Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556615
S. S. Reddy, J. Momoh
This paper solves an optimization problem to minimize the emission due to carbon oxides, nitrogen oxides and sulfur oxides with cost as a constraint for a wind-solar-thermal power system. Wind and solar energy can reach significant penetration in modern power system and they will introduce additional uncertainties. Market price is mainly influenced by the generating fuel cost, as the wind and solar power being environmental friendly need to be utilized in optimum. But, the intermittency of wind and solar power affects the system operation. In such uncertain environment, the decision to be taken should be reasonable, economical and not risky. Under this regime the System Operator should be aware of wind and solar uncertainty and schedule the renewable power accordingly. This paper depicts the trade-off between the cost and emission minimization objectives for the wind-solar-thermal power system using the Self Adaptive Differential Algorithm (SADE). The effectiveness of the proposed approach is tested on IEEE 30 bus test system with wind farms located at different buses.
{"title":"Minimum emission dispatch in an integrated thermal and wind energy conservation system using self-adaptive differential evolution","authors":"S. S. Reddy, J. Momoh","doi":"10.1109/POWERAFRICA.2016.7556615","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556615","url":null,"abstract":"This paper solves an optimization problem to minimize the emission due to carbon oxides, nitrogen oxides and sulfur oxides with cost as a constraint for a wind-solar-thermal power system. Wind and solar energy can reach significant penetration in modern power system and they will introduce additional uncertainties. Market price is mainly influenced by the generating fuel cost, as the wind and solar power being environmental friendly need to be utilized in optimum. But, the intermittency of wind and solar power affects the system operation. In such uncertain environment, the decision to be taken should be reasonable, economical and not risky. Under this regime the System Operator should be aware of wind and solar uncertainty and schedule the renewable power accordingly. This paper depicts the trade-off between the cost and emission minimization objectives for the wind-solar-thermal power system using the Self Adaptive Differential Algorithm (SADE). The effectiveness of the proposed approach is tested on IEEE 30 bus test system with wind farms located at different buses.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124382345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556609
D. Mulongoti, M. Hakakole, A. Mulembo, K. Banda
The population of Zambia has rapidly grown in the past 56 years and so has the demand for electric power. Limited generation capacity and increased load shedding of hydroelectric power has influenced the shifting of attention to renewable energy sources. The Copperbelt province in Zambia is an important case study in the context of renewable energy because it possesses relatively high profusion of solar radiation, abundant bio-energy resources and moderate wind speeds. This paper discusses the design of an efficient system of sustainable renewable energy for domestic use and the estimated energy output from the ten districts in the province. The method of this study was collection of basic data for solar radiation, biomass (brewery waste, pigs, goats and cow manure) and wind speeds, followed by hybrid optimization simulation model using the software HOMER. The study is targeted at domestic and micro industrial applications. However, feeding power from these sources into the main grid can be considered as an option. The simulation model has been used to find out the most cost effective, renewable based energy system. It also presents results in an efficient and economical way for different numbers of households.
{"title":"Design and energy yield analysis of a hybrid renewable power system","authors":"D. Mulongoti, M. Hakakole, A. Mulembo, K. Banda","doi":"10.1109/POWERAFRICA.2016.7556609","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556609","url":null,"abstract":"The population of Zambia has rapidly grown in the past 56 years and so has the demand for electric power. Limited generation capacity and increased load shedding of hydroelectric power has influenced the shifting of attention to renewable energy sources. The Copperbelt province in Zambia is an important case study in the context of renewable energy because it possesses relatively high profusion of solar radiation, abundant bio-energy resources and moderate wind speeds. This paper discusses the design of an efficient system of sustainable renewable energy for domestic use and the estimated energy output from the ten districts in the province. The method of this study was collection of basic data for solar radiation, biomass (brewery waste, pigs, goats and cow manure) and wind speeds, followed by hybrid optimization simulation model using the software HOMER. The study is targeted at domestic and micro industrial applications. However, feeding power from these sources into the main grid can be considered as an option. The simulation model has been used to find out the most cost effective, renewable based energy system. It also presents results in an efficient and economical way for different numbers of households.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115457370","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556590
O. Okpako, H. Rajamani, P. Pillai, Ugonna Anuebunwa, K. Swarup
Recently, significant advances in renewable energy generation have made it possible to consider consumers as prosumers. However, with increase in embedded generation, storage of electrical energy in batteries, flywheels and supercapacitors has become important so as to better utilize the existing grid by helping smooth the peaks and troughs of renewable electricity generation, and also of demand. This has led to the possibility of controlling the times when stored energy from these storage units is fed back to the grid. In this paper we look at how energy resource sharing is achieved if these storage units are part of a virtual power plant. In a virtual power plant, these storage units become energy resources that need to be optimally scheduled over time so as to benefit both prosumer and the grid supplier. In this paper, a smart energy resources allocation algorithm is presented for a virtual power plants using genetic algorithms. It is also proposed that the cause of battery depreciation be accounted for in the allocation of discharge rates. The algorithm was tested under various pricing scenarios, depreciation cost, as well as constraint. The results are presented and discussed. Conclusions were drawn, and suggestion for further work was made.
