scholarly journals Integration of demand side and supply side energy management resources for optimal scheduling of demand response loads – South Africa in focus

2018 ◽  
Vol 158 ◽  
pp. 92-104 ◽  
Author(s):  
C.G. Monyei ◽  
A.O. Adewumi
Keyword(s):  
South Africa ◽  
Energy Management ◽  
Demand Response ◽  
Optimal Scheduling ◽  
Supply Side ◽  
Demand Side

scholarly journals An Energy Management Optimization Method for Community Integrated Energy System Based on User Dominated Demand Side Response

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4398
Author(s):  
Yiqi Li ◽  
Jing Zhang ◽  
Zhoujun Ma ◽  
Yang Peng ◽  
Shuwen Zhao
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Value At Risk ◽  
Operating Cost ◽  
Optimization Method ◽  
Conditional Value At Risk ◽  
Demand Side ◽  
Scheduling Model ◽  
Management Optimization ◽  
Demand Side Response

With the development of integrated energy systems (IES), the traditional demand response technologies for single energy that do not take customer satisfaction into account have been unable to meet actual needs. Therefore, it is urgent to study the integrated demand response (IDR) technology for integrated energy, which considers consumers’ willingness to participate in IDR. This paper proposes an energy management optimization method for community IES based on user dominated demand side response (UDDSR). Firstly, the responsive power loads and thermal loads are modeled, and aggregated using UDDSR bidding optimization. Next, the community IES is modeled and an aggregated building thermal model is introduced to measure the temperature requirements of the entire community of users for heating. Then, a day-ahead scheduling model is proposed to realize the energy management optimization. Finally, a penalty mechanism is introduced to punish the participants causing imbalance response against the day-ahead IDR bids, and the conditional value-at-risk (CVaR) theory is introduced to enhance the robustness of the scheduling model under different prediction accuracies. The case study demonstrates that the proposed method can reduce the operating cost of the community under the premise of fully considering users’ willingness, and can complete the IDR request initiated by the power grid operator or the dispatching department.

scholarly journals AN OPTIMISATION APPROACH TOWARD ONBOARD ENERGY MANAGEMENT SYSTEMS: MODELLING AND SIMULATION OF SUPPLY SIDE

2012 ◽  
Vol 11 (1) ◽  
pp. 1
Author(s):  
HADI SUROSO ◽  
ONTOSENO PENANGSANG
Keyword(s):  
Energy Management ◽  
Economic Dispatch ◽  
Operating Cost ◽  
Electric Power System ◽  
Management Systems ◽  
Supply Side ◽  
Optimization Approach ◽  
Demand Side ◽  
Cost Index ◽  
Energy Management Systems

Optimization in the operation of electric power system is an important task for both inland and onboard. The objective is to minimize operating cost index. Taking advantage of thescheme that onboard operator has the authority not only in the supply side but also in the demandside, an optimization approach toward onboard energy management systems based onintegrated model for supply and demand side is being developed. The model utilizes unit commitmentand economic dispatch in the supply side and load management based on multipleattribute decision-making in the demand side. As a part of the whole concept, this paper focuseson the modeling and simulation of demand side. A user friendly demand side model consistingof Unit Commitment and Economic Dispatch is developed by using LabVIEW, LaboratoryVirtual Instrument Engineering Workbench. Data taken from 3 units of Steam Power Plantare simulated. It is then eventually confirmed that 9% total cost saving can be achieved in theselected load demand range

scholarly journals A review of electrical energy management techniques: supply and consumer side (industries)

2009 ◽  
Vol 20 (3) ◽  
pp. 14-21 ◽  
Author(s):  
Afua Mohamed ◽  
Mohamed Tariq Khan
Keyword(s):  
Energy Management ◽  
Electrical Energy ◽  
Load Control ◽  
Supply Side ◽  
Demand Side ◽  
Interruptible Load ◽  
Direct Load Control ◽  
Management Techniques ◽  
Power Utilities ◽  
Demand Control

A review of electrical energy management tech-niques on the supply side and demand side is pre-sented. The paper suggests that direct load control, interruptible load control, and time of use (TOU) are the main load management techniques used on the supply side (SS). The supply side authorities normally design these techniques and implement them on demand side consumers. Load manage-ment (LM) initiated on the demand side leads to valley filling and peak clipping. Power factor correc-tion (PFC) techniques have also been analysed and presented. It has been observed that many power utilities, especially in developing countries, have neither developed nor implemented DSM for their electrical energy management. This paper proposes that the existing PFC techniques should be re-eval-uated especially when loads are nonlinear. It also recommends automatic demand control methods to be used on the demand side in order to acquire optimal energy consumption. This would lead to improved reliability of the supply side and thereby reducing environmental degradation.

scholarly journals Development of Optimized Methodology for Improvement Domestic Energy Management

2019 ◽  
Vol 8 (4) ◽  
pp. 5288-5294
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Wind Speed ◽  
Energy Management ◽  
Electrical Energy ◽  
Supply Side ◽  
Demand Side ◽  
Load Schedule ◽  
The Cost ◽  
Daily Load

