a trade-off between maximizing the utilization of EPT and ensuring the operational stability of VPP. The control strategy includes two modes (1) gaining benefits through electricity tariff differences and participation in the carbon trading market and (2) peak shaving the consumption of VPP using off-peak grid power. Moreover, the evaluation model related to the control performance and achievement of targets is established. The influence of the EPT number on benefits and peak shaving capability is compared. Results show that the optimal number of EPT for the system is the value at which the energy storage utilization is maximum at the specific period. The optimal daily benefit is 37,300–83,700 yuan, and the optimal daily discharge value is 117.77 MW·h when the maximum peak demand reduction is 38.31 MW. Overall, the proposed strategy makes full use of the energy storage potential of EPT groups, which provide technical support for maintaining grid security and achieving the dual‑carbon target.

Analysis of Energy Sector of Bangladesh’s to Ensure the Route of Vision 2041

Energy is a major driving force for economic and socio-economic development of a country. Throughout the last decade Power & Energy Sector of Bangladesh has been undergone unprecedented transition towards realizing its targets set for achieving Visions (2021 & 2041). Keeping pace with the economic growth, all out efforts have been undertaken in Power & Energy Sector. As Per successful implementation of PP 2021 and MDGs, the power and energy sector targets of PP2041 and SDG7 are reasonably expected to be realized in due course. The sector is moving towards achieving long term targets to ensure energy sustainability 33,000 MW plant generation capacity, maximum peak demand 29,300 MW (in 2030), and 56,734 MW plant generation capacity, maximum peak demand 51,300 MW (in 2041). This is an appropriate time to review the achievements so far. The main objective of this research paper is to analyze the performance of the energy sector over the last decade in order to identify the areas of weaknesses and challenges and to present a set of recommendations on long term sustainability. From methodological point of view, the current practice is to analyze a gap in the sector aimed at identifying weaknesses. Therefore, this study focuses on the following issues in the energy sector of Bangladesh’s to ensure the route of vision 2041: (i) Perspective Plan 2041 for Energy Sector in Bangladesh; (ii) Present status of Electricity Generation in energy sector of Bangladesh (iii) Energy Pricing and Policy in Bangladesh (iv) Major Initiatives in Energy Sectors of Bangladesh (v) Challenges faced by vision 2041 in energy sector of Bangladesh. Energy plays an important role in the development and security of any country, poverty eradication, economic growth and sustainable infrastructure. Therefore, future economic growth will depend significantly on the availability of electricity.

Passive Cooling in the System of a Heat Pump with a Vertical Ground Collector

Heat pumps from more than ten years are known as an alternative source of thermal energy. They are primarily used for central heating and domestic hot water preparation. Next to the solar collectors, they are the cheapest and easiest way to save energy. But heat pump can also be used for cooling. Heat can spontaneously flow from a colder to a hotter body. Flows from a body with a higher temperature to a body with a lower temperature are commonly known as the second law of thermodynamics. The heat pump pulled out of cooler ambient heat which may be used for central heating or for domestic hot water. There are many types of cooling pumps. This depends mainly on the type of pump, and actually kind of heat source that can be used in two ways: as a heat receiving surface - or as a source of cooling for utilization. Knowing the general principle of operation of the pump, we can introduce innovative technologies that allow more devices to reduce the operating costs. In this solution, the heat pump installation, initially designed only for heating or, ultimately, also for cooling purposes, enables the use of a system that will be based on the part of the installation associated with the lower heat source, but not as a source of heat but as a source of coolness. This system is often referred to as “natural cooling” or as a passive cooling system. In such a system, during the production of chilled water, a significant reduction in production costs is obtained due to the lack of energy consumption for the drive of refrigeration compressors, and only the use of circulation pumps for the lower and upper circulation of the heat source. The disadvantage of this solution is the limitation resulting from the situation of close connections between ground temperature and chilled water temperature in the supply, which causes the limitation of its use for the period beyond the maximum peak demand for cold in the cooling season, i.e. most often at the highest outside temperatures. Thanks to the economical use of electricity, we can contribute to protect the environment.