{"title":"Investigation of an optimized energy resource allocation algorithm for a community based virtual power plant","authors":"O. Okpako, H. Rajamani, P. Pillai, Ugonna Anuebunwa, K. Swarup","doi":"10.1109/POWERAFRICA.2016.7556590","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556590","url":null,"abstract":"Recently, significant advances in renewable energy generation have made it possible to consider consumers as prosumers. However, with increase in embedded generation, storage of electrical energy in batteries, flywheels and supercapacitors has become important so as to better utilize the existing grid by helping smooth the peaks and troughs of renewable electricity generation, and also of demand. This has led to the possibility of controlling the times when stored energy from these storage units is fed back to the grid. In this paper we look at how energy resource sharing is achieved if these storage units are part of a virtual power plant. In a virtual power plant, these storage units become energy resources that need to be optimally scheduled over time so as to benefit both prosumer and the grid supplier. In this paper, a smart energy resources allocation algorithm is presented for a virtual power plants using genetic algorithms. It is also proposed that the cause of battery depreciation be accounted for in the allocation of discharge rates. The algorithm was tested under various pricing scenarios, depreciation cost, as well as constraint. The results are presented and discussed. Conclusions were drawn, and suggestion for further work was made.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132617942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556593
T. Matlokotsi, S. Chowdhury
This paper presents a comprehensive review on various impacts of DG integration on PQ and importance of proper grid-integration planning in light of maintaining PQ at the levels compliant with grid code requirements. It also focusses on the effective utilization of DGs for power quality enhancement in the utility grids. The proposed solutions essential for PQ enhancement in electricity networks with DG integration are also discussed. An overview of different issues associated with DG integration into utility networks has also been presented. Research areas pertaining to the improvement of PQ in grid-connected DGs are identified for further consideration with a focus on South Africa and the rest of African energy markets.
{"title":"Role of grid integration of distributed generation in power quality enhancement: A review","authors":"T. Matlokotsi, S. Chowdhury","doi":"10.1109/POWERAFRICA.2016.7556593","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556593","url":null,"abstract":"This paper presents a comprehensive review on various impacts of DG integration on PQ and importance of proper grid-integration planning in light of maintaining PQ at the levels compliant with grid code requirements. It also focusses on the effective utilization of DGs for power quality enhancement in the utility grids. The proposed solutions essential for PQ enhancement in electricity networks with DG integration are also discussed. An overview of different issues associated with DG integration into utility networks has also been presented. Research areas pertaining to the improvement of PQ in grid-connected DGs are identified for further consideration with a focus on South Africa and the rest of African energy markets.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130774600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556610
S. Rosen, Paranietharan Arunagirinathan, Iroshani Jayawardene, G. Venayagamoorthy
The integration of renewables, such as solar and wind power, introduces new challenges for existing multi-area power system operations. These variable generation sources are transforming the grid into a more dynamic system which significantly affects real-time operation. With dynamic generation, supply and demand will deviate frequently over time causing severe frequency fluctuations. The generators on the grid must respond rapidly to these fluctuations in order to stabilize the system and ultimately return to nominal frequency. In this paper, a 210 MW photovoltaic (PV) plant is integrated into a two-area four-machine power system. Due to the output variations of the PV plant, especially during cloudy conditions, the system frequency will significantly fluctuate. The objective of this paper is the optimal tuning of governors on synchronous generators in order to damp and mitigate frequency deviations as fast as possible. The governor parameters are tuned using a heuristic optimization method to provide the least number of frequency events and minimum frequency deviation with varying penetration levels of PV power. With optimally tuned governor parameters, a multi-area power system can operate reliably while maximizing the utilization of clean power generation sources.