Electrical energy management (EEM) is an object that has proceeds appointed importance in the 21 th - century in order to its assistance to economic development and ecological ascertainment. “EEM” may be perfected on the supply side “(SS)” or demand side “(DS)”. On the supply side, “EEM” is cultivated when: There is an outgrowth desire “(demand requirement is higher than supply)”. “EEM” assists to suspend the design a resent generation station. On the “DS”, “EEM” is used to minimize the cost of electrical energy consumption and the interrelated forfeitures. The technique utilized for “EEM” is demand side load management that plan at ending valley filling, peak clipping and strategic preservation of electrical systems [1]. Seeming new inventions like “distributed generation (DG)”, “distributed storage (DS)” and “DSLM” will modify the method we use and generate energy. A smart grid (SG) is an electrical network that manages electricity demand in an unstoppable sustainable, reliable and economic manner. A smart grid uses smart net meters to overcome the sickliness of traditional electrical grid. “(DSM)” is a vital advantage of “(SG)” to progress power efficiency, minimize the peak average load and minimize the cost. From basic purposes of DSM is shifting load from peak hours to off-peak hours and reducing consumption during peak hours. Generally, a deregulated grid system is considered where the retailer purchases electricity from the electricity market to cover the end users’ energy need. In this research, Demand Side Management (DSM) techniques (load shifting and Peak clipping) are used to maximize the profit for Retailer Company by reducing total power demand pending peak demand periods and achieve an optimal daily load schedule using linear programming method and Genetic Algorithm. This method is performed on the 69-bus radial network. Also, a short term Artificial Neural Network technique is used to get forecasted wind speed, solar radiation and forecasted users load for date 15-Aug-2019. The neural network here uses an actual hourly load data, actual hourly wind speed and solar radiation data. Then the forecasted data is used in the optimization to get optimal daily load schedule to maximize the profit for Retailer Company. Then comparison between profit using linear programing and genetic algorithm are made. The optimized DSM succeeded to maximize the profits of the company.

scholarly journals Two-Stage Optimization Model for Two-Side Daily Reserve Capacity of a Power System Considering Demand Response and Wind Power Consumption

2019 ◽  
Vol 11 (24) ◽  
pp. 7171 ◽  
Author(s):  
Jun Dong ◽  
Anyuan Fu ◽  
Yao Liu ◽  
Shilin Nie ◽  
Peiwen Yang ◽  
...  
Keyword(s):  
Power Consumption ◽  
Wind Power ◽  
Demand Response ◽  
Optimization Model ◽  
Reserve Capacity ◽  
Supply Side ◽  
Compensation Mechanism ◽  
Demand Side ◽  
Clustering Method ◽  
Wind Curtailment

Today, wind power is becoming an important energy source for the future development of electric energy due to its clean and environmentally friendly characteristics. However, due to the uncertainty of incoming wind, the utilization efficiency of wind energy is extremely low, which means the problem of wind curtailment becomes more and more serious. To solve the issue of wind power large-scale consumption, a two-stage stochastic optimization model is established in this paper. Different from other research frameworks, a novel two-side reserve capacity mechanism, which simultaneously takes into account supply side and demand side, is designed to ensure the stable consumption of wind power in the real-time market stage. Specifically, the reserve capacity of thermal power units is considered on the supply side, and the demand response is introduced as the reserve capacity on the demand side. At the same time, the compensation mechanism of reserve capacity is introduced to encourage generation companies (GENCOs) to actively participate in the power balance process of the real-time market. In terms of solution method, compared with the traditional k-means clustering method, this paper uses the K-means classification based on numerical weather prediction (K-means-NWP) scenario clustering method to better describe the fluctuation of wind power output. Finally, an example simulation is conducted to analyze the influence of reserve capacity compensation mechanism and system parameters on wind power consumption results. The results demonstrate that with the introduction of reserve capacity compensation mechanism, the wind curtailment quantity of the power system has a significant reduction. Besides, the income of GENCOs is gradually increasing, which motivates their enthusiasm to provide reserve capacity. Furthermore, the reserve capacity mechanism designed in this paper promotes the consumption of wind power and the sustainable development of renewable energy.

scholarly journals Implementation of Advanced Demand Side Management for Microgrid Incorporating Demand Response and Home Energy Management System

2018 ◽  
Vol 3 (4) ◽  
pp. 50 ◽  
Author(s):  
Izaz Zunnurain ◽  
Md. Maruf ◽  
Md. Rahman ◽  
GM Shafiullah
Keyword(s):  
Energy Management ◽  
Demand Response ◽  
Energy Cost ◽  
Energy Savings ◽  
Energy Management System ◽  
Demand Side ◽  
Case Study Analysis ◽  
Home Energy Management ◽  
Home Energy Management System

To facilitate the possible technology and demand changes in a renewable-energy dominated future energy system, an integrated approach that involves Renewable Energy Sources (RES)-based generation, cutting-edge communication strategies, and advanced Demand Side Management (DSM) is essential. A Home Energy Management System (HEMS) with integrated Demand Response (DR) programs is able to perform optimal coordination and scheduling of various smart appliances. This paper develops an advanced DSM framework for microgrids, which encompasses modeling of a microgrid, inclusion of a smart HEMS comprising of smart load monitoring and an intelligent load controller, and finally, incorporation of a DR strategy to reduce peak demand and energy costs. Effectiveness of the proposed framework is assessed through a case study analysis, by investigation of DR opportunities and identification of energy savings for the developed model on a typical summer day in Western Australia. From the case study analysis, it is evident that a maximum amount of 2.95 kWh energy can be shifted to low demand periods, which provides a total daily energy savings of 3%. The total energy cost per day is AU$2.50 and AU$3.49 for a house with and without HEMS, respectively. Finally, maximum possible peak shaving, maximum shiftable energy, and maximum standby power losses and energy cost savings with or without HEMS have been calculated to identify the energy saving opportunities of the proposed strategy for a microgrid of 100 houses with solar, wind, and a back-up diesel generator in the generation side.

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