A Review on Demand Side Management Applications, Techniques, and Potential Energy and Cost saving

Shalaby, Hossam Eldin Hamed

doi:10.11113/elektrika.v20n1.248

Cited by 6 publications

(1 citation statement)

References 52 publications

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“…According to prior research, energy efficiency (EE) and demand response (DR) are the most reliable, costeffective, and efficient ways to influence the demand curve. Conventionally, there are six DSM strategies available in the DR program [21]. For example, Load shifting declines demand during on-peak hours by shifting load to off-peak hours.…”

Section: Dsm Strategiesmentioning

confidence: 99%

Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm

Sulaima

Baharin

Kadir

et al. 2022

IJEECS

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<span>A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed where the maximum load shifting weightage was set up to 30% to reflect the consumers’ effort towards energy efficiency (EE) program. The previously proposed TOU design was identified to be a suitable structure that can promote balancing of EE and demand response (DR) program effort in most consumers' houses category in Malaysia.</span>

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Section: Dsm Strategiesmentioning

confidence: 99%

Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm

Sulaima

Baharin

Kadir

et al. 2022

IJEECS

View full text Add to dashboard Cite

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Impacts of multiple demand-side management strategies on microgrids planning: a literature survey

Elazab,

Abdelnaby,

Ali

2024

Clean Energy

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Demand-side management (DSM) schemes play a crucial role in managing renewable energy generation and load fluctuations by utilizing demand–response programmes (DRPs). This paper aims to provide a detailed overview of DRPs that help microgrid operators to keep costs and reliability within acceptable ranges. Additionally, this review paper provides a detailed economic load model for DRPs based on initial load, demand–response (DR) incentive, DR penalty and elasticity coefficients. This article also aims to guide researchers in identifying research gaps in DSM applications in microgrids by comparing various DSM schemes from different countries and regions in terms of DSM strategies, objective functions and optimization techniques. Furthermore, this study analyses the impact of DRPs on microgrid configuration from the perspective of utilities and customers, considering technical and economic performance metrics. As a result, it can be concluded that none of the studied cases provides models or guidelines for choosing appropriate DSM schemes that consider different consumer interests or load-type features. Furthermore, a few researchers have addressed the features of a modern price-based DR strategy, renewable generation-based dynamic pricing DR, which offers higher customer satisfaction than traditional DRPs.

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Analysis of Microgrid’s Operation Integrated to Renewable Energy and Electric Vehicles in View of Multiple Demand Response Programs

et al. 2022

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A suitable energy management scheme and integrating renewable energy resources (RERs) can significantly increase energy efficiency and the stability of future grids operation. This work modeled a household energy management comprising a microgrid (MG) system and demand response programs (DRPs). Residential loads with price-based tariffs are introduced to reduce peak load demands and energy costs. For incorporating the uncertainties in RERs, their stochastic nature is modeled with a probabilistic method. This paper proposes a joint optimization approach for the optimal planning and operation of grid-connected residential, rural MG integrated into renewable energy and electric vehicles (EVs) in view of DRPs. The investigation focuses on energy saving of residential homes under different DRPs and RERs integration. The EVs are integrated into MG by including photovoltaic (PV), wind turbine (WT), fuel cell (FC), and diesel engines (DEs). A multi-objective optimization problem has been formulated to minimize the operating cost, pollutant treatment cost, and carbon emissions cost defined as C1, C2, and C3, respectively. The load demand has been rescheduled because of three DRPs, i.e., critical peak pricing (CPP), real-time electricity pricing (RTEP), and time of use (TOU). Further, the EV load has also been analyzed in autonomous and coordinated charging strategies. Using a judgement matrix, the proposed multi-objective problem is transformed into a single-objective problem. The results of an artificial bee colony (ABC) algorithm are compared with the particle swarm optimization (PSO) algorithm. The simulation analysis was accomplished by employing ABC and PSO in MATLAB. The mathematical model of MG was implemented, and the effects of DRPs based MG were investigated under different numbers of EVs and load data to reduce different costs. To analyze the impact of DRPs, the residential, rural MG is implemented for 50 homes with a peak load of 5 kW each and EV load with 80 EVs and 700 EVs, respectively. The simulation results with different test cases are

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A Review on Demand Side Management Applications, Techniques, and Potential Energy and Cost saving

Cited by 6 publications

References 52 publications

Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm

Investigation of electricity load shifting under various tariff design using ant colony optimization algorithm

Impacts of multiple demand-side management strategies on microgrids planning: a literature survey

Analysis of Microgrid’s Operation Integrated to Renewable Energy and Electric Vehicles in View of Multiple Demand Response Programs

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