Analyzing the impact of small solar water heating systems on peak demand and on emissions in the Brazilian context

Abstract This study presents a methodology to measure the impact of solar heating systems, on reducing peak demand and on avoided emissions, when applied in low-income housing projects. To this end, a real-time monitoring system was implemented over a year in five clusters representative of a heterogeneous socioeconomic context in new housing subsidized with solar water heating system through the national program “My House, My Life”. The results showed an expressive contribution of the system in reducing the maximum peak demand, obtaining, on average, a 64% reduction in relation to the electric showerhead, predominantly used in the country. The cumulative energy savings of 577 kWh per year resulted in an average of 250 kgCO2 avoided per housing unit. The extrapolation of the data to 224,000 units already delivered by the national program would result in an economy of 56,089 tCO2 per year. This study demonstrates the importance of measurement as a strategic tool in public policies for energy efficiency and in the estimation of emissions associated with greenhouse gases. The solar heating system positions itself as an important energy efficiency policy for Brazil, which minimizes the demand for thermoelectric plants during peak hours and postpones investments with new power generation plants.

Use of Load Shedding Scheme to Increase the Capacity Limit on the Single Largest Generator

This paper examines the stability of the Sri Lankan power system with the emergence of the large coal power plants. Such coal power plants are being introduced to Sri Lanka with the aim of bringing down electricity costs. Sri Lanka at present has a maximum peak demand of around 2100 MW with an off peak demand of being a low of nearly 900 MW during the early hours of the morning. It is in such a backdrop that a large coal power plant of 300 MW has been introduced to Sri Lanka intended to run as base load. Due to reasons of current practice, the capacity limit of the single largest generator is set at 20% of the instantaneous system demand. Thus underutilization of the coal power plant would occur during the off peak hours. This paper looks into ways of increasing the 20% limit up to an amount such that the coal power plant could be used to full capacity even during off peak hours. The 220 kV and part of the 132 kV transmission system of Sri Lankan power system has been modeled on PSCAD software, taking into account the various parameters of power stations and transmission lines. With the use of the software, contingency situations have been analyzed and the load shedding scheme currently being used by the CEB is revised such that the limit placed on the single largest generator could be increased to 25% of the current demand. ENGINEER, Vol. 46, No. 01, pp. 31-36, 2013

Building load management using cluster and statistical analyses

Building energy management systems has become very significant to monitor and control loads, mainly due to the tariff and demand side management programs. This technology allows the performance of key energy management functions such as organizing energy use data, identifying energy consumption anomalies, managing energy costs, and automating demand response strategies. Load management techniques allow the energy manager to reshape the building load curve and reduce the peak demand. The synthesis of load shapes is one of the most critical steps in evaluating load management programs. The energy manager should be able to recognize the typical shape of the daily load curve in order to manage the energy use. This paper presents a methodology to perform the synthesis of load shapes. On that purpose, it is essential to identify typical daily load curves as well as the best way to find their representative model. By getting to know the typical load curves of a building, an energy manager may predict load and peak demands. Results have shown the efficiency of clustering technology in the analysis of time series data such as load curves. Using historical data, the total accumulated energy in the end of the day as well as the maximum peak demand of the day may be predicted.