{"title":"Optimal tuning of governors on synchronous generators in a multi-area power system with a large photovoltaic plant","authors":"S. Rosen, Paranietharan Arunagirinathan, Iroshani Jayawardene, G. Venayagamoorthy","doi":"10.1109/POWERAFRICA.2016.7556610","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556610","url":null,"abstract":"The integration of renewables, such as solar and wind power, introduces new challenges for existing multi-area power system operations. These variable generation sources are transforming the grid into a more dynamic system which significantly affects real-time operation. With dynamic generation, supply and demand will deviate frequently over time causing severe frequency fluctuations. The generators on the grid must respond rapidly to these fluctuations in order to stabilize the system and ultimately return to nominal frequency. In this paper, a 210 MW photovoltaic (PV) plant is integrated into a two-area four-machine power system. Due to the output variations of the PV plant, especially during cloudy conditions, the system frequency will significantly fluctuate. The objective of this paper is the optimal tuning of governors on synchronous generators in order to damp and mitigate frequency deviations as fast as possible. The governor parameters are tuned using a heuristic optimization method to provide the least number of frequency events and minimum frequency deviation with varying penetration levels of PV power. With optimally tuned governor parameters, a multi-area power system can operate reliably while maximizing the utilization of clean power generation sources.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"127 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124310829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556597
A. Densmore, M. Hanif
Recent years have seen increased interest in the use of off-grid solutions for electrification of rural areas. Off-grid electrification (such as solar home systems and micro-grids) are particularly applicable to the rural African context, where little infrastructure exists and in many regions grid extension is prohibitively expensive. To be economically viable, these systems must maximize the power delivered while ensuring the health of energy storage devices. Batteries in particular are a key weakness and typically the first major component to fail. In this paper we present an improved and simplified method for simulating the state of charge (SoC) and state of health (SoH) of lithium-ion batteries. SoC and SoH are predicted using the Extreme Learning Machine (ELM) algorithm. ELM is a state of the art single layer, feed-forward neural network that is characterized by its good generalized performance and fast learning speed. Real-life battery data from the NASA-AMES dataset provides the benchmark for evaluation of the ELM model.
{"title":"Modeling the condition of lithium ion batteries using the extreme learning machine","authors":"A. Densmore, M. Hanif","doi":"10.1109/POWERAFRICA.2016.7556597","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556597","url":null,"abstract":"Recent years have seen increased interest in the use of off-grid solutions for electrification of rural areas. Off-grid electrification (such as solar home systems and micro-grids) are particularly applicable to the rural African context, where little infrastructure exists and in many regions grid extension is prohibitively expensive. To be economically viable, these systems must maximize the power delivered while ensuring the health of energy storage devices. Batteries in particular are a key weakness and typically the first major component to fail. In this paper we present an improved and simplified method for simulating the state of charge (SoC) and state of health (SoH) of lithium-ion batteries. SoC and SoH are predicted using the Extreme Learning Machine (ELM) algorithm. ELM is a state of the art single layer, feed-forward neural network that is characterized by its good generalized performance and fast learning speed. Real-life battery data from the NASA-AMES dataset provides the benchmark for evaluation of the ELM model.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125414386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556604
B. Rawn, T. Nwachukwu, E. Cebeci
This paper presents the structure, tuning, and evaluation of a model for power system frequency response in Nigeria. We demonstrate that a 100MW utility scale solar farm is unlikely to degrade frequency performance, and we quantify the effect of several possible interventions to improve frequency regulation. The Nigerian system already experiences wide frequency variations due to steel mill loads and load rejection during storms, and this often necessitates manual intervention and load management. The model is one of several employed in grid-integration evaluations of proposed large utility-scale solar farms. The model is intended to support ongoing discussions on how grid code and market policies should specify ancillary services supplied by participants.
{"title":"Factors and options for improved frequency regulation: Case study of utility scale solar in Nigeria","authors":"B. Rawn, T. Nwachukwu, E. Cebeci","doi":"10.1109/POWERAFRICA.2016.7556604","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556604","url":null,"abstract":"This paper presents the structure, tuning, and evaluation of a model for power system frequency response in Nigeria. We demonstrate that a 100MW utility scale solar farm is unlikely to degrade frequency performance, and we quantify the effect of several possible interventions to improve frequency regulation. The Nigerian system already experiences wide frequency variations due to steel mill loads and load rejection during storms, and this often necessitates manual intervention and load management. The model is one of several employed in grid-integration evaluations of proposed large utility-scale solar farms. The model is intended to support ongoing discussions on how grid code and market policies should specify ancillary services supplied by participants.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127597426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556594
T. Ayodele, A. Ogunjuyigbe, O. Ojo
Increasing pressure from both customers and regulators to maintain and enhance service reliability, while at the same time controlling costs has put power utilities on their toes. In view of this, asset management has become an increasingly important aspect of power business strategies such that electricity companies can utilize assets to the fullest while maintaining system reliability. This paper discusses the transformer fleet in the most obvious region of the Nigerian Electricity Industry. 15 years data (1990-2004) on transformer failure was collected and collated for the transformer population of the region. Statistical means was used to express the age distribution of transformer for 10year spread (2007-2017) and identified that about 58.82% of these transformers will exceed the average technical life. It thus, present the need for a proper replacement/refurbishment expenditure profile for transformers over the next 10 years; development of a user friendly condition assessment and prioritization tool for field personnel and management reporting, such that the subsequent failure rate of transformers can be reduced.
{"title":"On the transmission power transformers in Nigeria: Lagos sub region as case study","authors":"T. Ayodele, A. Ogunjuyigbe, O. Ojo","doi":"10.1109/POWERAFRICA.2016.7556594","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556594","url":null,"abstract":"Increasing pressure from both customers and regulators to maintain and enhance service reliability, while at the same time controlling costs has put power utilities on their toes. In view of this, asset management has become an increasingly important aspect of power business strategies such that electricity companies can utilize assets to the fullest while maintaining system reliability. This paper discusses the transformer fleet in the most obvious region of the Nigerian Electricity Industry. 15 years data (1990-2004) on transformer failure was collected and collated for the transformer population of the region. Statistical means was used to express the age distribution of transformer for 10year spread (2007-2017) and identified that about 58.82% of these transformers will exceed the average technical life. It thus, present the need for a proper replacement/refurbishment expenditure profile for transformers over the next 10 years; development of a user friendly condition assessment and prioritization tool for field personnel and management reporting, such that the subsequent failure rate of transformers can be reduced.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117035739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556561
Amini Ntakirutimana, T. Ustun
Rapid advances in the control and distribution of electricity (electrical energy) is causing change in micro-grid technology. Similarly, the constant increase in the number of consumers is changing the management and control of power distribution. This paradigm change in power networks is also influenced by the fact that the world is re-thinking how energy should be controlled in order to avoid energy loss and limit accidents. Unlike traditional grids, microgrids have a unique power operation of distribute energy without controlling and communication. The focus of this paper is the implementation of smart interface subsystems to enhance control and communication in microgrids. In order to perform this task, smart interfaces are designed so that the operations can be done seamlessly, the overall power cost is reduced with and failures and accidents are reduced. This paper demonstrates smart grid interfaces designed for different components of the grid and their implementation of a prototype with a PIC 16F887 microcontroller.
{"title":"Implementation of smart interface subsystems for enhanced control and communication in smartgrids","authors":"Amini Ntakirutimana, T. Ustun","doi":"10.1109/POWERAFRICA.2016.7556561","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556561","url":null,"abstract":"Rapid advances in the control and distribution of electricity (electrical energy) is causing change in micro-grid technology. Similarly, the constant increase in the number of consumers is changing the management and control of power distribution. This paradigm change in power networks is also influenced by the fact that the world is re-thinking how energy should be controlled in order to avoid energy loss and limit accidents. Unlike traditional grids, microgrids have a unique power operation of distribute energy without controlling and communication. The focus of this paper is the implementation of smart interface subsystems to enhance control and communication in microgrids. In order to perform this task, smart interfaces are designed so that the operations can be done seamlessly, the overall power cost is reduced with and failures and accidents are reduced. This paper demonstrates smart grid interfaces designed for different components of the grid and their implementation of a prototype with a PIC 16F887 microcontroller.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117096911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-06-01DOI: 10.1109/POWERAFRICA.2016.7556568
Kashale Chimanga, J. Kalezhi, P. Mumba
In the recent past, Zambia has faced a critical power deficit due to low water levels in the Kariba Dam, which is a main source of electricity. This problem has negatively affected the economy. One way to mitigate this problem is by diversifying to renewable solar energy. Though the government is making efforts to diversify, the current photovoltaic (PV) systems are not efficient in managing the energy produced. In this paper we propose a system that applies the Best First Search algorithm to demand control in PV systems. The proposed system is capable of finding the best combination of household appliances that optimizes user priorities and limits the power consumed from the grid. This goal is achieved by using heuristic search techniques that are used in Artificial Intelligence. The Best First Search algorithm with appropriate heuristic function is employed to determine the best combination of these household appliances. The application of the algorithm limits the demand below the generation capacity of the PV system and also limit grid dependence by consumers.
{"title":"Application of best first search algorithm to demand control","authors":"Kashale Chimanga, J. Kalezhi, P. Mumba","doi":"10.1109/POWERAFRICA.2016.7556568","DOIUrl":"https://doi.org/10.1109/POWERAFRICA.2016.7556568","url":null,"abstract":"In the recent past, Zambia has faced a critical power deficit due to low water levels in the Kariba Dam, which is a main source of electricity. This problem has negatively affected the economy. One way to mitigate this problem is by diversifying to renewable solar energy. Though the government is making efforts to diversify, the current photovoltaic (PV) systems are not efficient in managing the energy produced. In this paper we propose a system that applies the Best First Search algorithm to demand control in PV systems. The proposed system is capable of finding the best combination of household appliances that optimizes user priorities and limits the power consumed from the grid. This goal is achieved by using heuristic search techniques that are used in Artificial Intelligence. The Best First Search algorithm with appropriate heuristic function is employed to determine the best combination of these household appliances. The application of the algorithm limits the demand below the generation capacity of the PV system and also limit grid dependence by consumers.","PeriodicalId":177444,"journal":{"name":"2016 IEEE PES PowerAfrica","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126800952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：