Demand side management for water heating installations in South African commercial buildings

The largest percentage of the sanitary hot water used in South African buildings is heated by means of direct electrical resistance heaters. This is one of the major contributing factors of the undesirable high morning and afternoon peaks imposed on the national electricity supply grid. Water heating therefore continues to be of concern to ESKOM, the country's only electrical utility company. The so-called in-line water heating system design methodology was developed to address this problem. This paper investigates the potential impact of in-line systems on the national peak electrical demand. A computer simulation model was developed that combines a deterministic mathematical model with a statistical approach in order to predict the diversity factors associated with both the existing and in-line design methodologies. A study was also conducted to estimate the total installed water heating capacity in the national commercial building sector. This figure can be combined with the simulated diversity factor to determine the peak electrical demand. The deterministic model includes the detailed simulation of the hot water storage vessel, the electrical heater and the system control algorithm. The mathematical model for the storage vessel is based on an electrical analogue approach that includes the effects of conduction as well as forced and natural convection. This model was verified extensively with the aid of laboratory measurements and compared with existing storage vessel models. It was found that the new storage vessel model could predict the supply temperature within 2 per cent for a system configuration with the heater in parallel outside the reservoir and within 12 per cent for a configuration with the heater situated inside the reservoir. This compares favourably with existing models found in the literature. The complete simulation based on the statistical approach showed that extensive application of the new design methodology could result in a reduction of approximately 75 MW in the total maximum peak demand imposed on the electricity supply grid in wintertime. This is 58 per cent of the current peak demand due to commercial water heating and 12.5 per cent of the peak load reduction target set by ESKOM until the year 2015. Copyright © 2001 John Wiley & Sons, Ltd.

Long‐Term Load Forecasting Using Grey System Theory

AbstractSupply and demand in power system planning and operation is required to be balanced. An operational reserve for protection against faults or accidental demands also is required. Therefore load forecasting is one of the most important fields and various load forecasting methods have been applied.In this paper the grey system theory which mats uncertain information is applied to the long‐term load forecasting from three aspects: the point prediction; the interval prediction; and the topological forecasting. In the point prediction, the annual total demand is predicted, in the interval prediction, the annual peak demand is predicted, and in the topological forecasting, the date where a yearly maximum peak demand would occur is predicted. The grey dynamic model (abbreviated as GM model) is adopted as the predicted model. The GM model is a differential equation model which is different from most forecasting models. The GM model is quite powerful when combined with the preliminary transformation called the accumulated generating operation (AGO).This paper proposes a new method for the long‐term load‐forecasting problems involving uncertainty. The predicted results have been found to be very satisfactory. The grey system theory is a new tool which is very efficient for load forecasting.

Grey System理論を用いた長期需要想定

Supply and demand in power system planning and operation is required to be balanced. An operational reserve for protection against faults or accidental demands also is required. Therefore load forecasting is one of the most important fields and various load forecasting methods have been applied. In this paper the grey system theory which mats uncertain information is applied to the long-term load forecasting from three aspects: the point prediction; the interval prediction; and the topological forecasting. In the point prediction, the annual total demand is predicted, in the interval prediction, the annual peak demand is predicted, and in the topological forecasting, the date where a yearly maximum peak demand would occur is predicted. The grey dynamic model (abbreviated as GM model) is adopted as the predicted model. The GM model is a differential equation model which is different from most forecasting models. The GM model is quite powerful when combined with the preliminary transformation called the accumulated generating operation (AGO). This paper proposes a new method for the long-term load-forecasting problems involving uncertainty. The predicted results have been found to be very satisfactory. The grey system theory is a new tool which is very efficient for load forecasting.

Tools for the Workshop

IT is well known that the spot welding of light alloys of inherently high electrical conductivity involves several problems necessitating the use of specialized high capacity machines giving close control of the heat‐pressure cycle, and designed to give rapid electrode follow‐up, i.e. permitting the electrodes to follow closely the cooling and contracting weld. What is not so well appreciated is the disproportionate increase in energy required to weld satisfactorily material of increasing thickness. For example, the energy for welding an included thickness of 2 x 10 S.W.G. or 2 x 8 S.W.G. sheet under production conditions is so great that it precludes the use of the conventional A.C. transformer type of welder except under very favourable supply conditions. It is estimated in fact that a maximum peak demand of at least 1,000 kVA single phase, would be imposed upon the supply mains by an A.C. machine of suitable capacity.